diff --git a/02-data/processed/extracted.csv b/02-data/processed/extracted.csv
index d8b703d..3275ad5 100644
--- a/02-data/processed/extracted.csv
+++ b/02-data/processed/extracted.csv
@@ -7,9 +7,6 @@ Xu2021,"Xu, C., Han, M., Dossou, T. A. M., & Bekun, F. V.",2021,"Trade openness,
Wong2019,"Wong, S. A.",2019,Minimum wage impacts on wages and hours worked of low-income workers in Ecuador,World Development,https://doi.org/10.1016/j.worlddev.2018.12.004,article,development,Ecuador,2011-2014,12.0,implicit,wage workers,national employment survey (ENEMDU),quasi-experimental,difference-in-difference approach,1624422.0,individual,"national, census",1.0,,some small sort-dependency in panel data; can only account for effects in period of economic growth,,minimum wage,1,1,0,income; gender,0.0,1.0,Gini coeff,"decreased income inequality through significant increase on income of low-wage earners; larger effect for agricultural workers, smaller for women; potentially negative impact on income of high-earners",income-compression effect,-1.0,2.0,5.0,3.0
Wong2019,"Wong, S. A.",2019,Minimum wage impacts on wages and hours worked of low-income workers in Ecuador,World Development,https://doi.org/10.1016/j.worlddev.2018.12.004,article,development,Ecuador,2011-2014,12.0,implicit,wage workers,national employment survey (ENEMDU),quasi-experimental,difference-in-difference approach,1624422.0,individual,"national, census",1.0,,some small sort-dependency in panel data; can only account for effects in period of economic growth,,minimum wage,1,1,0,income; gender,0.0,0.0,hours worked,significant effect on hours worked; no significant spillover effect on workers in control group; significant negative impact on female hours worked,possibly decreased intensive margin for female workers; affecting lower income increase of women,1.0,0.0,5.0,3.0
Whitworth2021,"Whitworth, A.",2021,Spatial creaming and parking?: The case of the UK work programme,Applied Spatial Analysis and Policy,https://doi.org/10.1007/s12061-020-09349-0,article,economics,United Kingdom,2011-2017,72.0,implicit,unemployed,Department for Work and Pensions Work Programme statistics,observational,three-stage linear model,1494.0,individual,national,0.0,social creaming & parking (used spatially),no causal inferrence attempted,,work programme,0,1,0,spatial,1.0,0.0,employment,already deprived areas experience further deprivation,providers de-prioritize job-weak areas (spatial parking),-1.0,2.0,4.0,0.0
-Wang2020,"Wang, C., Deng, M., & Deng, J.",2020,Factor reallocation and structural transformation implications of grain subsidies in China,Journal of Asian Economics,https://doi.org/10.1016/j.asieco.2020.101248,article,economics,China,2007-2016,108.0,implicit,rural workers,TERMCN-Land database; Chinese Input-Output Table 2007,simulation,historical and TERMCN-Land simulation model,,sector,,0.0,,aggregate national employment exogenous to model; strong correlation to Chinese economic characteristics makes generalisability difficult,,subsidy (firm-level),0,1,0,income; spatial,1.0,1.0,income ratio,the rural-urban income inequality is exacerbated if grain subsidies are removed; over the long term this increase attenuates but income ratio remains decreased for rural labour,"displacement of rural unskilled labour; unskilled labour supply increase, labour difficult to absorb into manufacturing/service sectors; low income/price elasticity for agr. products lower rural income",1.0,2.0,0.0,0.0
-Thoresen2021,"Thoresen, S. H., Cocks, E., & Parsons, R.",2021,Three year longitudinal study of graduate employment outcomes for Australian apprentices and trainees with and without disabilities,International journal of disability development and education,https://doi.org/10.1080/1034912X.2019.1699648,article,education,Australia,2011-204,36.0,explicit,disabled,experimental survey,quasi-experimental,"quantitative survey (n=489); qualitative semi-structured face-to-face interviews (n=30); annual postal survey, baseline and 2 follow-ups; generalised estimating equation GEE",489.0,individual,local,0.0,,"non-representative sample, over-representation of learning disability; limited generalisability through sample LFP bias and attrition bias; small control sample size",Disaggregated results for female participants overall more unequal,training,0,1,1,disability; income,1.0,0.0,hours worked,"slightly lower for disabled group initially, increase to no significant difference with non-disabled group at last survey",significant but small overall increase (3.1 hours to 1 hour difference); fluctuations for non-disability group,1.0,2.0,2.0,4.0
