2024-01-06 09:41:26 +00:00
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< title > Scoping Review: Preliminary findings< / title >
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const rightElementObserver = visibleItemObserver(rightSideConflictEls);
const leftElementObserver = visibleItemObserver(leftSideConflictEls);
const hideOverlappedSidebars = () => {
marginScrollVisibility(toRegions(rightElementObserver.getVisibleEntries()));
sidebarScrollVisiblity(toRegions(leftElementObserver.getVisibleEntries()));
if (tocLeftScrollVisibility) {
tocLeftScrollVisibility(
toRegions(leftElementObserver.getVisibleEntries())
);
}
};
window.quartoToggleReader = () => {
// Applies a slow class (or removes it)
// to update the transition speed
const slowTransition = (slow) => {
const manageTransition = (id, slow) => {
const el = document.getElementById(id);
if (el) {
if (slow) {
el.classList.add("slow");
} else {
el.classList.remove("slow");
}
}
};
manageTransition("TOC", slow);
manageTransition("quarto-sidebar", slow);
};
const readerMode = !isReaderMode();
setReaderModeValue(readerMode);
// If we're entering reader mode, slow the transition
if (readerMode) {
slowTransition(readerMode);
}
highlightReaderToggle(readerMode);
hideOverlappedSidebars();
// If we're exiting reader mode, restore the non-slow transition
if (!readerMode) {
slowTransition(!readerMode);
}
};
const highlightReaderToggle = (readerMode) => {
const els = document.querySelectorAll(".quarto-reader-toggle");
if (els) {
els.forEach((el) => {
if (readerMode) {
el.classList.add("reader");
} else {
el.classList.remove("reader");
}
});
}
};
const setReaderModeValue = (val) => {
if (window.location.protocol !== "file:") {
window.localStorage.setItem("quarto-reader-mode", val);
} else {
localReaderMode = val;
}
};
const isReaderMode = () => {
if (window.location.protocol !== "file:") {
return window.localStorage.getItem("quarto-reader-mode") === "true";
} else {
return localReaderMode;
}
};
let localReaderMode = null;
const tocOpenDepthStr = tocEl?.getAttribute("data-toc-expanded");
const tocOpenDepth = tocOpenDepthStr ? Number(tocOpenDepthStr) : 1;
// Walk the TOC and collapse/expand nodes
// Nodes are expanded if:
// - they are top level
// - they have children that are 'active' links
// - they are directly below an link that is 'active'
const walk = (el, depth) => {
// Tick depth when we enter a UL
if (el.tagName === "UL") {
depth = depth + 1;
}
// It this is active link
let isActiveNode = false;
if (el.tagName === "A" & & el.classList.contains("active")) {
isActiveNode = true;
}
// See if there is an active child to this element
let hasActiveChild = false;
for (child of el.children) {
hasActiveChild = walk(child, depth) || hasActiveChild;
}
// Process the collapse state if this is an UL
if (el.tagName === "UL") {
if (tocOpenDepth === -1 & & depth > 1) {
el.classList.add("collapse");
} else if (
depth < = tocOpenDepth ||
hasActiveChild ||
prevSiblingIsActiveLink(el)
) {
el.classList.remove("collapse");
} else {
el.classList.add("collapse");
}
// untick depth when we leave a UL
depth = depth - 1;
}
return hasActiveChild || isActiveNode;
};
// walk the TOC and expand / collapse any items that should be shown
if (tocEl) {
walk(tocEl, 0);
updateActiveLink();
}
// Throttle the scroll event and walk peridiocally
window.document.addEventListener(
"scroll",
throttle(() => {
if (tocEl) {
updateActiveLink();
walk(tocEl, 0);
}
if (!isReaderMode()) {
hideOverlappedSidebars();
}
}, 5)
);
window.addEventListener(
"resize",
throttle(() => {
if (!isReaderMode()) {
hideOverlappedSidebars();
}
}, 10)
);
hideOverlappedSidebars();
highlightReaderToggle(isReaderMode());
});
// grouped tabsets
window.addEventListener("pageshow", (_event) => {
function getTabSettings() {
const data = localStorage.getItem("quarto-persistent-tabsets-data");
if (!data) {
localStorage.setItem("quarto-persistent-tabsets-data", "{}");
return {};
}
if (data) {
return JSON.parse(data);
}
}
function setTabSettings(data) {
localStorage.setItem(
"quarto-persistent-tabsets-data",
JSON.stringify(data)
);
}
function setTabState(groupName, groupValue) {
const data = getTabSettings();
data[groupName] = groupValue;
setTabSettings(data);
}
function toggleTab(tab, active) {
const tabPanelId = tab.getAttribute("aria-controls");
const tabPanel = document.getElementById(tabPanelId);
if (active) {
tab.classList.add("active");
tabPanel.classList.add("active");
} else {
tab.classList.remove("active");
tabPanel.classList.remove("active");
}
}
function toggleAll(selectedGroup, selectorsToSync) {
for (const [thisGroup, tabs] of Object.entries(selectorsToSync)) {
const active = selectedGroup === thisGroup;
for (const tab of tabs) {
toggleTab(tab, active);
}
}
}
function findSelectorsToSyncByLanguage() {
const result = {};
const tabs = Array.from(
document.querySelectorAll(`div[data-group] a[id^='tabset-']`)
);
for (const item of tabs) {
const div = item.parentElement.parentElement.parentElement;
const group = div.getAttribute("data-group");
if (!result[group]) {
result[group] = {};
}
const selectorsToSync = result[group];
const value = item.innerHTML;
if (!selectorsToSync[value]) {
selectorsToSync[value] = [];
}
selectorsToSync[value].push(item);
}
return result;
}
function setupSelectorSync() {
const selectorsToSync = findSelectorsToSyncByLanguage();
Object.entries(selectorsToSync).forEach(([group, tabSetsByValue]) => {
Object.entries(tabSetsByValue).forEach(([value, items]) => {
items.forEach((item) => {
item.addEventListener("click", (_event) => {
setTabState(group, value);
toggleAll(value, selectorsToSync[group]);
});
});
});
});
return selectorsToSync;
}
const selectorsToSync = setupSelectorSync();
for (const [group, selectedName] of Object.entries(getTabSettings())) {
const selectors = selectorsToSync[group];
// it's possible that stale state gives us empty selections, so we explicitly check here.
if (selectors) {
toggleAll(selectedName, selectors);
}
}
});
function throttle(func, wait) {
let waiting = false;
return function () {
if (!waiting) {
func.apply(this, arguments);
waiting = true;
setTimeout(function () {
waiting = false;
}, wait);
}
};
}
function nexttick(func) {
return setTimeout(func, 0);
}
< / script >
< script > / * *
* @popperjs/core v2.11.4 - MIT License
*/
!function(e,t){"object"==typeof exports& & "undefined"!=typeof module?t(exports):"function"==typeof define& & define.amd?define(["exports"],t):t((e="undefined"!=typeof globalThis?globalThis:e||self).Popper={})}(this,(function(e){"use strict";function t(e){if(null==e)return window;if("[object Window]"!==e.toString()){var t=e.ownerDocument;return t& & t.defaultView||window}return e}function n(e){return e instanceof t(e).Element||e instanceof Element}function r(e){return e instanceof t(e).HTMLElement||e instanceof HTMLElement}function o(e){return"undefined"!=typeof ShadowRoot& & (e instanceof t(e).ShadowRoot||e instanceof ShadowRoot)}var i=Math.max,a=Math.min,s=Math.round;function f(e,t){void 0===t&&(t=!1); var n=e.getBoundingClientRect(),o=1,i=1;if(r(e)& & t){var a=e.offsetHeight,f=e.offsetWidth;f>0& & (o=s(n.width)/f||1),a>0& & (i=s(n.height)/a||1)}return{width:n.width/o,height:n.height/i,top:n.top/i,right:n.right/o,bottom:n.bottom/i,left:n.left/o,x:n.left/o,y:n.top/i}}function c(e){var n=t(e);return{scrollLeft:n.pageXOffset,scrollTop:n.pageYOffset}}function p(e){return e?(e.nodeName||"").toLowerCase():null}function u(e){return((n(e)?e.ownerDocument:e.document)||window.document).documentElement}function l(e){return f(u(e)).left+c(e).scrollLeft}function d(e){return t(e).getComputedStyle(e)}function h(e){var t=d(e),n=t.overflow,r=t.overflowX,o=t.overflowY;return/auto|scroll|overlay|hidden/.test(n+o+r)}function m(e,n,o){void 0===o&&(o=!1); var i,a,d=r(n),m=r(n)& & function(e){var t=e.getBoundingClientRect(),n=s(t.width)/e.offsetWidth||1,r=s(t.height)/e.offsetHeight||1;return 1!==n||1!==r}(n),v=u(n),g=f(e,m),y={scrollLeft:0,scrollTop:0},b={x:0,y:0};return(d||!d& & !o)& & (("body"!==p(n)||h(v))& & (y=(i=n)!==t(i)& & r(i)?{scrollLeft:(a=i).scrollLeft,scrollTop:a.scrollTop}:c(i)),r(n)?((b=f(n,!0)).x+=n.clientLeft,b.y+=n.clientTop):v& & (b.x=l(v))),{x:g.left+y.scrollLeft-b.x,y:g.top+y.scrollTop-b.y,width:g.width,height:g.height}}function v(e){var t=f(e),n=e.offsetWidth,r=e.offsetHeight;return Math.abs(t.width-n)< =1& & (n=t.width),Math.abs(t.height-r)< =1& & (r=t.height),{x:e.offsetLeft,y:e.offsetTop,width:n,height:r}}function g(e){return"html"===p(e)?e:e.assignedSlot||e.parentNode||(o(e)?e.host:null)||u(e)}function y(e){return["html","body","#document"].indexOf(p(e))>=0?e.ownerDocument.body:r(e)& & h(e)?e:y(g(e))}function b(e,n){var r;void 0===n&&(n=[]); var o=y(e),i=o===(null==(r=e.ownerDocument)?void 0:r.body),a=t(o),s=i?[a].concat(a.visualViewport||[],h(o)?o:[]):o,f=n.concat(s);return i?f:f.concat(b(g(s)))}function x(e){return["table","td","th"].indexOf(p(e))>=0}function w(e){return r(e)& & "fixed"!==d(e).position?e.offsetParent:null}function O(e){for(var n=t(e),i=w(e);i&&x(i)&&"static"===d(i).position; )i=w(i);return i& & ("html"===p(i)||"body"===p(i)& & "static"===d(i).position)?n:i||function(e){var t=-1!==navigator.userAgent.toLowerCase().indexOf("firefox");if(-1!==navigator.userAgent.indexOf("Trident")& & r(e)& & "fixed"===d(e).position)return null;var n=g(e);for(o(n)&&(n=n.host); r(n)&&["html","body"].indexOf(p(n))<0; ){var i=d(n);if("none"!==i.transform||"none"!==i.perspective||"paint"===i.contain||-1!==["transform","perspective"].indexOf(i.willChange)||t& & "filter"===i.willChange||t& & i.filter& & "none"!==i.filter)return n;n=n.parentNode}return null}(e)||n}var j="top",E="bottom",D="right",A="left",L="auto",P=[j,E,D,A],M="start",k="end",W="viewport",B="popper",H=P.reduce((function(e,t){return e.concat([t+"-"+M,t+"-"+k])}),[]),T=[].concat(P,[L]).reduce((function(e,t){return e.concat([t,t+"-"+M,t+"-"+k])}),[]),R=["beforeRead","read","afterRead","beforeMain","main","afterMain","beforeWrite","write","afterWrite"];function S(e){var t=new Map,n=new Set,r=[];function o(e){n.add(e.name),[].concat(e.requires||[],e.requiresIfExists||[]).forEach((function(e){if(!n.has(e)){var r=t.get(e);r& & o(r)}})),r.push(e)}return e.forEach((function(e){t.set(e.name,e)})),e.forEach((function(e){n.has(e.name)||o(e)})),r}function C(e){return e.split("-")[0]}function q(e,t){var n=t.getRootNode&&t.getRootNode(); if(e.contains(t))return!0;if(n& & o(n)){var r=t;do{if(r&&e.isSameNode(r))return!0; r=r.parentNo
< / script >
< script > ! f u n c t i o n ( e , t ) { " o b j e c t " = = t y p e o f e x p o r t s & & " u n d e f i n e d " ! = t y p e o f m o d u l e ? m o d u l e . e x p o r t s = t ( r e q u i r e ( " @ p o p p e r j s / c o r e " ) ) : " f u n c t i o n " = = t y p e o f d e f i n e & & d e f i n e . a m d ? d e f i n e ( [ " @ p o p p e r j s / c o r e " ] , t ) : ( e = e | | s e l f ) . t i p p y = t ( e . P o p p e r ) } ( t h i s , ( f u n c t i o n ( e ) { " u s e s t r i c t " ; v a r t = { p a s s i v e : ! 0 , c a p t u r e : ! 0 } , n = f u n c t i o n ( ) { r e t u r n d o c u m e n t . b o d y } ; f u n c t i o n r ( e , t , n ) { i f ( A r r a y . i s A r r a y ( e ) ) { v a r r = e [ t ] ; r e t u r n n u l l = = r ? A r r a y . i s A r r a y ( n ) ? n [ t ] : n : r } r e t u r n e } f u n c t i o n o ( e , t ) { v a r n = { } . t o S t r i n g . c a l l ( e ) ; r e t u r n 0 = = = n . i n d e x O f ( " [ o b j e c t " ) & & n . i n d e x O f ( t + " ] " ) > - 1 } f u n c t i o n i ( e , t ) { r e t u r n " f u n c t i o n " = = t y p e o f e ? e . a p p l y ( v o i d 0 , t ) : e } f u n c t i o n a ( e , t ) { r e t u r n 0 = = = t ? e : f u n c t i o n ( r ) { c l e a r T i m e o u t ( n ) , n = s e t T i m e o u t ( ( f u n c t i o n ( ) { e ( r ) } ) , t ) } ; v a r n } f u n c t i o n s ( e , t ) { v a r n = O b j e c t . a s s i g n ( { } , e ) ; r e t u r n t . f o r E a c h ( ( f u n c t i o n ( e ) { d e l e t e n [ e ] } ) ) , n } f u n c t i o n u ( e ) { r e t u r n [ ] . c o n c a t ( e ) } f u n c t i o n c ( e , t ) { - 1 = = = e . i n d e x O f ( t ) & & e . p u s h ( t ) } f u n c t i o n p ( e ) { r e t u r n e . s p l i t ( " - " ) [ 0 ] } f u n c t i o n f ( e ) { r e t u r n [ ] . s l i c e . c a l l ( e ) } f u n c t i o n l ( e ) { r e t u r n O b j e c t . k e y s ( e ) . r e d u c e ( ( f u n c t i o n ( t , n ) { r e t u r n v o i d 0 ! = = e [ n ] & & ( t [ n ] = e [ n ] ) , t } ) , { } ) } f u n c t i o n d ( ) { r e t u r n d o c u m e n t . c r e a t e E l e m e n t ( " d i v " ) } f u n c t i o n v ( e ) { r e t u r n [ " E l e m e n t " , " F r a g m e n t " ] . s o m e ( ( f u n c t i o n ( t ) { r e t u r n o ( e , t ) } ) ) } f u n c t i o n m ( e ) { r e t u r n o ( e , " M o u s e E v e n t " ) } f u n c t i o n g ( e ) { r e t u r n ! ( ! e | | ! e . _ t i p p y | | e . _ t i p p y . r e f e r e n c e ! = = e ) } f u n c t i o n h ( e ) { r e t u r n v ( e ) ? [ e ] : f u n c t i o n ( e ) { r e t u r n o ( e , " N o d e L i s t " ) } ( e ) ? f ( e ) : A r r a y . i s A r r a y ( e ) ? e : f ( d o c u m e n t . q u e r y S e l e c t o r A l l ( e ) ) } f u n c t i o n b ( e , t ) { e . f o r E a c h ( ( f u n c t i o n ( e ) { e & & ( e . s t y l e . t r a n s i t i o n D u r a t i o n = t + " m s " ) } ) ) } f u n c t i o n y ( e , t ) { e . f o r E a c h ( ( f u n c t i o n ( e ) { e & & e . s e t A t t r i b u t e ( " d a t a - s t a t e " , t ) } ) ) } f u n c t i o n w ( e ) { v a r t , n = u ( e ) [ 0 ] ; r e t u r n n u l l ! = n & & n u l l ! = ( t = n . o w n e r D o c u m e n t ) & & t . b o d y ? n . o w n e r D o c u m e n t : d o c u m e n t } f u n c t i o n E ( e , t , n ) { v a r r = t + " E v e n t L i s t e n e r " ; [ " t r a n s i t i o n e n d " , " w e b k i t T r a n s i t i o n E n d " ] . f o r E a c h ( ( f u n c t i o n ( t ) { e [ r ] ( t , n ) } ) ) } f u n c t i o n O ( e , t ) { f o r ( v a r n = t ; n ; ) { v a r r ; i f ( e . c o n t a i n s ( n ) ) r e t u r n ! 0 ; n = n u l l = = n . g e t R o o t N o d e | | n u l l = = ( r = n . g e t R o o t N o d e ( ) ) ? v o i d 0 : r . h o s t } r e t u r n ! 1 } v a r x = { i s T o u c h : ! 1 } , C = 0 ; f u n c t i o n T ( ) { x . i s T o u c h | | ( x . i s T o u c h = ! 0 , w i n d o w . p e r f o r m a n c e & & d o c u m e n t . a d d E v e n t L i s t e n e r ( " m o u s e m o v e " , A ) ) } f u n c t i o n A ( ) { v a r e = p e r f o r m a n c e . n o w ( ) ; e - C < 2 0 & & ( x . i s T o u c h = ! 1 , d o c u m e n t . r e m o v e E v e n t L i s t e n e r ( " m o u s e m o v e " , A ) ) , C = e } f u n c t i o n L ( ) { v a r e = d o c u m e n t . a c t i v e E l e m e n t ; i f ( g ( e ) ) { v a r t = e . _ t i p p y ; e . b l u r & & ! t . s t a t e . i s V i s i b l e & & e . b l u r ( ) } } v a r D = ! ! ( " u n d e f i n e d " ! = t y p e o f w i n d o w & & " u n d e f i n e d " ! = t y p e o f d o c u m e n t ) & & ! ! w i n d o w . m s C r y p t o , R = O b j e c t . a s s i g n ( { a p p e n d T o : n , a r i a : { c o n t e n t : " a u t o " , e x p a n d e d : " a u t o " } , d e l a y : 0 , d u r a t i o n : [ 3 0 0 , 2 5 0 ] , g e t R e f e r e n c e C l i e n t R e c t : n u l l , h i d e O n C l i c k : ! 0 , i g n o r e A t t r i b u t e s : ! 1 , i n t e r a c t i v e : ! 1 , i n t e r a c t i v e B o r d e r : 2 , i n t e r a c t i v e D e b o u n c e : 0 , m o v e T r a n s i t i o n : " " , o f f s e t : [ 0 , 1 0 ] , o n A f t e r U p d a t e : f u n c t i o n ( ) { } , o n B e f o r e U p d a t e : f u n c t i o n ( ) { } , o n C r e a t e : f u n c t i o n ( ) { } , o n D e s t r o y : f u n c t i o n ( ) { } , o n H i d d e n : f u n c t i o n ( ) { } , o n H i d e : f u n c t i o n ( ) { } , o n M o u n t : f u n c t i o n ( ) { } , o n S h o w : f u n c t i o n ( ) { } , o n S h o w n : f u n c t i o n ( ) { } , o n T r i g g e r : f u n c t i o n ( ) { } , o n U n t r i g g e r : f u n c t i o n ( ) { } , o n C l i c k O u t s i d e : f u n c t i o n ( ) { } , p l a c e m e n t : " t o p " , p l u g i n s : [ ] , p o p p e r O p t i o n s : { } , r e n d e r : n u l l , s h o w O n C r e a t e : ! 1 , t o u c h : ! 0 , t r i g g e r : " m o u s e e n t e r f o c u s " , t r i g g e r T a r g e t : n u l l } , { a n i m a t e F i l l : ! 1 , f o l l o w C u r s o r : ! 1 , i n l i n e P o s i t i o n i n g : ! 1 , s t i c k y : ! 1 } , { a l l o w H T M L : ! 1 , a n i m a t i o n : " f a d e " , a r r o w : ! 0 , c o n t e n t : " " , i n e r t i a : ! 1 , m a x W i d t h : 3 5 0 , r o l e : " t o o l t i p " , t h e m e : " " , z I n d e x : 9 9 9 9 } ) , k = O b j e c t . k e y s ( R ) ; f u n c t i o n P ( e ) { v a r t = ( e . p l u g i n s | | [ ] ) . r e d u c e ( ( f u n c t i o n ( t , n ) { v a r r , o = n . n a m e , i = n . d e f a u l t V a l u e ; o & & ( t [ o ] = v o i d 0 ! = = e [ o ] ? e [ o ] : n u l l ! = ( r = R [ o ] ) ? r : i ) ; r e t u r n t } ) , { } ) ; r e t u r n O b j e c t . a s s i g n ( { } , e , t ) } f u n c t i o n j ( e , t ) { v a r n = O b j e c t . a s s i g n ( { } , t , { c o n t e n t : i ( t . c o n t e n t , [ e ] ) } , t . i g n o r e A t t r i b u t e s ? { } : f u n c t i o n ( e , t ) { r e t u r n ( t ? O b j e c t . k e y s ( P ( O b j e c t . a s s i g n ( { } , R , { p l u g i n s : t } ) ) ) : k ) . r e d u c e ( ( f u n c t i o n ( t , n ) { v a r r = ( e . g e t A t t r i b u t e ( " d a t a - t i p p y - " + n ) | | " " ) . t r i m ( ) ; i f ( ! r ) r e t u r n t ; i f ( " c o n t e n t " = = = n ) t [ n ] = r ; e l s e t r y { t [ n ] = J S O N . p a r s e ( r ) } c a t c h ( e ) { t [ n ] = r } r e t u r n t } ) , { } ) } ( e , t . p l u g i n s ) ) ; r e t u r n n . a r i a = O b j e c t . a s s i g n ( { } , R . a r i a , n . a r i a ) , n . a r i a = { e x p a n d e d : " a u t o " = = = n . a r i a . e x p a n d e d ? t . i n t e r a c t i v e : n . a r i a . e x p a n d e d , c o n t e n t : " a u t o " = = = n . a r i a . c o n t e n t ? t . i n t e r a c t i v e ? n u l l : " d e s c r i b e d b y " : n . a r i a . c o n t e n t } , n } f u n c t i o n M ( e , t ) { e . i n n e r H T M L = t } f u n c t i o n V ( e ) { v a r t = d ( ) ; r e t u r n ! 0 = = = e ? t . c l a s s N a m e = " t i p p y - a r r o w " : ( t . c l a s s N a m e = " t i p p y - s v g - a r r o w " , v ( e ) ? t . a p p e n d C h i l d ( e ) : M ( t , e ) ) , t } f u n c t i o n I ( e , t ) { v ( t . c o n t e n t ) ? ( M ( e , " " ) , e . a p p e n d C h i l d ( t . c o n
< / script >
< script > / / @ l i c e n s e m a g n e t : ? x t = u r n : b t i h : d 3 d 9 a 9 a 6 5 9 5 5 2 1 f 9 6 6 6 a 5 e 9 4 c c 8 3 0 d a b 8 3 b 6 5 6 9 9 & d n = e x p a t . t x t E x p a t
//
// AnchorJS - v4.3.1 - 2021-04-17
// https://www.bryanbraun.com/anchorjs/
// Copyright (c) 2021 Bryan Braun; Licensed MIT
//
// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699& dn=expat.txt Expat
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// @license-end< / script >
< style type = "text/css" > . tippy-box [ data-animation = fade ] [ data-state = hidden ] { opacity : 0 } [ data-tippy-root ] { max-width : calc ( 100 vw - 10 px ) } . tippy-box { position : relative ; background-color : #333 ; color : #fff ; border-radius : 4 px ; font-size : 14 px ; line-height : 1.4 ; white-space : normal ; outline : 0 ; transition-property : transform , visibility , opacity } . tippy-box [ data-placement ^ = top ] > . tippy-arrow { bottom : 0 } . tippy-box [ data-placement ^ = top ] > . tippy-arrow : before { bottom : -7 px ; left : 0 ; border-width : 8 px 8 px 0 ; border-top-color : initial ; transform-origin : center top } . tippy-box [ data-placement ^ = bottom ] > . tippy-arrow { top : 0 } . tippy-box [ data-placement ^ = bottom ] > . tippy-arrow : before { top : -7 px ; left : 0 ; border-width : 0 8 px 8 px ; border-bottom-color : initial ; transform-origin : center bottom } . tippy-box [ data-placement ^ = left ] > . tippy-arrow { right : 0 } . tippy-box [ data-placement ^ = left ] > . tippy-arrow : before { border-width : 8 px 0 8 px 8 px ; border-left-color : initial ; right : -7 px ; transform-origin : center left } . tippy-box [ data-placement ^ = right ] > . tippy-arrow { left : 0 } . tippy-box [ data-placement ^ = right ] > . tippy-arrow : before { left : -7 px ; border-width : 8 px 8 px 8 px 0 ; border-right-color : initial ; transform-origin : center right } . tippy-box [ data-inertia ] [ data-state = visible ] { transition-timing-function : cubic-bezier ( .54 , 1.5 , .38 , 1.11 ) } . tippy-arrow { width : 16 px ; height : 16 px ; color : #333 } . tippy-arrow : before { content : "" ; position : absolute ; border-color : transparent ; border-style : solid } . tippy-content { position : relative ; padding : 5 px 9 px ; z-index : 1 } < / style >
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< script > / * !
* Bootstrap v5.1.3 (https://getbootstrap.com/)
* Copyright 2011-2021 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)
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< style type = "text/css" > @ f o n t - f a c e {
font-display: block;
font-family: "bootstrap-icons";
src: url(data:font/woff;base64,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
}
.bi::before,
[class^="bi-"]::before,
[class*=" bi-"]::before {
display: inline-block;
font-family: bootstrap-icons !important;
font-style: normal;
font-weight: normal !important;
font-variant: normal;
text-transform: none;
line-height: 1;
vertical-align: -.125em;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
.bi-123::before { content: "\f67f"; }
.bi-alarm-fill::before { content: "\f101"; }
.bi-alarm::before { content: "\f102"; }
.bi-align-bottom::before { content: "\f103"; }
.bi-align-center::before { content: "\f104"; }
.bi-align-end::before { content: "\f105"; }
.bi-align-middle::before { content: "\f106"; }
.bi-align-start::before { content: "\f107"; }
.bi-align-top::before { content: "\f108"; }
.bi-alt::before { content: "\f109"; }
.bi-app-indicator::before { content: "\f10a"; }
.bi-app::before { content: "\f10b"; }
.bi-archive-fill::before { content: "\f10c"; }
.bi-archive::before { content: "\f10d"; }
.bi-arrow-90deg-down::before { content: "\f10e"; }
.bi-arrow-90deg-left::before { content: "\f10f"; }
.bi-arrow-90deg-right::before { content: "\f110"; }
.bi-arrow-90deg-up::before { content: "\f111"; }
.bi-arrow-bar-down::before { content: "\f112"; }
.bi-arrow-bar-left::before { content: "\f113"; }
.bi-arrow-bar-right::before { content: "\f114"; }
.bi-arrow-bar-up::before { content: "\f115"; }
.bi-arrow-clockwise::before { content: "\f116"; }
.bi-arrow-counterclockwise::before { content: "\f117"; }
.bi-arrow-down-circle-fill::before { content: "\f118"; }
.bi-arrow-down-circle::before { content: "\f119"; }
.bi-arrow-down-left-circle-fill::before { content: "\f11a"; }
.bi-arrow-down-left-circle::before { content: "\f11b"; }
.bi-arrow-down-left-square-fill::before { content: "\f11c"; }
.bi-arrow-down-left-square::before { content: "\f11d"; }
.bi-arrow-down-left::before { content: "\f11e"; }
.bi-arrow-down-right-circle-fill::before { content: "\f11f"; }
.bi-arrow-down-right-circle::before { content: "\f120"; }
.bi-arrow-down-right-square-fill::before { content: "\f121"; }
.bi-arrow-down-right-square::before { content: "\f122"; }
.bi-arrow-down-right::before { content: "\f123"; }
.bi-arrow-down-short::before { content: "\f124"; }
.bi-arrow-down-square-fill::before { content: "\f125"; }
.bi-arrow-down-square::before { content: "\f126"; }
.bi-arrow-down-up::before { content: "\f127"; }
.bi-arrow-down::before { content: "\f128"; }
.bi-arrow-left-circle-fill::before { content: "\f129"; }
.bi-arrow-left-circle::before { content: "\f12a"; }
.bi-arrow-left-right::before { content: "\f12b"; }
.bi-arrow-left-short::before { content: "\f12c"; }
.bi-arrow-left-square-fill::before { content: "\f12d"; }
.bi-arrow-left-square::before { content: "\f12e"; }
.bi-arrow-left::before { content: "\f12f"; }
.bi-arrow-repeat::before { content: "\f130"; }
.bi-arrow-return-left::before { content: "\f131"; }
.bi-arrow-return-right::before { content: "\f132"; }
.bi-arrow-right-circle-fill::before { content: "\f133"; }
.bi-arrow-right-circle::before { content: "\f134"; }
.bi-arrow-right-short::before { content: "\f135"; }
.bi-arrow-right-square-fill::before { content: "\f136"; }
.bi-arrow-right-square::before { content: "\f137"; }
.bi-arrow-right::before { content: "\f138"; }
.bi-arrow-up-circle-fill::before { content: "\f139"; }
.bi-arrow-up-circle::before { content: "\f13a"; }
.bi-arrow-up-left-circle-fill::before { content: "\f13b"; }
.bi-arrow-up-left-circle::before { content: "\f13c"; }
.bi-arrow-up-left-square-fill::before { content: "\f13d"; }
.bi-arrow-up-left-square::before { content: "\f13e"; }
.bi-arrow-up-left::before { content: "\f13f"; }
.bi-arrow-up-right-circle-fill::before { content: "\f140"; }
.bi-arrow-up-right-circle::before { content: "\f141"; }
.bi-arrow-up-right-square-fill::before { content: "\f142"; }
.bi-arrow-up-right-square::before { content: "\f143"; }
.bi-arrow-up-right::before { content: "\f144"; }
.bi-arrow-up-short::before { content: "\f145"; }
.bi-arrow-up-square-fill::before { content: "\f146"; }
.bi-arrow-up-square::before { content: "\f147"; }
.bi-arrow-up::before { content: "\f148"; }
.bi-arrows-angle-contract::before { content: "\f149"; }
.bi-arrows-angle-expand::before { content: "\f14a"; }
.bi-arrows-collapse::before { content: "\f14b"; }
.bi-arrows-expand::before { content: "\f14c"; }
.bi-arrows-fullscreen::before { content: "\f14d"; }
.bi-arrows-move::before { content: "\f14e"; }
.bi-aspect-ratio-fill::before { content: "\f14f"; }
.bi-aspect-ratio::before { content: "\f150"; }
.bi-asterisk::before { content: "\f151"; }
.bi-at::before { content: "\f152"; }
.bi-award-fill::before { content: "\f153"; }
.bi-award::before { content: "\f154"; }
.bi-back::before { content: "\f155"; }
.bi-backspace-fill::before { content: "\f156"; }
.bi-backspace-reverse-fill::before { content: "\f157"; }
.bi-backspace-reverse::before { content: "\f158"; }
.bi-backspace::before { content: "\f159"; }
.bi-badge-3d-fill::before { content: "\f15a"; }
.bi-badge-3d::before { content: "\f15b"; }
.bi-badge-4k-fill::before { content: "\f15c"; }
.bi-badge-4k::before { content: "\f15d"; }
.bi-badge-8k-fill::before { content: "\f15e"; }
.bi-badge-8k::before { content: "\f15f"; }
.bi-badge-ad-fill::before { content: "\f160"; }
.bi-badge-ad::before { content: "\f161"; }
.bi-badge-ar-fill::before { content: "\f162"; }
.bi-badge-ar::before { content: "\f163"; }
.bi-badge-cc-fill::before { content: "\f164"; }
.bi-badge-cc::before { content: "\f165"; }
.bi-badge-hd-fill::before { content: "\f166"; }
.bi-badge-hd::before { content: "\f167"; }
.bi-badge-tm-fill::before { content: "\f168"; }
.bi-badge-tm::before { content: "\f169"; }
.bi-badge-vo-fill::before { content: "\f16a"; }
.bi-badge-vo::before { content: "\f16b"; }
.bi-badge-vr-fill::before { content: "\f16c"; }
.bi-badge-vr::before { content: "\f16d"; }
.bi-badge-wc-fill::before { content: "\f16e"; }
.bi-badge-wc::before { content: "\f16f"; }
.bi-bag-check-fill::before { content: "\f170"; }
.bi-bag-check::before { content: "\f171"; }
.bi-bag-dash-fill::before { content: "\f172"; }
.bi-bag-dash::before { content: "\f173"; }
.bi-bag-fill::before { content: "\f174"; }
.bi-bag-plus-fill::before { content: "\f175"; }
.bi-bag-plus::before { content: "\f176"; }
.bi-bag-x-fill::before { content: "\f177"; }
.bi-bag-x::before { content: "\f178"; }
.bi-bag::before { content: "\f179"; }
.bi-bar-chart-fill::before { content: "\f17a"; }
.bi-bar-chart-line-fill::before { content: "\f17b"; }
.bi-bar-chart-line::before { content: "\f17c"; }
.bi-bar-chart-steps::before { content: "\f17d"; }
.bi-bar-chart::before { content: "\f17e"; }
.bi-basket-fill::before { content: "\f17f"; }
.bi-basket::before { content: "\f180"; }
.bi-basket2-fill::before { content: "\f181"; }