-Thoresen2021,"Thoresen, S. H., Cocks, E., & Parsons, R.",2021,Three year longitudinal study of graduate employment outcomes for Australian apprentices and trainees with and without disabilities,International journal of disability development and education,https://doi.org/10.1080/1034912X.2019.1699648,article,education,Australia,2011-204,36.0,explicit,disabled,experimental survey,quasi-experimental,"quantitative survey (n=489); qualitative semi-structured face-to-face interviews (n=30); annual postal survey, baseline and 2 follow-ups; generalised estimating equation GEE",489.0,individual,local,0.0,,"non-representative sample, over-representation of learning disability; limited generalisability through sample LFP bias and attrition bias; small control sample size",Disaggregated results for female participants overall more unequal,training,0,1,1,disability; income,1.0,0.0,hourly/weekly income,wages of disability group substantially lower than non-disability; increases to be non-significant over time; lower for female and disability-pension recipient groups,strong initial diff means disability group potentially more often initially employed at junior rates or skewed through attrition bias,1.0,2.0,2.0,4.0
Suh2017,"Suh, M.-G.",2017,Determinants of female labor force participation in south korea: Tracing out the U-shaped curve by economic growth,Social Indicators Research,https://doi.org/10.1007/s11205-016-1245-1,article,sociology,"Korea, Rep.",1980-2014,,implicit,married women,Statistical Database in Statistical Information Service Korea 2015,quasi-experimental,OLS regression; log-linear analysis; contingency analysis with cross-tab statistics; Gini coeff as income inequality indicator,35.0,case,"national, census",0.0,,,,education,0,1,0,income; generational; gender,1.0,1.0,employment,education significant increase in married women's employment; female labour force participation negative correlation with income inequality; female education also positively affects daughters' education level,"education being necessary not sufficient condition, also influenced by family size and structure",1.0,2.0,5.0,2.0
Stock2021,"Stock, R. (2021).",2021,Bright as night: Illuminating the antinomies of `gender positive’ solar development,World Development,https://doi.org/10.1016/j.worlddev.2020.105196,article,development,India,2018,1.0,implicit,women,"baseline survey, interviews",observational,quantitative survey and in-depth interviews; discourse analysis,200.0,household,"subnational, rural",0.0,authoritative knowledge power framework (Laclau&Mouffe),no causal research,,infrastructure,0,1,0,gender; income; spatial,1.0,0.0,employment,insignificant increased employment probability; advantaged women predominantly belong to dominant castes,project capture by village female elites; women of disadvantaged castes further excluded from training and work opportunities,1.0,0.0,3.0,0.0
Standing2015,"Standing, G.",2015,Why Basic Income’s Emancipatory Value Exceeds Its Monetary Value,Basic Income Studies,https://doi.org/10.1515/bis-2015-0021,article,economics,India,2010-2013,18.0,implicit,low-income households,baseline & 3 follow-up surveys and censuses; structured interviews,experimental,"rural RCT, randomization at village level; 18/12 months of ubi provision with follow up surveys and interviews",1665.0,household,"subnational, rural",1.0,"Lauderdale paradox (money, if scarce becomes even more valuable resource)",,"ubi paid in addition to any other state transfers; included in sample for effects on work choice (forced to work for debtors, free to pursue own-work)",ubi,1,0,1,income; ethnicity,0.0,0.0,debt,ubi significantly decreases debts; results go beyond direct monetary value; households did not have to work for lenders/to pay off debt,directly enables debt reduction; reduces debt-dependency risks; avoids taking on new debt; enables choosing less exploitative forms of borrowing,-1.0,2.0,3.0,5.0
@@ -55,7 +52,6 @@ Adams2015,"Adams, S., & Atsu, F.",2015,Assessing the distributional effects of r