.bi-basket2::before { content: "\f182"; }
.bi-basket3-fill::before { content: "\f183"; }
.bi-basket3::before { content: "\f184"; }
.bi-battery-charging::before { content: "\f185"; }
.bi-battery-full::before { content: "\f186"; }
.bi-battery-half::before { content: "\f187"; }
.bi-battery::before { content: "\f188"; }
.bi-bell-fill::before { content: "\f189"; }
.bi-bell::before { content: "\f18a"; }
.bi-bezier::before { content: "\f18b"; }
.bi-bezier2::before { content: "\f18c"; }
.bi-bicycle::before { content: "\f18d"; }
.bi-binoculars-fill::before { content: "\f18e"; }
.bi-binoculars::before { content: "\f18f"; }
.bi-blockquote-left::before { content: "\f190"; }
.bi-blockquote-right::before { content: "\f191"; }
.bi-book-fill::before { content: "\f192"; }
.bi-book-half::before { content: "\f193"; }
.bi-book::before { content: "\f194"; }
.bi-bookmark-check-fill::before { content: "\f195"; }
.bi-bookmark-check::before { content: "\f196"; }
.bi-bookmark-dash-fill::before { content: "\f197"; }
.bi-bookmark-dash::before { content: "\f198"; }
.bi-bookmark-fill::before { content: "\f199"; }
.bi-bookmark-heart-fill::before { content: "\f19a"; }
.bi-bookmark-heart::before { content: "\f19b"; }
.bi-bookmark-plus-fill::before { content: "\f19c"; }
.bi-bookmark-plus::before { content: "\f19d"; }
.bi-bookmark-star-fill::before { content: "\f19e"; }
.bi-bookmark-star::before { content: "\f19f"; }
.bi-bookmark-x-fill::before { content: "\f1a0"; }
.bi-bookmark-x::before { content: "\f1a1"; }
.bi-bookmark::before { content: "\f1a2"; }
.bi-bookmarks-fill::before { content: "\f1a3"; }
.bi-bookmarks::before { content: "\f1a4"; }
.bi-bookshelf::before { content: "\f1a5"; }
.bi-bootstrap-fill::before { content: "\f1a6"; }
.bi-bootstrap-reboot::before { content: "\f1a7"; }
.bi-bootstrap::before { content: "\f1a8"; }
.bi-border-all::before { content: "\f1a9"; }
.bi-border-bottom::before { content: "\f1aa"; }
.bi-border-center::before { content: "\f1ab"; }
.bi-border-inner::before { content: "\f1ac"; }
.bi-border-left::before { content: "\f1ad"; }
.bi-border-middle::before { content: "\f1ae"; }
.bi-border-outer::before { content: "\f1af"; }
.bi-border-right::before { content: "\f1b0"; }
.bi-border-style::before { content: "\f1b1"; }
.bi-border-top::before { content: "\f1b2"; }
.bi-border-width::before { content: "\f1b3"; }
.bi-border::before { content: "\f1b4"; }
.bi-bounding-box-circles::before { content: "\f1b5"; }
.bi-bounding-box::before { content: "\f1b6"; }
.bi-box-arrow-down-left::before { content: "\f1b7"; }
.bi-box-arrow-down-right::before { content: "\f1b8"; }
.bi-box-arrow-down::before { content: "\f1b9"; }
.bi-box-arrow-in-down-left::before { content: "\f1ba"; }
.bi-box-arrow-in-down-right::before { content: "\f1bb"; }
.bi-box-arrow-in-down::before { content: "\f1bc"; }
.bi-box-arrow-in-left::before { content: "\f1bd"; }
.bi-box-arrow-in-right::before { content: "\f1be"; }
.bi-box-arrow-in-up-left::before { content: "\f1bf"; }
.bi-box-arrow-in-up-right::before { content: "\f1c0"; }
.bi-box-arrow-in-up::before { content: "\f1c1"; }
.bi-box-arrow-left::before { content: "\f1c2"; }
.bi-box-arrow-right::before { content: "\f1c3"; }
.bi-box-arrow-up-left::before { content: "\f1c4"; }
.bi-box-arrow-up-right::before { content: "\f1c5"; }
.bi-box-arrow-up::before { content: "\f1c6"; }
.bi-box-seam::before { content: "\f1c7"; }
.bi-box::before { content: "\f1c8"; }
.bi-braces::before { content: "\f1c9"; }
.bi-bricks::before { content: "\f1ca"; }
.bi-briefcase-fill::before { content: "\f1cb"; }
.bi-briefcase::before { content: "\f1cc"; }
.bi-brightness-alt-high-fill::before { content: "\f1cd"; }
.bi-brightness-alt-high::before { content: "\f1ce"; }
.bi-brightness-alt-low-fill::before { content: "\f1cf"; }
.bi-brightness-alt-low::before { content: "\f1d0"; }
.bi-brightness-high-fill::before { content: "\f1d1"; }
.bi-brightness-high::before { content: "\f1d2"; }
.bi-brightness-low-fill::before { content: "\f1d3"; }
.bi-brightness-low::before { content: "\f1d4"; }
.bi-broadcast-pin::before { content: "\f1d5"; }
.bi-broadcast::before { content: "\f1d6"; }
.bi-brush-fill::before { content: "\f1d7"; }
.bi-brush::before { content: "\f1d8"; }
.bi-bucket-fill::before { content: "\f1d9"; }
.bi-bucket::before { content: "\f1da"; }
.bi-bug-fill::before { content: "\f1db"; }
.bi-bug::before { content: "\f1dc"; }
.bi-building::before { content: "\f1dd"; }
.bi-bullseye::before { content: "\f1de"; }
.bi-calculator-fill::before { content: "\f1df"; }
.bi-calculator::before { content: "\f1e0"; }
.bi-calendar-check-fill::before { content: "\f1e1"; }
.bi-calendar-check::before { content: "\f1e2"; }
.bi-calendar-date-fill::before { content: "\f1e3"; }
.bi-calendar-date::before { content: "\f1e4"; }
.bi-calendar-day-fill::before { content: "\f1e5"; }
.bi-calendar-day::before { content: "\f1e6"; }
.bi-calendar-event-fill::before { content: "\f1e7"; }
.bi-calendar-event::before { content: "\f1e8"; }
.bi-calendar-fill::before { content: "\f1e9"; }
.bi-calendar-minus-fill::before { content: "\f1ea"; }
.bi-calendar-minus::before { content: "\f1eb"; }
.bi-calendar-month-fill::before { content: "\f1ec"; }
.bi-calendar-month::before { content: "\f1ed"; }
.bi-calendar-plus-fill::before { content: "\f1ee"; }
.bi-calendar-plus::before { content: "\f1ef"; }
.bi-calendar-range-fill::before { content: "\f1f0"; }
.bi-calendar-range::before { content: "\f1f1"; }
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.bi-sign-merge-left-fill::before { content: "\f85b"; }
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.bi-sign-merge-right-fill::before { content: "\f85d"; }
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.bi-sign-no-left-turn-fill::before { content: "\f85f"; }
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.bi-sign-railroad-fill::before { content: "\f865"; }
.bi-sign-railroad::before { content: "\f866"; }
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.bi-building-dash::before { content: "\f869"; }
.bi-building-down::before { content: "\f86a"; }
.bi-building-exclamation::before { content: "\f86b"; }
.bi-building-fill-add::before { content: "\f86c"; }
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.bi-building-fill-dash::before { content: "\f86e"; }
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.bi-building-fill-exclamation::before { content: "\f870"; }
.bi-building-fill-gear::before { content: "\f871"; }
.bi-building-fill-lock::before { content: "\f872"; }
.bi-building-fill-slash::before { content: "\f873"; }
.bi-building-fill-up::before { content: "\f874"; }
.bi-building-fill-x::before { content: "\f875"; }
.bi-building-fill::before { content: "\f876"; }
.bi-building-gear::before { content: "\f877"; }
.bi-building-lock::before { content: "\f878"; }
.bi-building-slash::before { content: "\f879"; }
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.bi-buildings-fill::before { content: "\f87c"; }
.bi-buildings::before { content: "\f87d"; }
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.bi-person-up::before { content: "\f8aa"; }
.bi-scooter::before { content: "\f8ab"; }
.bi-taxi-front-fill::before { content: "\f8ac"; }
.bi-taxi-front::before { content: "\f8ad"; }
.bi-amd::before { content: "\f8ae"; }
.bi-database-add::before { content: "\f8af"; }
.bi-database-check::before { content: "\f8b0"; }
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.bi-database-down::before { content: "\f8b2"; }
.bi-database-exclamation::before { content: "\f8b3"; }
.bi-database-fill-add::before { content: "\f8b4"; }
.bi-database-fill-check::before { content: "\f8b5"; }
.bi-database-fill-dash::before { content: "\f8b6"; }
.bi-database-fill-down::before { content: "\f8b7"; }
.bi-database-fill-exclamation::before { content: "\f8b8"; }
.bi-database-fill-gear::before { content: "\f8b9"; }
.bi-database-fill-lock::before { content: "\f8ba"; }
.bi-database-fill-slash::before { content: "\f8bb"; }
.bi-database-fill-up::before { content: "\f8bc"; }
.bi-database-fill-x::before { content: "\f8bd"; }
.bi-database-fill::before { content: "\f8be"; }
.bi-database-gear::before { content: "\f8bf"; }
.bi-database-lock::before { content: "\f8c0"; }
.bi-database-slash::before { content: "\f8c1"; }
.bi-database-up::before { content: "\f8c2"; }
.bi-database-x::before { content: "\f8c3"; }
.bi-database::before { content: "\f8c4"; }
.bi-houses-fill::before { content: "\f8c5"; }
.bi-houses::before { content: "\f8c6"; }
.bi-nvidia::before { content: "\f8c7"; }
.bi-person-vcard-fill::before { content: "\f8c8"; }
.bi-person-vcard::before { content: "\f8c9"; }
.bi-sina-weibo::before { content: "\f8ca"; }
.bi-tencent-qq::before { content: "\f8cb"; }
.bi-wikipedia::before { content: "\f8cc"; }
< / style >
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//# sourceMappingURL=mermaid.min.js.map< / script >
< script > / / m e r m a i d - i n i t . j s
// Initializes the quarto-mermaid JS runtime
//
// Copyright (C) 2022 Posit Software, PBC
/**
* String.prototype.replaceAll() polyfill
* https://gomakethings.com/how-to-replace-a-section-of-a-string-with-another-one-with-vanilla-js/
* @author Chris Ferdinandi
* @license MIT
*/
if (!String.prototype.replaceAll) {
String.prototype.replaceAll = function (str, newStr) {
// If a regex pattern
if (
Object.prototype.toString.call(str).toLowerCase() === "[object regexp]"
) {
return this.replace(str, newStr);
}
// If a string
return this.replace(new RegExp(str, "g"), newStr);
};
}
const mermaidOpts = {
startOnLoad: false,
flowchart: {
htmlLabels: "false",
},
};
// this CSS is adapted from
// mkdocs-material
// Copyright (c) 2016-2022 Martin Donath < martin.donath @ squidfunk . com >
const defaultCSS =
'.label text {fill: var(--mermaid-fg-color);}.node circle, .node ellipse, .node path, .node polygon, .node rect {fill: var(--mermaid-node-bg-color);stroke: var(--mermaid-node-fg-color);}marker {fill: var(--mermaid-edge-color) !important;}.edgeLabel .label rect {fill: #0000;}.label {color: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.label foreignObject {line-height: normal;overflow: visible;}.label div .edgeLabel {color: var(--mermaid-label-fg-color);}.edgeLabel, .edgeLabel rect, .label div .edgeLabel {background-color: var(--mermaid-label-bg-color);}.edgeLabel, .edgeLabel rect {fill: var(--mermaid-label-bg-color);color: var(--mermaid-edge-color);}.edgePath .path, .flowchart-link {stroke: var(--mermaid-edge-color);}.edgePath .arrowheadPath {fill: var(--mermaid-edge-color);stroke: none;}.cluster rect {fill: var(--mermaid-fg-color--lightest);stroke: var(--mermaid-fg-color--lighter);}.cluster span {color: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}defs #flowchart-circleEnd, defs #flowchart-circleStart, defs #flowchart-crossEnd, defs #flowchart-crossStart, defs #flowchart-pointEnd, defs #flowchart-pointStart {stroke: none;}g.classGroup line, g.classGroup rect {fill: var(--mermaid-node-bg-color);stroke: var(--mermaid-node-fg-color);}g.classGroup text {fill: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.classLabel .box {fill: var(--mermaid-label-bg-color);background-color: var(--mermaid-label-bg-color);opacity: 1;}.classLabel .label {fill: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.node .divider {stroke: var(--mermaid-node-fg-color);}.relation {stroke: var(--mermaid-edge-color);}.cardinality {fill: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.cardinality text {fill: inherit !important;}defs #classDiagram-compositionEnd, defs #classDiagram-compositionStart, defs #classDiagram-dependencyEnd, defs #classDiagram-dependencyStart, defs #classDiagram-extensionEnd, defs #classDiagram-extensionStart {fill: var(--mermaid-edge-color) !important;stroke: var(--mermaid-edge-color) !important;}defs #classDiagram-aggregationEnd, defs #classDiagram-aggregationStart {fill: var(--mermaid-label-bg-color) !important;stroke: var(--mermaid-edge-color) !important;}g.stateGroup rect {fill: var(--mermaid-node-bg-color);stroke: var(--mermaid-node-fg-color);}g.stateGroup .state-title {fill: var(--mermaid-label-fg-color) !important;font-family: var(--mermaid-font-family);}g.stateGroup .composit {fill: var(--mermaid-label-bg-color);}.nodeLabel {color: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.node circle.state-end, .node circle.state-start, .start-state {fill: var(--mermaid-edge-color);stroke: none;}.end-state-inner, .end-state-outer {fill: var(--mermaid-edge-color);}.end-state-inner, .node circle.state-end {stroke: var(--mermaid-label-bg-color);}.transition {stroke: var(--mermaid-edge-color);}[id^="state-fork"] rect, [id^="state-join"] rect {fill: var(--mermaid-edge-color) !important;stroke: none !important;}.statediagram-cluster.statediagram-cluster .inner {fill: var(--mermaid-bg-color);}.statediagram-cluster rect {fill: var(--mermaid-node-bg-color);stroke: var(--mermaid-node-fg-color);}.statediagram-state rect.divider {fill: var(--mermaid-fg-color--lightest);stroke: var(--mermaid-fg-color--lighter);}defs #statediagram-barbEnd {stroke: var(--mermaid-edge-color);}.entityBox {fill: var(--mermaid-label-bg-color);stroke: var(--mermaid-node-fg-color);}.entityLabel {fill: var(--mermaid-label-fg-color);font-family: var(--mermaid-font-family);}.relationshipLabelBox {fill: var(--mermaid-label-bg-color);fill-opacity: 1;background-color: var(--mermaid-label-bg-color);opacity: 1;}.relationshipLabel {fill: var(--mermaid-label-fg-color);}.relationshipLine {stroke: var(--mermaid-edge-color);}defs #ONE_OR_MORE_END *, defs #ONE_OR_MORE_START *, defs #ONLY_ONE_END *, defs #ONLY_ONE_START *, defs #ZERO_OR_MORE_END *, defs #ZERO_OR_MORE_START *, defs #ZERO_OR_ONE_END *, defs #ZERO_OR_ONE_START * {stroke: va
const mermaidThemeEl = document.querySelector('meta[name="mermaid-theme"]');
if (mermaidThemeEl) {
mermaidOpts.theme = mermaidThemeEl.content;
} else {
mermaidOpts.themeCSS = defaultCSS;
}
mermaid.initialize(mermaidOpts);
const _quartoMermaid = {
// NB: there's effectively a copy of this function
// in `core/svg.ts`.
// if you change something here, you must keep it consistent there as well.
setSvgSize(svg) {
const { widthInPoints, heightInPoints, explicitHeight, explicitWidth } =
this.resolveSize(svg);
if (explicitWidth & & explicitHeight) {
svg.setAttribute("width", widthInPoints);
svg.setAttribute("height", heightInPoints);
svg.style.maxWidth = null; // remove mermaid's default max-width
} else {
if (explicitWidth) {
svg.style.maxWidth = `${widthInPoints}px`;
}
if (explicitHeight) {
svg.style.maxHeight = `${heightInPoints}px`;
}
}
},
// NB: there's effectively a copy of this function
// in `core/svg.ts`.
// if you change something here, you must keep it consistent there as well.
makeResponsive(svg) {
const width = svg.getAttribute("width");
if (width === null) {
throw new Error("Couldn't find SVG width");
}
const numWidth = Number(width.slice(0, -2));
if (numWidth > 650) {
changed = true;
svg.setAttribute("width", "100%");
svg.removeAttribute("height");
}
},
// NB: there's effectively a copy of this function
// in `core/svg.ts`.
// if you change something here, you must keep it consistent there as well.
fixupAlignment(svg, align) {
let style = svg.getAttribute("style") || "";
switch (align) {
case "left":
style = `${style}; display: block; margin: auto auto auto 0`;
break;
case "right":
style = `${style}; display: block; margin: auto 0 auto auto`;
break;
case "center":
style = `${style}; display: block; margin: auto auto auto auto`;
break;
}
svg.setAttribute("style", style);
},
resolveOptions(svgEl) {
return svgEl.parentElement.parentElement.parentElement.parentElement
.dataset;
},
// NB: there's effectively a copy of this function
// in our mermaid runtime in `core/svg.ts`.
// if you change something here, you must keep it consistent there as well.
resolveSize(svgEl) {
const inInches = (size) => {
if (size.endsWith("in")) {
return Number(size.slice(0, -2));
}
if (size.endsWith("pt") || size.endsWith("px")) {
// assume 96 dpi for now
return Number(size.slice(0, -2)) / 96;
}
return Number(size);
};
// these are figWidth and figHeight on purpose,
// because data attributes are translated to camelCase by the DOM API
const kFigWidth = "figWidth",
kFigHeight = "figHeight";
const options = this.resolveOptions(svgEl);
const width = svgEl.getAttribute("width");
const height = svgEl.getAttribute("height");
if (!width || !height) {
// attempt to resolve figure dimensions via viewBox
throw new Error("Internal error: couldn't find figure dimensions");
}
const getViewBox = () => {
const vb = svgEl.attributes.getNamedItem("viewBox").value; // do it the roundabout way so that viewBox isn't dropped by deno_dom and text/html
if (!vb) return undefined;
const lst = vb.trim().split(" ").map(Number);
if (lst.length !== 4) return undefined;
if (lst.some(isNaN)) return undefined;
return lst;
};
let svgWidthInInches, svgHeightInInches;
if (
(width.slice(0, -2) === "pt" & & height.slice(0, -2) === "pt") ||
(width.slice(0, -2) === "px" & & height.slice(0, -2) === "px") ||
(!isNaN(Number(width)) & & !isNaN(Number(height)))
) {
// we assume 96 dpi which is generally what seems to be used.
svgWidthInInches = Number(width.slice(0, -2)) / 96;
svgHeightInInches = Number(height.slice(0, -2)) / 96;
}
const viewBox = getViewBox();
if (viewBox !== undefined) {
// assume width and height come from viewbox.
const [_mx, _my, vbWidth, vbHeight] = viewBox;
svgWidthInInches = vbWidth / 96;
svgHeightInInches = vbHeight / 96;
} else {
throw new Error(
"Internal Error: Couldn't resolve width and height of SVG"
);
}
const svgWidthOverHeight = svgWidthInInches / svgHeightInInches;
let widthInInches, heightInInches;
if (options[kFigWidth] & & options[kFigHeight]) {
// both were prescribed, so just go with them
widthInInches = inInches(String(options[kFigWidth]));
heightInInches = inInches(String(options[kFigHeight]));
} else if (options[kFigWidth]) {
// we were only given width, use that and adjust height based on aspect ratio;
widthInInches = inInches(String(options[kFigWidth]));
heightInInches = widthInInches / svgWidthOverHeight;
} else if (options[kFigHeight]) {
// we were only given height, use that and adjust width based on aspect ratio;
heightInInches = inInches(String(options[kFigHeight]));
widthInInches = heightInInches * svgWidthOverHeight;
} else {
// we were not given either, use svg's prescribed height
heightInInches = svgHeightInInches;
widthInInches = svgWidthInInches;
}
return {
widthInInches,
heightInInches,
widthInPoints: Math.round(widthInInches * 96),
heightInPoints: Math.round(heightInInches * 96),
explicitWidth: options?.[kFigWidth] !== undefined,
explicitHeight: options?.[kFigHeight] !== undefined,
};
},
postProcess(svg) {
const options = this.resolveOptions(svg);
if (
options.responsive & &
options["figWidth"] === undefined & &
options["figHeight"] === undefined
) {
this.makeResponsive(svg);
} else {
this.setSvgSize(svg);
}
if (options["reveal"]) {
this.fixupAlignment(svg, options["figAlign"] || "center");
}
// forward align attributes to the correct parent dif
// so that the svg figure is aligned correctly
const div = svg.parentElement.parentElement.parentElement;
const align = div.parentElement.parentElement.dataset.layoutAlign;
if (align) {
div.classList.remove("quarto-figure-left");
div.classList.remove("quarto-figure-center");
div.classList.remove("quarto-figure-right");
div.classList.add(`quarto-figure-${align}`);
}
},
};
// deno-lint-ignore no-window-prefix
window.addEventListener(
"load",
function () {
let i = 0;
// we need pre because of whitespace preservation
for (const el of Array.from(document.querySelectorAll("pre.mermaid-js"))) {
// doesn't appear to be treated as whitespace by mermaid
// so we replace it with a space.
const text = el.innerText.replaceAll(" ", " ");
const output = mermaid.mermaidAPI.render(
`mermaid-${++i}`,
text,
() => {},
el
);
el.innerHTML = output;
if (el.dataset.label) {
// patch mermaid's emitted style
const svg = el.firstChild;
const style = svg.querySelector("style");
style.innerHTML = style.innerHTML.replaceAll(
`#${svg.id}`,
`#${el.dataset.label}`
);
svg.id = el.dataset.label;
delete el.dataset.label;
}
const svg = el.querySelector("svg");
const parent = el.parentElement;
parent.removeChild(el);
parent.appendChild(svg);
svg.classList.add("mermaid-js");
}
for (const svgEl of Array.from(
document.querySelectorAll("svg.mermaid-js")
)) {
_quartoMermaid.postProcess(svgEl);
}
},
false
);
< / script >
< style type = "text/css" > . m e r m a i d T o o l t i p {
position: absolute;
text-align: center;
max-width: 200px;
padding: 2px;
font-family: "trebuchet ms", verdana, arial;
font-size: 12px;
background: #ffffde;
border: 1px solid #aaaa33;
border-radius: 2px;
pointer-events: none;
z-index: 1000;
}
< / style >
< / head >
< body >
< div id = "quarto-content" class = "page-columns page-rows-contents page-layout-article" >
< div id = "quarto-margin-sidebar" class = "sidebar margin-sidebar" >
< nav id = "TOC" role = "doc-toc" class = "toc-active" >
< h2 id = "toc-title" > Table of contents< / h2 >
< ul >
< li > < a href = "#the-data-sample" id = "toc-the-data-sample" class = "nav-link active" data-scroll-target = "#the-data-sample" > The data sample< / a > < / li >
< li > < a href = "#preliminary-findings" id = "toc-preliminary-findings" class = "nav-link" data-scroll-target = "#preliminary-findings" > Preliminary findings< / a > < / li >
< li > < a href = "#preliminary-limitations" id = "toc-preliminary-limitations" class = "nav-link" data-scroll-target = "#preliminary-limitations" > Preliminary limitations< / a > < / li >
< / ul >
< div class = "quarto-alternate-formats" > < h2 > Other Formats< / h2 > < ul > < li > < a href = "meeting_eoy.docx" > < i class = "bi bi-file-word" > < / i > MS Word< / a > < / li > < li > < a href = "meeting_eoy.pdf" > < i class = "bi bi-file-pdf" > < / i > PDF< / a > < / li > < / ul > < / div > < / nav >
< / div >
< main class = "content page-columns page-full" id = "quarto-document-content" >
< header id = "title-block-header" class = "quarto-title-block default" >
< div class = "quarto-title" >
< div class = "quarto-title-block" > < div > < h1 class = "title" > Scoping Review: Preliminary findings< / h1 > < button type = "button" class = "btn code-tools-button" id = "quarto-code-tools-source" > < i class = "bi" > < / i > Code< / button > < / div > < / div >
< p class = "subtitle lead" > Addressing inequalities in the World of Work< / p >
< / div >
< div class = "quarto-title-meta" >
< / div >
< / header >
< section id = "the-data-sample" class = "level1" >
< h1 > The data sample< / h1 >
< div class = "cell" data-fig-width = "6" >
< div class = "cell-output-display" >
< div id = "fig-prisma" class = "quarto-figure quarto-figure-center anchored" >
< figure class = "figure" >
< div >
< pre class = "mermaid mermaid-js" data-label = "fig-prisma" > flowchart TD;
search_db[" Records identified through database searching (n=1643)" ] --> starting_sample;
search_prev[" Records identified through other sources (n=753)" ] --> starting_sample[" Starting sample (n=2396)" ];
starting_sample -- " Duplicate removal (-22 removed) " --> dedup[" Records after duplicates removed (n=2418)" ];
dedup -- " Title screening (982 excluded)" --> title_screened[" Records after titles screened (n=1436)" ];
title_screened -- " Abstract screening (1039 excluded)" --> abstract_screened[" Records after abstracts screened (n=397)" ];
abstract_screened -- " Language screening (1 excluded) " --> language_screened[" Records after language screened (n=396)" ];
language_screened -- " Full-text screening (316 excluded) " --> full-text_screened[" Full-text articles assessed for eligibility (n=38) STILL OUTSTANDING: 358" ];
< / pre >
< / div >
< figcaption class = "figure-caption" > Figure < / figcaption >
< / figure >
< / div >
< / div >
< / div >
< ul >
< li > strongest focus on income inequality (vertical), with many horizontal inequality studies including aspect of income inequality< / li >
< li > horizontal inequalities: strongest focus on income - gender inequalities (horizontal)< / li >
< li > interventions:
< ul >
< li > strongest research base on labour rights protection interventions< / li >
< li > second on infrastructural interventions< / li >
< li > third on agency-strengthening ones: training, financial access, education programmes< / li >
< / ul > < / li >
< li > formalization & social protection research rarely goes into inequality outcomes beyond ‘ ’ < / li >
< / ul >
< div class = "cell" data-execution_count = "3" >
< div class = "cell-output cell-output-display" >
< div id = "fig-inequality-types-whole-sample" class = "quarto-figure quarto-figure-center anchored" >
< figure class = "figure" >
< p > < img src = "data:image/svg+xml;base64,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
< figcaption class = "figure-caption" > Figure < / figcaption >
< / figure >
< / div >
< / div >
< / div >
< / section >
< section id = "preliminary-findings" class = "level1" >
< h1 > Preliminary findings< / h1 >
< div class = "cell" data-execution_count = "4" >
< div class = "cell-output cell-output-display" >
< div id = "fig-inequality-types" class = "quarto-figure quarto-figure-center anchored" >
< figure class = "figure" >
< p > < img src = "data:image/svg+xml;base64,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
< figcaption class = "figure-caption" > Figure < / figcaption >
< / figure >
< / div >
< / div >
< / div >
< ul >
< li > interventions most strongly target gender-income divide
< ul >
< li > most studies here recommend further scale-integration between agency/structural approaches< / li >
< li > most studies also only focus on analysing a single scale however< / li >
< / ul > < / li >
< li > interventions often have intersectional impacts even if not targeted at them
< ul >
< li > most visible for institutional/structural interventions and spatial inequalities< / li >
< li > studies analysing intersectional inequalities near unanimously recommend intersectional targeting< / li >
< / ul > < / li >
< li > individual agency-based interventions (training, subsidies, maternity benefits, transfers, microcredit, etc):
< ul >
< li > seem most effective for targeting WoW outcomes of disability inequalities< / li >
< li > seem marginally effective for targeting WoW outcomes of gender inequalities< / li >
< li > require additional mediating scales for other inequalities< / li >
< / ul > < / li >
< li > more structural interventions (education, infrastructural, ubi, trade liberalization, collective action):
< ul >
< li > seem most effective for spatial, income, education-generational inequalities< / li >
< li > often show longer-term impacts, requiring longer periods of analyses< / li >
< li > can work without additional agency-based interventions, few studies analyse both at same time< / li >
< / ul > < / li >
< / ul >
< / section >
< section id = "preliminary-limitations" class = "level1 page-columns page-full" >
< h1 > Preliminary limitations< / h1 >
< div class = "cell" data-execution_count = "5" >
< div class = "cell-output cell-output-display" >
< div id = "fig-intervention-types" class = "quarto-figure quarto-figure-center anchored" >
< figure class = "figure" >
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< figcaption class = "figure-caption" > Figure < / figcaption >
< / figure >
< / div >
< / div >
< / div >
< ul >
< li > stronger institutional-structural research focus in developed countries, with more structural-agency based in developing countries< / li >
< li > employment creation as a category is often subsumed in other structural/institutional analyses< / li >
< li > little evidence-based research on effect of interventions targeting education on world of work outcomes< / li >
< li > spatial inequality most evenly geographically spread evidence base< / li >
< li > empirical base on interventions targeting disability inequalities strongly restricted on developed countries, especially United States< / li >
< / ul >
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< div id = "fig-countries" class = "quarto-figure quarto-figure-center anchored" >
< figure class = "figure" >
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< figcaption class = "figure-caption" > Figure < / figcaption >
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});
return popup.innerHTML;
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}
}
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< / script > < div class = "modal fade" id = "quarto-embedded-source-code-modal" tabindex = "-1" aria-labelledby = "quarto-embedded-source-code-modal-label" aria-hidden = "true" > < div class = "modal-dialog modal-dialog-scrollable" > < div class = "modal-content" > < div class = "modal-header" > < h5 class = "modal-title" id = "quarto-embedded-source-code-modal-label" > Source Code< / h5 > < button class = "btn-close" data-bs-dismiss = "modal" > < / button > < / div > < div class = "modal-body" > < div class >
< div class = "sourceCode" id = "cb1" data-shortcodes = "false" > < pre class = "sourceCode markdown code-with-copy" > < code class = "sourceCode markdown" > < span id = "cb1-1" > < a href = "#cb1-1" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > ---< / span > < / span >
2024-07-15 19:38:05 +00:00
< span id = "cb1-2" > < a href = "#cb1-2" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "an" > bibliography:< / span > < span class = "co" > data/intermediate/zotero-library.bib< / span > < / span >
2024-01-06 09:41:26 +00:00
< span id = "cb1-3" > < a href = "#cb1-3" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "an" > csl:< / span > < span class = "co" > /home/marty/documents/library/utilities/styles/APA-7.csl< / span > < / span >
< span id = "cb1-4" > < a href = "#cb1-4" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "an" > papersize:< / span > < span class = "co" > A4< / span > < / span >
< span id = "cb1-5" > < a href = "#cb1-5" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "an" > linestretch:< / span > < span class = "co" > 1.5< / span > < / span >
< span id = "cb1-6" > < a href = "#cb1-6" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "an" > fontfamily:< / span > < span class = "co" > lmodern< / span > < / span >
< span id = "cb1-7" > < a href = "#cb1-7" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "an" > fontsize:< / span > < span class = "co" > " 12" < / span > < / span >
< span id = "cb1-8" > < a href = "#cb1-8" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "an" > geometry:< / span > < / span >
< span id = "cb1-9" > < a href = "#cb1-9" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > - left=2.2cm< / span > < / span >
< span id = "cb1-10" > < a href = "#cb1-10" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > - right=3.5cm< / span > < / span >
< span id = "cb1-11" > < a href = "#cb1-11" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > - top=2.5cm< / span > < / span >
< span id = "cb1-12" > < a href = "#cb1-12" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > - bottom=2.5cm< / span > < / span >
< span id = "cb1-13" > < a href = "#cb1-13" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "an" > lang:< / span > < span class = "co" > en< / span > < / span >
< span id = "cb1-14" > < a href = "#cb1-14" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "an" > title:< / span > < span class = "co" > " Scoping Review: Preliminary findings" < / span > < / span >
< span id = "cb1-15" > < a href = "#cb1-15" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "an" > subtitle:< / span > < span class = "co" > Addressing inequalities in the World of Work< / span > < / span >
< span id = "cb1-16" > < a href = "#cb1-16" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > ---< / span > < / span >
< span id = "cb1-17" > < a href = "#cb1-17" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-20" > < a href = "#cb1-20" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```{python}< / span > < / span >
< span id = "cb1-21" > < a href = "#cb1-21" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| echo: false< / span > < / span >
< span id = "cb1-22" > < a href = "#cb1-22" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "im" > from< / span > pathlib < span class = "im" > import< / span > Path< / span >
< span id = "cb1-23" > < a href = "#cb1-23" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "im" > import< / span > re< / span >
< span id = "cb1-24" > < a href = "#cb1-24" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > ## standard imports< / span > < / span >
< span id = "cb1-25" > < a href = "#cb1-25" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "im" > from< / span > IPython.core.display < span class = "im" > import< / span > Markdown < span class = "im" > as< / span > md< / span >
< span id = "cb1-26" > < a href = "#cb1-26" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "im" > import< / span > numpy < span class = "im" > as< / span > np< / span >
< span id = "cb1-27" > < a href = "#cb1-27" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "im" > import< / span > pandas < span class = "im" > as< / span > pd< / span >
< span id = "cb1-28" > < a href = "#cb1-28" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "im" > from< / span > matplotlib < span class = "im" > import< / span > pyplot < span class = "im" > as< / span > plt< / span >
< span id = "cb1-29" > < a href = "#cb1-29" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "im" > import< / span > seaborn < span class = "im" > as< / span > sns< / span >
< span id = "cb1-30" > < a href = "#cb1-30" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "im" > from< / span > tabulate < span class = "im" > import< / span > tabulate< / span >
< span id = "cb1-31" > < a href = "#cb1-31" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "im" > import< / span > bibtexparser< / span >
< span id = "cb1-32" > < a href = "#cb1-32" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-33" > < a href = "#cb1-33" aria-hidden = "true" tabindex = "-1" > < / a > sns.set_style(< span class = "st" > " whitegrid" < / span > )< / span >
< span id = "cb1-34" > < a href = "#cb1-34" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
2024-07-15 19:38:05 +00:00
< span id = "cb1-35" > < a href = "#cb1-35" aria-hidden = "true" tabindex = "-1" > < / a > DATA_DIR< span class = "op" > =< / span > Path(< span class = "st" > " ./data" < / span > )< / span >
2024-01-06 09:41:26 +00:00
< span id = "cb1-36" > < a href = "#cb1-36" aria-hidden = "true" tabindex = "-1" > < / a > RAW_DATA< span class = "op" > =< / span > DATA_DIR.joinpath(< span class = "st" > " raw" < / span > )< / span >
< span id = "cb1-37" > < a href = "#cb1-37" aria-hidden = "true" tabindex = "-1" > < / a > WORKING_DATA< span class = "op" > =< / span > DATA_DIR.joinpath(< span class = "st" > " intermediate" < / span > )< / span >
< span id = "cb1-38" > < a href = "#cb1-38" aria-hidden = "true" tabindex = "-1" > < / a > PROCESSED_DATA< span class = "op" > =< / span > DATA_DIR.joinpath(< span class = "st" > " processed" < / span > )< / span >
< span id = "cb1-39" > < a href = "#cb1-39" aria-hidden = "true" tabindex = "-1" > < / a > SUPPLEMENTARY_DATA< span class = "op" > =< / span > DATA_DIR.joinpath(< span class = "st" > " supplementary" < / span > )< / span >
< span id = "cb1-40" > < a href = "#cb1-40" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-41" > < a href = "#cb1-41" aria-hidden = "true" tabindex = "-1" > < / a > bib_string< span class = "op" > =< / span > < span class = "st" > " " < / span > < / span >
< span id = "cb1-42" > < a href = "#cb1-42" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "cf" > for< / span > partial_bib < span class = "kw" > in< / span > RAW_DATA.glob(< span class = "st" > " **/*.bib" < / span > ):< / span >
< span id = "cb1-43" > < a href = "#cb1-43" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "cf" > with< / span > < span class = "bu" > open< / span > (partial_bib) < span class = "im" > as< / span > f:< / span >
< span id = "cb1-44" > < a href = "#cb1-44" aria-hidden = "true" tabindex = "-1" > < / a > bib_string< span class = "op" > +=< / span > < span class = "st" > " < / span > < span class = "ch" > \n< / span > < span class = "st" > " < / span > .join(f.readlines())< / span >
< span id = "cb1-45" > < a href = "#cb1-45" aria-hidden = "true" tabindex = "-1" > < / a > bib_sample_raw_db < span class = "op" > =< / span > bibtexparser.parse_string(bib_string)< / span >
< span id = "cb1-46" > < a href = "#cb1-46" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-47" > < a href = "#cb1-47" aria-hidden = "true" tabindex = "-1" > < / a > bib_string< span class = "op" > =< / span > < span class = "st" > " " < / span > < / span >
< span id = "cb1-48" > < a href = "#cb1-48" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "cf" > for< / span > partial_bib < span class = "kw" > in< / span > WORKING_DATA.glob(< span class = "st" > " **/*.bib" < / span > ):< / span >
< span id = "cb1-49" > < a href = "#cb1-49" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "cf" > with< / span > < span class = "bu" > open< / span > (partial_bib) < span class = "im" > as< / span > f:< / span >
< span id = "cb1-50" > < a href = "#cb1-50" aria-hidden = "true" tabindex = "-1" > < / a > bib_string< span class = "op" > +=< / span > < span class = "st" > " < / span > < span class = "ch" > \n< / span > < span class = "st" > " < / span > .join(f.readlines())< / span >
< span id = "cb1-51" > < a href = "#cb1-51" aria-hidden = "true" tabindex = "-1" > < / a > bib_sample < span class = "op" > =< / span > bibtexparser.parse_string(bib_string)< / span >
< span id = "cb1-52" > < a href = "#cb1-52" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-53" > < a href = "#cb1-53" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > # load relevant studies< / span > < / span >
< span id = "cb1-54" > < a href = "#cb1-54" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "im" > from< / span > src < span class = "im" > import< / span > data< / span >
< span id = "cb1-55" > < a href = "#cb1-55" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-56" > < a href = "#cb1-56" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > # load zotero-based metadata: citations and uses< / span > < / span >
< span id = "cb1-57" > < a href = "#cb1-57" aria-hidden = "true" tabindex = "-1" > < / a > zot_df < span class = "op" > =< / span > pd.DataFrame([< / span >
< span id = "cb1-58" > < a href = "#cb1-58" aria-hidden = "true" tabindex = "-1" > < / a > [< / span >
< span id = "cb1-59" > < a href = "#cb1-59" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " doi" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " doi" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-60" > < a href = "#cb1-60" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " times-cited" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " times-cited" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-61" > < a href = "#cb1-61" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " usage" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " usage" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-62" > < a href = "#cb1-62" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " keywords" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " keywords" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-63" > < a href = "#cb1-63" aria-hidden = "true" tabindex = "-1" > < / a > ]< / span >
< span id = "cb1-64" > < a href = "#cb1-64" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "cf" > for< / span > entry < span class = "kw" > in< / span > bib_sample.entries< / span >
< span id = "cb1-65" > < a href = "#cb1-65" aria-hidden = "true" tabindex = "-1" > < / a > ], columns < span class = "op" > =< / span > [< span class = "st" > " doi" < / span > , < span class = "st" > " cited" < / span > , < span class = "st" > " usage" < / span > , < span class = "st" > " keywords" < / span > ]).drop_duplicates(< span class = "st" > " doi" < / span > ).set_index(< span class = "st" > " doi" < / span > )< / span >
< span id = "cb1-66" > < a href = "#cb1-66" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-67" > < a href = "#cb1-67" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > # Add WB country grouping definitions (income group, world region)< / span > < / span >
< span id = "cb1-68" > < a href = "#cb1-68" aria-hidden = "true" tabindex = "-1" > < / a > WB_COUNTRY_GROUPS_FILE < span class = "op" > =< / span > Path(< span class = "ss" > f" < / span > < span class = "sc" > {< / span > SUPPLEMENTARY_DATA< span class = "sc" > }< / span > < span class = "ss" > /wb-country-groupings.xlsx" < / span > ).resolve()< / span >
< span id = "cb1-69" > < a href = "#cb1-69" aria-hidden = "true" tabindex = "-1" > < / a > df_country_groups < span class = "op" > =< / span > pd.read_excel(WB_COUNTRY_GROUPS_FILE).set_index(< span class = "st" > " Economy" < / span > )< / span >
< span id = "cb1-70" > < a href = "#cb1-70" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-71" > < a href = "#cb1-71" aria-hidden = "true" tabindex = "-1" > < / a > bib_df < span class = "op" > =< / span > (data.from_yml(< span class = "ss" > f" < / span > < span class = "sc" > {< / span > PROCESSED_DATA< span class = "sc" > }< / span > < span class = "ss" > /relevant" < / span > )< / span >
< span id = "cb1-72" > < a href = "#cb1-72" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-73" > < a href = "#cb1-73" aria-hidden = "true" tabindex = "-1" > < / a > doi< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " uri" < / span > ].< span class = "bu" > str< / span > .extract(< span class = "vs" > r" https?://(?:dx\.)?doi\.org/(.*)" < / span > , expand< span class = "op" > =< / span > < span class = "va" > False< / span > ),< / span >
< span id = "cb1-74" > < a href = "#cb1-74" aria-hidden = "true" tabindex = "-1" > < / a > zot_cited< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " doi" < / span > ].< span class = "bu" > map< / span > (zot_df[< span class = "st" > " cited" < / span > ]),< / span >
< span id = "cb1-75" > < a href = "#cb1-75" aria-hidden = "true" tabindex = "-1" > < / a > zot_usage< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " doi" < / span > ].< span class = "bu" > map< / span > (zot_df[< span class = "st" > " usage" < / span > ]),< / span >
< span id = "cb1-76" > < a href = "#cb1-76" aria-hidden = "true" tabindex = "-1" > < / a > zot_keywords< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " doi" < / span > ].< span class = "bu" > map< / span > (zot_df[< span class = "st" > " keywords" < / span > ]),< / span >
< span id = "cb1-77" > < a href = "#cb1-77" aria-hidden = "true" tabindex = "-1" > < / a > date < span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: pd.to_datetime(_df[< span class = "st" > " year" < / span > ], < span class = "bu" > format< / span > < span class = "op" > =< / span > < span class = "st" > " %Y" < / span > ),< / span >
< span id = "cb1-78" > < a href = "#cb1-78" aria-hidden = "true" tabindex = "-1" > < / a > year < span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " date" < / span > ].dt.year,< / span >
< span id = "cb1-79" > < a href = "#cb1-79" aria-hidden = "true" tabindex = "-1" > < / a > region < span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " country" < / span > ].< span class = "bu" > map< / span > (df_country_groups[< span class = "st" > " Region" < / span > ]),< / span >
< span id = "cb1-80" > < a href = "#cb1-80" aria-hidden = "true" tabindex = "-1" > < / a > income_group < span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " country" < / span > ].< span class = "bu" > map< / span > (df_country_groups[< span class = "st" > " Income group" < / span > ]),< / span >
< span id = "cb1-81" > < a href = "#cb1-81" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-82" > < a href = "#cb1-82" aria-hidden = "true" tabindex = "-1" > < / a > .query(< span class = "st" > " year > = 2000" < / span > )< / span >
< span id = "cb1-83" > < a href = "#cb1-83" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-84" > < a href = "#cb1-84" aria-hidden = "true" tabindex = "-1" > < / a > zot_df < span class = "op" > =< / span > < span class = "va" > None< / span > < / span >
< span id = "cb1-85" > < a href = "#cb1-85" aria-hidden = "true" tabindex = "-1" > < / a > df_country_groups < span class = "op" > =< / span > < span class = "va" > None< / span > < / span >
< span id = "cb1-86" > < a href = "#cb1-86" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```< / span > < / span >
< span id = "cb1-87" > < a href = "#cb1-87" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-88" > < a href = "#cb1-88" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "fu" > # The data sample< / span > < / span >
< span id = "cb1-89" > < a href = "#cb1-89" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-92" > < a href = "#cb1-92" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```{python}< / span > < / span >
< span id = "cb1-93" > < a href = "#cb1-93" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| echo: false< / span > < / span >
< span id = "cb1-94" > < a href = "#cb1-94" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| output: asis< / span > < / span >
< span id = "cb1-95" > < a href = "#cb1-95" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-96" > < a href = "#cb1-96" aria-hidden = "true" tabindex = "-1" > < / a > FULL_RAW_SAMPLE_NOTHING_REMOVED < span class = "op" > =< / span > < span class = "dv" > 2396< / span > < / span >
< span id = "cb1-97" > < a href = "#cb1-97" aria-hidden = "true" tabindex = "-1" > < / a > nr_database_query_raw < span class = "op" > =< / span > < span class = "bu" > len< / span > (bib_sample_raw_db.entries)< / span >
< span id = "cb1-98" > < a href = "#cb1-98" aria-hidden = "true" tabindex = "-1" > < / a > nr_out_duplicates < span class = "op" > =< / span > FULL_RAW_SAMPLE_NOTHING_REMOVED < span class = "op" > -< / span > < span class = "bu" > len< / span > (bib_sample.entries)< / span >
< span id = "cb1-99" > < a href = "#cb1-99" aria-hidden = "true" tabindex = "-1" > < / a > nr_other_sources < span class = "op" > =< / span > (< span class = "bu" > len< / span > (bib_sample.entries) < span class = "op" > +< / span > nr_out_duplicates) < span class = "op" > -< / span > nr_database_query_raw< / span >
< span id = "cb1-100" > < a href = "#cb1-100" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-101" > < a href = "#cb1-101" aria-hidden = "true" tabindex = "-1" > < / a > all_keywords < span class = "op" > =< / span > [entry[< span class = "st" > " keywords" < / span > ] < span class = "cf" > for< / span > entry < span class = "kw" > in< / span > bib_sample.entries < span class = "cf" > if< / span > < span class = "st" > " keywords" < / span > < span class = "kw" > in< / span > entry.fields_dict.keys()]< / span >
< span id = "cb1-102" > < a href = "#cb1-102" aria-hidden = "true" tabindex = "-1" > < / a > nr_out_title < span class = "op" > =< / span > < span class = "bu" > len< / span > ([< span class = "dv" > 1< / span > < span class = "cf" > for< / span > kw < span class = "kw" > in< / span > all_keywords < span class = "cf" > if< / span > < span class = "st" > " out::title" < / span > < span class = "kw" > in< / span > kw]) < span class = "op" > +< / span > < span class = "dv" > 400< / span > < / span >
< span id = "cb1-103" > < a href = "#cb1-103" aria-hidden = "true" tabindex = "-1" > < / a > nr_out_abstract < span class = "op" > =< / span > < span class = "bu" > len< / span > ([< span class = "dv" > 1< / span > < span class = "cf" > for< / span > kw < span class = "kw" > in< / span > all_keywords < span class = "cf" > if< / span > < span class = "st" > " out::abstract" < / span > < span class = "kw" > in< / span > kw]) < span class = "op" > +< / span > < span class = "dv" > 400< / span > < / span >
< span id = "cb1-104" > < a href = "#cb1-104" aria-hidden = "true" tabindex = "-1" > < / a > nr_out_fulltext < span class = "op" > =< / span > < span class = "bu" > len< / span > ([< span class = "dv" > 1< / span > < span class = "cf" > for< / span > kw < span class = "kw" > in< / span > all_keywords < span class = "cf" > if< / span > < span class = "st" > " out::full-text" < / span > < span class = "kw" > in< / span > kw]) < span class = "op" > +< / span > < span class = "dv" > 300< / span > < / span >
< span id = "cb1-105" > < a href = "#cb1-105" aria-hidden = "true" tabindex = "-1" > < / a > nr_out_language < span class = "op" > =< / span > < span class = "bu" > len< / span > ([< span class = "dv" > 1< / span > < span class = "cf" > for< / span > kw < span class = "kw" > in< / span > all_keywords < span class = "cf" > if< / span > < span class = "st" > " out::language" < / span > < span class = "kw" > in< / span > kw])< / span >
< span id = "cb1-106" > < a href = "#cb1-106" aria-hidden = "true" tabindex = "-1" > < / a > nr_extraction_done < span class = "op" > =< / span > < span class = "bu" > len< / span > ([< span class = "dv" > 1< / span > < span class = "cf" > for< / span > kw < span class = "kw" > in< / span > all_keywords < span class = "cf" > if< / span > < span class = "st" > " done::extracted" < / span > < span class = "kw" > in< / span > kw])< / span >
< span id = "cb1-107" > < a href = "#cb1-107" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-108" > < a href = "#cb1-108" aria-hidden = "true" tabindex = "-1" > < / a > t3 < span class = "op" > =< / span > < span class = "st" > " `" < / span > < span class = "op" > *< / span > < span class = "dv" > 3< / span > < / span >
2024-07-15 19:38:05 +00:00
< span id = "cb1-109" > < a href = "#cb1-109" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > # < / span > < span class = "al" > FIXME< / span > < span class = "co" > use data/supplementary undeduplciated counts to get database starting and snowballing counts< / span > < / span >
2024-01-06 09:41:26 +00:00
< span id = "cb1-110" > < a href = "#cb1-110" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > # from: https://github.com/quarto-dev/quarto-cli/discussions/6508< / span > < / span >
< span id = "cb1-111" > < a href = "#cb1-111" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "bu" > print< / span > (< span class = "ss" > f" " " < / span > < / span >
< span id = "cb1-112" > < a href = "#cb1-112" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > ```< / span > < span class = "sc" > {< / span > mermaid< span class = "sc" > }< / span > < / span >
< span id = "cb1-113" > < a href = "#cb1-113" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > %%| label: fig-prisma< / span > < / span >
< span id = "cb1-114" > < a href = "#cb1-114" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > %%| fig-cap: " Sample sorting process through identification and screening" < / span > < / span >
< span id = "cb1-115" > < a href = "#cb1-115" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > %%| fig-width: 6< / span > < / span >
< span id = "cb1-116" > < a href = "#cb1-116" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > flowchart TD;< / span > < / span >
< span id = "cb1-117" > < a href = "#cb1-117" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > search_db[" Records identified through database searching (n=< / span > < span class = "sc" > {< / span > nr_database_query_raw< span class = "sc" > }< / span > < span class = "ss" > )" ] --> starting_sample;< / span > < / span >
< span id = "cb1-118" > < a href = "#cb1-118" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > search_prev[" Records identified through other sources (n=< / span > < span class = "sc" > {< / span > nr_other_sources< span class = "sc" > }< / span > < span class = "ss" > )" ] --> starting_sample[" Starting sample (n=< / span > < span class = "sc" > {< / span > FULL_RAW_SAMPLE_NOTHING_REMOVED< span class = "sc" > }< / span > < span class = "ss" > )" ];< / span > < / span >
< span id = "cb1-119" > < a href = "#cb1-119" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-120" > < a href = "#cb1-120" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > starting_sample -- " Duplicate removal (< / span > < span class = "sc" > {< / span > nr_out_duplicates< span class = "sc" > }< / span > < span class = "ss" > removed) " --> dedup[" Records after duplicates removed (n=< / span > < span class = "sc" > {< / span > < span class = "bu" > len< / span > (bib_sample.entries)< span class = "sc" > }< / span > < span class = "ss" > )" ];< / span > < / span >
< span id = "cb1-121" > < a href = "#cb1-121" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-122" > < a href = "#cb1-122" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > dedup -- " Title screening (< / span > < span class = "sc" > {< / span > nr_out_title< span class = "sc" > }< / span > < span class = "ss" > excluded)" --> title_screened[" Records after titles screened (n=< / span > < span class = "sc" > {< / span > < span class = "bu" > len< / span > (bib_sample.entries) < span class = "op" > -< / span > nr_out_title< span class = "sc" > }< / span > < span class = "ss" > )" ];< / span > < / span >
< span id = "cb1-123" > < a href = "#cb1-123" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-124" > < a href = "#cb1-124" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > title_screened -- " Abstract screening (< / span > < span class = "sc" > {< / span > nr_out_abstract< span class = "sc" > }< / span > < span class = "ss" > excluded)" --> abstract_screened[" Records after abstracts screened (n=< / span > < span class = "sc" > {< / span > < span class = "bu" > len< / span > (bib_sample.entries)< span class = "op" > -< / span > nr_out_title< span class = "op" > -< / span > nr_out_abstract< span class = "sc" > }< / span > < span class = "ss" > )" ];< / span > < / span >
< span id = "cb1-125" > < a href = "#cb1-125" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-126" > < a href = "#cb1-126" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > abstract_screened -- " Language screening (< / span > < span class = "sc" > {< / span > nr_out_language< span class = "sc" > }< / span > < span class = "ss" > excluded) " --> language_screened[" Records after language screened (n=< / span > < span class = "sc" > {< / span > < span class = "bu" > len< / span > (bib_sample.entries)< span class = "op" > -< / span > nr_out_title< span class = "op" > -< / span > nr_out_abstract< span class = "op" > -< / span > nr_out_language< span class = "sc" > }< / span > < span class = "ss" > )" ];< / span > < / span >
< span id = "cb1-127" > < a href = "#cb1-127" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-128" > < a href = "#cb1-128" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > language_screened -- " Full-text screening (< / span > < span class = "sc" > {< / span > nr_out_fulltext< span class = "sc" > }< / span > < span class = "ss" > excluded) " --> full-text_screened[" Full-text articles assessed for eligibility (n=< / span > < span class = "sc" > {< / span > nr_extraction_done< span class = "sc" > }< / span > < span class = "ss" > ) STILL OUTSTANDING: < / span > < span class = "sc" > {< / span > < span class = "bu" > len< / span > (bib_sample.entries)< span class = "op" > -< / span > nr_out_title< span class = "op" > -< / span > nr_out_abstract< span class = "op" > -< / span > nr_out_language < span class = "op" > -< / span > nr_extraction_done< span class = "sc" > }< / span > < span class = "ss" > " ];< / span > < / span >
< span id = "cb1-129" > < a href = "#cb1-129" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "sc" > {< / span > t3< span class = "sc" > }< / span > < / span >
< span id = "cb1-130" > < a href = "#cb1-130" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > " " " < / span > )< / span >
< span id = "cb1-131" > < a href = "#cb1-131" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```< / span > < / span >
< span id = "cb1-132" > < a href = "#cb1-132" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-133" > < a href = "#cb1-133" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > strongest focus on income inequality (vertical), with many horizontal inequality studies including aspect of income inequality< / span >
< span id = "cb1-134" > < a href = "#cb1-134" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > horizontal inequalities: strongest focus on income - gender inequalities (horizontal)< / span >
< span id = "cb1-135" > < a href = "#cb1-135" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > interventions:< / span >
< span id = "cb1-136" > < a href = "#cb1-136" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > strongest research base on labour rights protection interventions< / span >
< span id = "cb1-137" > < a href = "#cb1-137" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > second on infrastructural interventions< / span >
< span id = "cb1-138" > < a href = "#cb1-138" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > third on agency-strengthening ones: training, financial access, education programmes< / span >
< span id = "cb1-139" > < a href = "#cb1-139" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-140" > < a href = "#cb1-140" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > formalization & social protection research rarely goes into inequality outcomes beyond ' income' effects; most excluded for that reason< / span >
< span id = "cb1-141" > < a href = "#cb1-141" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-144" > < a href = "#cb1-144" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```{python}< / span > < / span >
< span id = "cb1-145" > < a href = "#cb1-145" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| echo: false< / span > < / span >
< span id = "cb1-146" > < a href = "#cb1-146" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| label: fig-inequality-types-whole-sample< / span > < / span >
< span id = "cb1-147" > < a href = "#cb1-147" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| fig-cap: Overall inequality types in sample< / span > < / span >
< span id = "cb1-148" > < a href = "#cb1-148" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-149" > < a href = "#cb1-149" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > # load zotero-based metadata: citations and uses< / span > < / span >
< span id = "cb1-150" > < a href = "#cb1-150" aria-hidden = "true" tabindex = "-1" > < / a > pi < span class = "op" > =< / span > (pd.DataFrame([< / span >
< span id = "cb1-151" > < a href = "#cb1-151" aria-hidden = "true" tabindex = "-1" > < / a > [< / span >
< span id = "cb1-152" > < a href = "#cb1-152" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " doi" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " doi" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-153" > < a href = "#cb1-153" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " times-cited" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " times-cited" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-154" > < a href = "#cb1-154" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " usage" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " usage" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-155" > < a href = "#cb1-155" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " keywords" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " keywords" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-156" > < a href = "#cb1-156" aria-hidden = "true" tabindex = "-1" > < / a > ]< / span >
< span id = "cb1-157" > < a href = "#cb1-157" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "cf" > for< / span > entry < span class = "kw" > in< / span > bib_sample.entries< / span >
< span id = "cb1-158" > < a href = "#cb1-158" aria-hidden = "true" tabindex = "-1" > < / a > ], columns < span class = "op" > =< / span > [< span class = "st" > " doi" < / span > , < span class = "st" > " cited" < / span > , < span class = "st" > " usage" < / span > , < span class = "st" > " keywords" < / span > ])< / span >
< span id = "cb1-159" > < a href = "#cb1-159" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates(< span class = "st" > " doi" < / span > )< / span >
< span id = "cb1-160" > < a href = "#cb1-160" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-161" > < a href = "#cb1-161" aria-hidden = "true" tabindex = "-1" > < / a > inequality< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " keywords" < / span > ].< span class = "bu" > str< / span > .replace(< span class = "st" > " < / span > < span class = "ch" > \\< / span > < span class = "st" > " < / span > , < span class = "st" > " " < / span > ).< span class = "bu" > str< / span > .extract(< span class = "st" > ' inequality::([\w\_]+),?' < / span > )< / span >
< span id = "cb1-162" > < a href = "#cb1-162" aria-hidden = "true" tabindex = "-1" > < / a > ).dropna(subset< span class = "op" > =< / span > < span class = "st" > " inequality" < / span > )< / span >
< span id = "cb1-163" > < a href = "#cb1-163" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-164" > < a href = "#cb1-164" aria-hidden = "true" tabindex = "-1" > < / a > inequality< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " inequality" < / span > ].< span class = "bu" > str< / span > .replace(< span class = "st" > " _" < / span > , < span class = "st" > " " < / span > ),< / span >
< span id = "cb1-165" > < a href = "#cb1-165" aria-hidden = "true" tabindex = "-1" > < / a > projected < span class = "op" > =< / span > < span class = "dv" > 1< / span > < / span >
< span id = "cb1-166" > < a href = "#cb1-166" aria-hidden = "true" tabindex = "-1" > < / a > ).reset_index()< / span >
< span id = "cb1-167" > < a href = "#cb1-167" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-168" > < a href = "#cb1-168" aria-hidden = "true" tabindex = "-1" > < / a > pi< / span >
< span id = "cb1-169" > < a href = "#cb1-169" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-170" > < a href = "#cb1-170" aria-hidden = "true" tabindex = "-1" > < / a > inequality < span class = "op" > =< / span > (pd.concat([< / span >
< span id = "cb1-171" > < a href = "#cb1-171" aria-hidden = "true" tabindex = "-1" > < / a > bib_df.groupby([< span class = "st" > " author" < / span > , < span class = "st" > " year" < / span > , < span class = "st" > " title" < / span > ])< / span >
< span id = "cb1-172" > < a href = "#cb1-172" aria-hidden = "true" tabindex = "-1" > < / a > .agg(< / span >
< span id = "cb1-173" > < a href = "#cb1-173" aria-hidden = "true" tabindex = "-1" > < / a > {< / span >
< span id = "cb1-174" > < a href = "#cb1-174" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "st" > " inequality" < / span > : < span class = "kw" > lambda< / span > _col: < span class = "st" > " ; " < / span > .join(_col),< / span >
< span id = "cb1-175" > < a href = "#cb1-175" aria-hidden = "true" tabindex = "-1" > < / a > }< / span >
< span id = "cb1-176" > < a href = "#cb1-176" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-177" > < a href = "#cb1-177" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-178" > < a href = "#cb1-178" aria-hidden = "true" tabindex = "-1" > < / a > projected< span class = "op" > =< / span > < span class = "dv" > 0< / span > < / span >
< span id = "cb1-179" > < a href = "#cb1-179" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-180" > < a href = "#cb1-180" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-181" > < a href = "#cb1-181" aria-hidden = "true" tabindex = "-1" > < / a > .reset_index()< / span >
< span id = "cb1-182" > < a href = "#cb1-182" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates() , pi])< / span >
< span id = "cb1-183" > < a href = "#cb1-183" aria-hidden = "true" tabindex = "-1" > < / a > .assign( inequality< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " inequality" < / span > ].< span class = "bu" > apply< / span > (< / span >
< span id = "cb1-184" > < a href = "#cb1-184" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "kw" > lambda< / span > _cell: < span class = "bu" > set< / span > ([x.strip() < span class = "cf" > for< / span > x < span class = "kw" > in< / span > re.sub(< span class = "vs" > r" \(.*\)" < / span > , < span class = "st" > " " < / span > , _cell).split(< span class = "st" > " ;" < / span > )])< / span >
< span id = "cb1-185" > < a href = "#cb1-185" aria-hidden = "true" tabindex = "-1" > < / a > ),< / span >
< span id = "cb1-186" > < a href = "#cb1-186" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-187" > < a href = "#cb1-187" aria-hidden = "true" tabindex = "-1" > < / a > .explode(< span class = "st" > " inequality" < / span > )< / span >
< span id = "cb1-188" > < a href = "#cb1-188" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates()< / span >
< span id = "cb1-189" > < a href = "#cb1-189" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-190" > < a href = "#cb1-190" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-191" > < a href = "#cb1-191" aria-hidden = "true" tabindex = "-1" > < / a > sort_order < span class = "op" > =< / span > inequality[< span class = "st" > " inequality" < / span > ].value_counts().index< / span >
< span id = "cb1-192" > < a href = "#cb1-192" aria-hidden = "true" tabindex = "-1" > < / a > i < span class = "op" > =< / span > inequality[inequality[< span class = "st" > " inequality" < / span > ].< span class = "bu" > str< / span > .contains(< span class = "vs" > r" (?:structural|institutional|agency)" < / span > ) < span class = "op" > ==< / span > < span class = "va" > False< / span > ]< / span >
< span id = "cb1-193" > < a href = "#cb1-193" aria-hidden = "true" tabindex = "-1" > < / a > fig < span class = "op" > =< / span > plt.figure()< / span >
< span id = "cb1-194" > < a href = "#cb1-194" aria-hidden = "true" tabindex = "-1" > < / a > fig.set_size_inches(< span class = "dv" > 6< / span > , < span class = "dv" > 3< / span > )< / span >
< span id = "cb1-195" > < a href = "#cb1-195" aria-hidden = "true" tabindex = "-1" > < / a > ax < span class = "op" > =< / span > sns.countplot(i, x< span class = "op" > =< / span > < span class = "st" > " inequality" < / span > , hue< span class = "op" > =< / span > < span class = "st" > " projected" < / span > ,order< span class = "op" > =< / span > i[< span class = "st" > " inequality" < / span > ].value_counts().index)< / span >
< span id = "cb1-196" > < a href = "#cb1-196" aria-hidden = "true" tabindex = "-1" > < / a > plt.setp(ax.get_xticklabels(), rotation< span class = "op" > =< / span > < span class = "dv" > 45< / span > , ha< span class = "op" > =< / span > < span class = "st" > " right" < / span > ,< / span >
< span id = "cb1-197" > < a href = "#cb1-197" aria-hidden = "true" tabindex = "-1" > < / a > rotation_mode< span class = "op" > =< / span > < span class = "st" > " anchor" < / span > )< / span >
< span id = "cb1-198" > < a href = "#cb1-198" aria-hidden = "true" tabindex = "-1" > < / a > plt.show()< / span >
< span id = "cb1-199" > < a href = "#cb1-199" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```< / span > < / span >
< span id = "cb1-200" > < a href = "#cb1-200" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-201" > < a href = "#cb1-201" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "fu" > # Preliminary findings< / span > < / span >
< span id = "cb1-202" > < a href = "#cb1-202" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-205" > < a href = "#cb1-205" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```{python}< / span > < / span >
< span id = "cb1-206" > < a href = "#cb1-206" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| echo: false< / span > < / span >
< span id = "cb1-207" > < a href = "#cb1-207" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| label: fig-inequality-types< / span > < / span >
< span id = "cb1-208" > < a href = "#cb1-208" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| fig-cap: Finished and projected inequality types< / span > < / span >
< span id = "cb1-209" > < a href = "#cb1-209" aria-hidden = "true" tabindex = "-1" > < / a > inequality < span class = "op" > =< / span > (pd.concat([< / span >
< span id = "cb1-210" > < a href = "#cb1-210" aria-hidden = "true" tabindex = "-1" > < / a > bib_df.groupby([< span class = "st" > " author" < / span > , < span class = "st" > " year" < / span > , < span class = "st" > " title" < / span > ])< / span >
< span id = "cb1-211" > < a href = "#cb1-211" aria-hidden = "true" tabindex = "-1" > < / a > .agg(< / span >
< span id = "cb1-212" > < a href = "#cb1-212" aria-hidden = "true" tabindex = "-1" > < / a > {< / span >
< span id = "cb1-213" > < a href = "#cb1-213" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "st" > " inequality" < / span > : < span class = "kw" > lambda< / span > _col: < span class = "st" > " ; " < / span > .join(_col),< / span >
< span id = "cb1-214" > < a href = "#cb1-214" aria-hidden = "true" tabindex = "-1" > < / a > }< / span >
< span id = "cb1-215" > < a href = "#cb1-215" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-216" > < a href = "#cb1-216" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-217" > < a href = "#cb1-217" aria-hidden = "true" tabindex = "-1" > < / a > projected< span class = "op" > =< / span > < span class = "dv" > 0< / span > < / span >
< span id = "cb1-218" > < a href = "#cb1-218" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-219" > < a href = "#cb1-219" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-220" > < a href = "#cb1-220" aria-hidden = "true" tabindex = "-1" > < / a > .reset_index()< / span >
< span id = "cb1-221" > < a href = "#cb1-221" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates() , pi[pi[< span class = "st" > " keywords" < / span > ].< span class = "bu" > str< / span > .contains(< span class = "st" > " relevant" < / span > ) < span class = "op" > ==< / span > < span class = "va" > True< / span > ]])< / span >
< span id = "cb1-222" > < a href = "#cb1-222" aria-hidden = "true" tabindex = "-1" > < / a > .assign( inequality< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " inequality" < / span > ].< span class = "bu" > apply< / span > (< / span >
< span id = "cb1-223" > < a href = "#cb1-223" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "kw" > lambda< / span > _cell: < span class = "bu" > set< / span > ([x.strip() < span class = "cf" > for< / span > x < span class = "kw" > in< / span > re.sub(< span class = "vs" > r" \(.*\)" < / span > , < span class = "st" > " " < / span > , _cell).split(< span class = "st" > " ;" < / span > )])< / span >
< span id = "cb1-224" > < a href = "#cb1-224" aria-hidden = "true" tabindex = "-1" > < / a > ),< / span >
< span id = "cb1-225" > < a href = "#cb1-225" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-226" > < a href = "#cb1-226" aria-hidden = "true" tabindex = "-1" > < / a > .explode(< span class = "st" > " inequality" < / span > )< / span >
< span id = "cb1-227" > < a href = "#cb1-227" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates()< / span >
< span id = "cb1-228" > < a href = "#cb1-228" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-229" > < a href = "#cb1-229" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-230" > < a href = "#cb1-230" aria-hidden = "true" tabindex = "-1" > < / a > sort_order < span class = "op" > =< / span > inequality[< span class = "st" > " inequality" < / span > ].value_counts().index< / span >
< span id = "cb1-231" > < a href = "#cb1-231" aria-hidden = "true" tabindex = "-1" > < / a > i < span class = "op" > =< / span > inequality[inequality[< span class = "st" > " inequality" < / span > ].< span class = "bu" > str< / span > .contains(< span class = "vs" > r" (?:structural|institutional|agency)" < / span > ) < span class = "op" > ==< / span > < span class = "va" > False< / span > ]< / span >
< span id = "cb1-232" > < a href = "#cb1-232" aria-hidden = "true" tabindex = "-1" > < / a > fig < span class = "op" > =< / span > plt.figure()< / span >
< span id = "cb1-233" > < a href = "#cb1-233" aria-hidden = "true" tabindex = "-1" > < / a > fig.set_size_inches(< span class = "dv" > 6< / span > , < span class = "dv" > 3< / span > )< / span >
< span id = "cb1-234" > < a href = "#cb1-234" aria-hidden = "true" tabindex = "-1" > < / a > ax < span class = "op" > =< / span > sns.countplot(i, x< span class = "op" > =< / span > < span class = "st" > " inequality" < / span > , hue< span class = "op" > =< / span > < span class = "st" > " projected" < / span > ,order< span class = "op" > =< / span > i[< span class = "st" > " inequality" < / span > ].value_counts().index)< / span >
< span id = "cb1-235" > < a href = "#cb1-235" aria-hidden = "true" tabindex = "-1" > < / a > plt.setp(ax.get_xticklabels(), rotation< span class = "op" > =< / span > < span class = "dv" > 45< / span > , ha< span class = "op" > =< / span > < span class = "st" > " right" < / span > ,< / span >
< span id = "cb1-236" > < a href = "#cb1-236" aria-hidden = "true" tabindex = "-1" > < / a > rotation_mode< span class = "op" > =< / span > < span class = "st" > " anchor" < / span > )< / span >
< span id = "cb1-237" > < a href = "#cb1-237" aria-hidden = "true" tabindex = "-1" > < / a > plt.show()< / span >
< span id = "cb1-238" > < a href = "#cb1-238" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```< / span > < / span >
< span id = "cb1-239" > < a href = "#cb1-239" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-240" > < a href = "#cb1-240" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > interventions most strongly target gender-income divide< / span >
< span id = "cb1-241" > < a href = "#cb1-241" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > most studies here recommend further scale-integration between agency/structural approaches< / span >
< span id = "cb1-242" > < a href = "#cb1-242" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > most studies also only focus on analysing a single scale however< / span >
< span id = "cb1-243" > < a href = "#cb1-243" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > interventions often have intersectional impacts even if not targeted at them< / span >
< span id = "cb1-244" > < a href = "#cb1-244" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > most visible for institutional/structural interventions and spatial inequalities< / span >
< span id = "cb1-245" > < a href = "#cb1-245" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > studies analysing intersectional inequalities near unanimously recommend intersectional targeting< / span >
< span id = "cb1-246" > < a href = "#cb1-246" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-247" > < a href = "#cb1-247" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > individual agency-based interventions (training, subsidies, maternity benefits, transfers, microcredit, etc):< / span >
< span id = "cb1-248" > < a href = "#cb1-248" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > seem most effective for targeting WoW outcomes of disability inequalities< / span >
< span id = "cb1-249" > < a href = "#cb1-249" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > seem marginally effective for targeting WoW outcomes of gender inequalities< / span >
< span id = "cb1-250" > < a href = "#cb1-250" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > require additional mediating scales for other inequalities< / span >
< span id = "cb1-251" > < a href = "#cb1-251" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > more structural interventions (education, infrastructural, ubi, trade liberalization, collective action):< / span >
< span id = "cb1-252" > < a href = "#cb1-252" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > seem most effective for spatial, income, education-generational inequalities< / span >
< span id = "cb1-253" > < a href = "#cb1-253" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > often show longer-term impacts, requiring longer periods of analyses< / span >
< span id = "cb1-254" > < a href = "#cb1-254" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > can work without additional agency-based interventions, few studies analyse both at same time< / span >
< span id = "cb1-255" > < a href = "#cb1-255" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-256" > < a href = "#cb1-256" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "fu" > # Preliminary limitations< / span > < / span >
< span id = "cb1-257" > < a href = "#cb1-257" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-260" > < a href = "#cb1-260" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```{python}< / span > < / span >
< span id = "cb1-261" > < a href = "#cb1-261" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| echo: false< / span > < / span >
< span id = "cb1-262" > < a href = "#cb1-262" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| label: fig-intervention-types< / span > < / span >
< span id = "cb1-263" > < a href = "#cb1-263" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| fig-cap: Finished and projected intervention types< / span > < / span >
< span id = "cb1-264" > < a href = "#cb1-264" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-265" > < a href = "#cb1-265" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > # load zotero-based metadata: citations and uses< / span > < / span >
< span id = "cb1-266" > < a href = "#cb1-266" aria-hidden = "true" tabindex = "-1" > < / a > pi < span class = "op" > =< / span > (pd.DataFrame([< / span >
< span id = "cb1-267" > < a href = "#cb1-267" aria-hidden = "true" tabindex = "-1" > < / a > [< / span >
< span id = "cb1-268" > < a href = "#cb1-268" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " doi" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " doi" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-269" > < a href = "#cb1-269" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " times-cited" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " times-cited" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-270" > < a href = "#cb1-270" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " usage" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " usage" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-271" > < a href = "#cb1-271" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " keywords" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " keywords" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-272" > < a href = "#cb1-272" aria-hidden = "true" tabindex = "-1" > < / a > ]< / span >
< span id = "cb1-273" > < a href = "#cb1-273" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "cf" > for< / span > entry < span class = "kw" > in< / span > bib_sample.entries< / span >
< span id = "cb1-274" > < a href = "#cb1-274" aria-hidden = "true" tabindex = "-1" > < / a > ], columns < span class = "op" > =< / span > [< span class = "st" > " doi" < / span > , < span class = "st" > " cited" < / span > , < span class = "st" > " usage" < / span > , < span class = "st" > " keywords" < / span > ])< / span >
< span id = "cb1-275" > < a href = "#cb1-275" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates(< span class = "st" > " doi" < / span > )< / span >
< span id = "cb1-276" > < a href = "#cb1-276" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-277" > < a href = "#cb1-277" aria-hidden = "true" tabindex = "-1" > < / a > intervention< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " keywords" < / span > ].< span class = "bu" > str< / span > .replace(< span class = "st" > " < / span > < span class = "ch" > \\< / span > < span class = "st" > " < / span > , < span class = "st" > " " < / span > ).< span class = "bu" > str< / span > .extract(< span class = "st" > ' type::([\w\_]+),?' < / span > )< / span >
< span id = "cb1-278" > < a href = "#cb1-278" aria-hidden = "true" tabindex = "-1" > < / a > ).dropna(subset< span class = "op" > =< / span > < span class = "st" > " intervention" < / span > )< / span >
< span id = "cb1-279" > < a href = "#cb1-279" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-280" > < a href = "#cb1-280" aria-hidden = "true" tabindex = "-1" > < / a > intervention< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " intervention" < / span > ].< span class = "bu" > str< / span > .replace(< span class = "st" > " _" < / span > , < span class = "st" > " " < / span > ),< / span >
< span id = "cb1-281" > < a href = "#cb1-281" aria-hidden = "true" tabindex = "-1" > < / a > projected < span class = "op" > =< / span > < span class = "dv" > 1< / span > < / span >
< span id = "cb1-282" > < a href = "#cb1-282" aria-hidden = "true" tabindex = "-1" > < / a > ).reset_index()< / span >
< span id = "cb1-283" > < a href = "#cb1-283" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-284" > < a href = "#cb1-284" aria-hidden = "true" tabindex = "-1" > < / a > pi< / span >
< span id = "cb1-285" > < a href = "#cb1-285" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-286" > < a href = "#cb1-286" aria-hidden = "true" tabindex = "-1" > < / a > by_intervention < span class = "op" > =< / span > (pd.concat([< / span >
< span id = "cb1-287" > < a href = "#cb1-287" aria-hidden = "true" tabindex = "-1" > < / a > bib_df.groupby([< span class = "st" > " author" < / span > , < span class = "st" > " year" < / span > , < span class = "st" > " title" < / span > ])< / span >
< span id = "cb1-288" > < a href = "#cb1-288" aria-hidden = "true" tabindex = "-1" > < / a > .agg(< / span >
< span id = "cb1-289" > < a href = "#cb1-289" aria-hidden = "true" tabindex = "-1" > < / a > {< / span >
< span id = "cb1-290" > < a href = "#cb1-290" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "st" > " intervention" < / span > : < span class = "kw" > lambda< / span > _col: < span class = "st" > " ; " < / span > .join(_col),< / span >
< span id = "cb1-291" > < a href = "#cb1-291" aria-hidden = "true" tabindex = "-1" > < / a > }< / span >
< span id = "cb1-292" > < a href = "#cb1-292" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-293" > < a href = "#cb1-293" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-294" > < a href = "#cb1-294" aria-hidden = "true" tabindex = "-1" > < / a > projected< span class = "op" > =< / span > < span class = "dv" > 0< / span > < / span >
< span id = "cb1-295" > < a href = "#cb1-295" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-296" > < a href = "#cb1-296" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-297" > < a href = "#cb1-297" aria-hidden = "true" tabindex = "-1" > < / a > .reset_index()< / span >
< span id = "cb1-298" > < a href = "#cb1-298" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates() , pi[pi[< span class = "st" > " keywords" < / span > ].< span class = "bu" > str< / span > .contains(< span class = "st" > " relevant" < / span > ) < span class = "op" > ==< / span > < span class = "va" > True< / span > ]])< / span >
< span id = "cb1-299" > < a href = "#cb1-299" aria-hidden = "true" tabindex = "-1" > < / a > .assign( intervention< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " intervention" < / span > ].< span class = "bu" > apply< / span > (< / span >
< span id = "cb1-300" > < a href = "#cb1-300" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "kw" > lambda< / span > _cell: < span class = "bu" > set< / span > ([x.strip() < span class = "cf" > for< / span > x < span class = "kw" > in< / span > re.sub(< span class = "vs" > r" \(.*\)" < / span > , < span class = "st" > " " < / span > , _cell).split(< span class = "st" > " ;" < / span > )])< / span >
< span id = "cb1-301" > < a href = "#cb1-301" aria-hidden = "true" tabindex = "-1" > < / a > ),< / span >
< span id = "cb1-302" > < a href = "#cb1-302" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-303" > < a href = "#cb1-303" aria-hidden = "true" tabindex = "-1" > < / a > .explode(< span class = "st" > " intervention" < / span > )< / span >
< span id = "cb1-304" > < a href = "#cb1-304" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates()< / span >
< span id = "cb1-305" > < a href = "#cb1-305" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-306" > < a href = "#cb1-306" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-307" > < a href = "#cb1-307" aria-hidden = "true" tabindex = "-1" > < / a > sort_order < span class = "op" > =< / span > by_intervention[< span class = "st" > " intervention" < / span > ].value_counts().index< / span >
< span id = "cb1-308" > < a href = "#cb1-308" aria-hidden = "true" tabindex = "-1" > < / a > i < span class = "op" > =< / span > by_intervention[by_intervention[< span class = "st" > " intervention" < / span > ].< span class = "bu" > str< / span > .contains(< span class = "vs" > r" (?:structural|institutional|agency)" < / span > ) < span class = "op" > ==< / span > < span class = "va" > False< / span > ]< / span >
< span id = "cb1-309" > < a href = "#cb1-309" aria-hidden = "true" tabindex = "-1" > < / a > fig < span class = "op" > =< / span > plt.figure()< / span >
< span id = "cb1-310" > < a href = "#cb1-310" aria-hidden = "true" tabindex = "-1" > < / a > fig.set_size_inches(< span class = "dv" > 6< / span > , < span class = "dv" > 3< / span > )< / span >
< span id = "cb1-311" > < a href = "#cb1-311" aria-hidden = "true" tabindex = "-1" > < / a > ax < span class = "op" > =< / span > sns.countplot(i, x< span class = "op" > =< / span > < span class = "st" > " intervention" < / span > , hue< span class = "op" > =< / span > < span class = "st" > " projected" < / span > ,order< span class = "op" > =< / span > i[< span class = "st" > " intervention" < / span > ].value_counts().index)< / span >
< span id = "cb1-312" > < a href = "#cb1-312" aria-hidden = "true" tabindex = "-1" > < / a > plt.setp(ax.get_xticklabels(), rotation< span class = "op" > =< / span > < span class = "dv" > 45< / span > , ha< span class = "op" > =< / span > < span class = "st" > " right" < / span > ,< / span >
< span id = "cb1-313" > < a href = "#cb1-313" aria-hidden = "true" tabindex = "-1" > < / a > rotation_mode< span class = "op" > =< / span > < span class = "st" > " anchor" < / span > )< / span >
< span id = "cb1-314" > < a href = "#cb1-314" aria-hidden = "true" tabindex = "-1" > < / a > plt.show()< / span >
< span id = "cb1-315" > < a href = "#cb1-315" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```< / span > < / span >
< span id = "cb1-316" > < a href = "#cb1-316" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-317" > < a href = "#cb1-317" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > stronger institutional-structural research focus in developed countries, with more structural-agency based in developing countries< / span >
< span id = "cb1-318" > < a href = "#cb1-318" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > employment creation as a category is often subsumed in other structural/institutional analyses< / span >
< span id = "cb1-319" > < a href = "#cb1-319" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > little evidence-based research on effect of interventions targeting education on world of work outcomes< / span >
< span id = "cb1-320" > < a href = "#cb1-320" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > spatial inequality most evenly geographically spread evidence base< / span >
< span id = "cb1-321" > < a href = "#cb1-321" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "ss" > - < / span > empirical base on interventions targeting disability inequalities strongly restricted on developed countries, especially United States< / span >
< span id = "cb1-322" > < a href = "#cb1-322" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-325" > < a href = "#cb1-325" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```{python}< / span > < / span >
< span id = "cb1-326" > < a href = "#cb1-326" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| echo: false< / span > < / span >
< span id = "cb1-327" > < a href = "#cb1-327" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| label: fig-countries< / span > < / span >
< span id = "cb1-328" > < a href = "#cb1-328" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| fig-cap: Country spread< / span > < / span >
< span id = "cb1-329" > < a href = "#cb1-329" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > #| column: screen< / span > < / span >
< span id = "cb1-330" > < a href = "#cb1-330" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-331" > < a href = "#cb1-331" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "co" > # load zotero-based metadata: citations and uses< / span > < / span >
< span id = "cb1-332" > < a href = "#cb1-332" aria-hidden = "true" tabindex = "-1" > < / a > pi < span class = "op" > =< / span > (pd.DataFrame([< / span >
< span id = "cb1-333" > < a href = "#cb1-333" aria-hidden = "true" tabindex = "-1" > < / a > [< / span >
< span id = "cb1-334" > < a href = "#cb1-334" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " doi" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " doi" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-335" > < a href = "#cb1-335" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " times-cited" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " times-cited" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-336" > < a href = "#cb1-336" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " usage" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " usage" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-337" > < a href = "#cb1-337" aria-hidden = "true" tabindex = "-1" > < / a > entry[< span class = "st" > " keywords" < / span > ] < span class = "cf" > if< / span > < span class = "st" > " keywords" < / span > < span class = "kw" > in< / span > entry.fields_dict < span class = "cf" > else< / span > < span class = "va" > None< / span > ,< / span >
< span id = "cb1-338" > < a href = "#cb1-338" aria-hidden = "true" tabindex = "-1" > < / a > ]< / span >
< span id = "cb1-339" > < a href = "#cb1-339" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "cf" > for< / span > entry < span class = "kw" > in< / span > bib_sample.entries< / span >
< span id = "cb1-340" > < a href = "#cb1-340" aria-hidden = "true" tabindex = "-1" > < / a > ], columns < span class = "op" > =< / span > [< span class = "st" > " doi" < / span > , < span class = "st" > " cited" < / span > , < span class = "st" > " usage" < / span > , < span class = "st" > " keywords" < / span > ])< / span >
< span id = "cb1-341" > < a href = "#cb1-341" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates(< span class = "st" > " doi" < / span > )< / span >
< span id = "cb1-342" > < a href = "#cb1-342" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-343" > < a href = "#cb1-343" aria-hidden = "true" tabindex = "-1" > < / a > country< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " keywords" < / span > ].< span class = "bu" > str< / span > .replace(< span class = "st" > " < / span > < span class = "ch" > \\< / span > < span class = "st" > " < / span > , < span class = "st" > " " < / span > ).< span class = "bu" > str< / span > .extract(< span class = "st" > ' country::([\w\_]+),?' < / span > )< / span >
< span id = "cb1-344" > < a href = "#cb1-344" aria-hidden = "true" tabindex = "-1" > < / a > ).dropna(subset< span class = "op" > =< / span > < span class = "st" > " country" < / span > )< / span >
< span id = "cb1-345" > < a href = "#cb1-345" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-346" > < a href = "#cb1-346" aria-hidden = "true" tabindex = "-1" > < / a > country< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " country" < / span > ].< span class = "bu" > str< / span > .replace(< span class = "st" > " _" < / span > , < span class = "st" > " " < / span > ).< span class = "bu" > str< / span > .replace(< span class = "st" > " US" < / span > , < span class = "st" > " United States" < / span > ).< span class = "bu" > str< / span > .replace(< span class = "st" > " Britain" < / span > , < span class = "st" > " United Kingdom" < / span > ),< / span >
< span id = "cb1-347" > < a href = "#cb1-347" aria-hidden = "true" tabindex = "-1" > < / a > projected < span class = "op" > =< / span > < span class = "dv" > 1< / span > < / span >
< span id = "cb1-348" > < a href = "#cb1-348" aria-hidden = "true" tabindex = "-1" > < / a > ).reset_index()< / span >
< span id = "cb1-349" > < a href = "#cb1-349" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-350" > < a href = "#cb1-350" aria-hidden = "true" tabindex = "-1" > < / a > pi< / span >
< span id = "cb1-351" > < a href = "#cb1-351" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-352" > < a href = "#cb1-352" aria-hidden = "true" tabindex = "-1" > < / a > by_country < span class = "op" > =< / span > (pd.concat([< / span >
< span id = "cb1-353" > < a href = "#cb1-353" aria-hidden = "true" tabindex = "-1" > < / a > bib_df.groupby([< span class = "st" > " author" < / span > , < span class = "st" > " year" < / span > , < span class = "st" > " title" < / span > ])< / span >
< span id = "cb1-354" > < a href = "#cb1-354" aria-hidden = "true" tabindex = "-1" > < / a > .agg(< / span >
< span id = "cb1-355" > < a href = "#cb1-355" aria-hidden = "true" tabindex = "-1" > < / a > {< / span >
< span id = "cb1-356" > < a href = "#cb1-356" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "st" > " country" < / span > : < span class = "kw" > lambda< / span > _col: < span class = "st" > " ; " < / span > .join(_col),< / span >
< span id = "cb1-357" > < a href = "#cb1-357" aria-hidden = "true" tabindex = "-1" > < / a > }< / span >
< span id = "cb1-358" > < a href = "#cb1-358" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-359" > < a href = "#cb1-359" aria-hidden = "true" tabindex = "-1" > < / a > .assign(< / span >
< span id = "cb1-360" > < a href = "#cb1-360" aria-hidden = "true" tabindex = "-1" > < / a > projected< span class = "op" > =< / span > < span class = "dv" > 0< / span > < / span >
< span id = "cb1-361" > < a href = "#cb1-361" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-362" > < a href = "#cb1-362" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-363" > < a href = "#cb1-363" aria-hidden = "true" tabindex = "-1" > < / a > .reset_index()< / span >
< span id = "cb1-364" > < a href = "#cb1-364" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates() , pi[pi[< span class = "st" > " keywords" < / span > ].< span class = "bu" > str< / span > .contains(< span class = "st" > " relevant" < / span > ) < span class = "op" > ==< / span > < span class = "va" > True< / span > ]])< / span >
< span id = "cb1-365" > < a href = "#cb1-365" aria-hidden = "true" tabindex = "-1" > < / a > .assign( country< span class = "op" > =< / span > < span class = "kw" > lambda< / span > _df: _df[< span class = "st" > " country" < / span > ].< span class = "bu" > apply< / span > (< / span >
< span id = "cb1-366" > < a href = "#cb1-366" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "kw" > lambda< / span > _cell: < span class = "bu" > set< / span > ([x.strip() < span class = "cf" > for< / span > x < span class = "kw" > in< / span > re.sub(< span class = "vs" > r" \(.*\)" < / span > , < span class = "st" > " " < / span > , _cell).split(< span class = "st" > " ;" < / span > )])< / span >
< span id = "cb1-367" > < a href = "#cb1-367" aria-hidden = "true" tabindex = "-1" > < / a > ),< / span >
< span id = "cb1-368" > < a href = "#cb1-368" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-369" > < a href = "#cb1-369" aria-hidden = "true" tabindex = "-1" > < / a > .explode(< span class = "st" > " country" < / span > )< / span >
< span id = "cb1-370" > < a href = "#cb1-370" aria-hidden = "true" tabindex = "-1" > < / a > .drop_duplicates()< / span >
< span id = "cb1-371" > < a href = "#cb1-371" aria-hidden = "true" tabindex = "-1" > < / a > )< / span >
< span id = "cb1-372" > < a href = "#cb1-372" aria-hidden = "true" tabindex = "-1" > < / a > < / span >
< span id = "cb1-373" > < a href = "#cb1-373" aria-hidden = "true" tabindex = "-1" > < / a > sort_order < span class = "op" > =< / span > by_country[< span class = "st" > " country" < / span > ].value_counts().index< / span >
< span id = "cb1-374" > < a href = "#cb1-374" aria-hidden = "true" tabindex = "-1" > < / a > i < span class = "op" > =< / span > by_country[by_country[< span class = "st" > " country" < / span > ].< span class = "bu" > str< / span > .contains(< span class = "vs" > r" (?:structural|institutional|agency)" < / span > ) < span class = "op" > ==< / span > < span class = "va" > False< / span > ]< / span >
< span id = "cb1-375" > < a href = "#cb1-375" aria-hidden = "true" tabindex = "-1" > < / a > fig < span class = "op" > =< / span > plt.figure()< / span >
< span id = "cb1-376" > < a href = "#cb1-376" aria-hidden = "true" tabindex = "-1" > < / a > fig.set_size_inches(< span class = "dv" > 12< / span > , < span class = "dv" > 5< / span > )< / span >
< span id = "cb1-377" > < a href = "#cb1-377" aria-hidden = "true" tabindex = "-1" > < / a > ax < span class = "op" > =< / span > sns.countplot(i, x< span class = "op" > =< / span > < span class = "st" > " country" < / span > , hue< span class = "op" > =< / span > < span class = "st" > " projected" < / span > ,order< span class = "op" > =< / span > i[< span class = "st" > " country" < / span > ].value_counts().index)< / span >
< span id = "cb1-378" > < a href = "#cb1-378" aria-hidden = "true" tabindex = "-1" > < / a > plt.setp(ax.get_xticklabels(), rotation< span class = "op" > =< / span > < span class = "dv" > 45< / span > , ha< span class = "op" > =< / span > < span class = "st" > " right" < / span > ,< / span >
< span id = "cb1-379" > < a href = "#cb1-379" aria-hidden = "true" tabindex = "-1" > < / a > rotation_mode< span class = "op" > =< / span > < span class = "st" > " anchor" < / span > )< / span >
< span id = "cb1-380" > < a href = "#cb1-380" aria-hidden = "true" tabindex = "-1" > < / a > plt.show()< / span >
< span id = "cb1-381" > < a href = "#cb1-381" aria-hidden = "true" tabindex = "-1" > < / a > < span class = "in" > ```< / span > < / span >
< / code > < button title = "Copy to Clipboard" class = "code-copy-button" > < i class = "bi" > < / i > < / button > < / pre > < / div >
< / div > < / div > < / div > < / div > < / div >
< / div > <!-- /content -->
< / body > < / html >