Adams2015,"Adams, S., & Atsu, F.",2015,Assessing the distributional effects of regulation in developing countries,Journal of Policy Modeling,https://doi.org/10.1016/j.jpolmod.2015.08.003,article,economics,global,1970-2012,,implicit,developing countries,panel data,quasi-experimental,"system general method of moments, fixed effects, OLS; using Gini coefficient",72.0,country,regional,0.0,,macro-level observations subsumed under region-level scale only,"LM regulations defined as hiring/firing, minimum wage, severance pay; business reg. bureaucracy costs, business starting costs, licensing and compliance costs; credit market oversight of banks, private sector credit, interest rate controls",regulation (labour),1,0,0,income,0.0,1.0,Gini coeff,labour regulations and business regulations negatively related to equitable income distribution while credit market regulation has no effect in income distribution; FDI unlikely to generate equity-oriented welfare effects; trade openness not significantly related,regulatory policies often lack institutional capability to optimize for benefits; policies require specific targeting of inequality reduction,1.0,2.0,4.0,4.0
Adams2015,"Adams, S., & Atsu, F.",2015,Assessing the distributional effects of regulation in developing countries,Journal of Policy Modeling,https://doi.org/10.1016/j.jpolmod.2015.08.003,article,economics,global,1970-2012,,implicit,developing countries,panel data,quasi-experimental,"system general method of moments, fixed effects, OLS; using Gini coefficient",72.0,country,regional,0.0,,macro-level observations subsumed under region-level scale only,"LM regulations defined as hiring/firing, minimum wage, severance pay; business reg. bureaucracy costs, business starting costs, licensing and compliance costs; credit market oversight of banks, private sector credit, interest rate controls",education (school enrolment),1,0,0,income,0.0,1.0,Gini coeff,school enrolment positively related to equitable income distribution,capacity-building for public administration practitioners; more context-adapted policies generated,-1.0,2.0,4.0,4.0
Alinaghi2020,"Alinaghi, N., Creedy, J., & Gemmell, N.",2020,The redistributive effects of a minimum wage increase in New Zealand: A microsimulation analysis,Australian Economic Review,https://doi.org/10.1111/1467-8462.12381,article,economics,New Zealand,2012-2013,,implicit,,New Zealand Household Economic Survey (HES),simulation,microsimulation model; uses Atkinson index,3500.0,individual,national,0.0,,"large sample weights may bias specific groups, e.g. sole parents",,minimum wage,1,1,0,income,0.0,1.0,Atkinson index,"small impact on inequality of income signals bad programme targeting; significant reduction in poverty measures for sole parents already in employment only, but insignificant for sole parents overall",many low-wage earners are secondary earners in higher income households; low-wage households often have no wage earners at all,-1.0,0.0,4.0,0.0
-Wang2016,"Wang, J., & Van Vliet, O.",2016,"Social Assistance and Minimum Income Benefits: Benefit Levels, Replacement Rates and Policies Across 26 Oecd Countries, 1990-2009",European Journal of Social Security,https://doi.org/10.1177/138826271601800401,article,economics,global,1990-2009,,implicit,low-income,"World Bank CPI indicators & Penn World Table; Social Assistance and Minimum Income Protection Dataset (Nelson, 2013)",observational,cross-country comparative analysis,26.0,country,regional,0.0,,some effects may stem from exchange rate/PPP changes instead,due to data availability indicator for real minimum benefits and replacement rates could be constructed for 26 OECD countries,direct transfers (social assistance),1,1,0,income,0.0,1.0,real wage; replacement rate,"real benefit levels increased in most countries, benefit levels increasing more than consumer prices; income replacement rates mixed outcomes with decreases in some countries where real benefit levels increased",bulk of increases comes from deliberate policy changes; but benefit levels not linked to wages and policy changes not taking into account changes in wages,1.0,,4.0,0.0
Sotomayor2021,"Sotomayor, Orlando J.",2021,Can the minimum wage reduce poverty and inequality in the developing world? Evidence from Brazil,World Development,https://doi.org/10.1016/j.worlddev.2020.105182,article,economics,Brazil,1995-2015,12.0,implicit,workers,national administrative surveys Monthly Employment survey (PME),quasi-experimental,difference-in-difference estimator,40000.0,household,"national, census",1.0,,"survey data limited to per dwelling, can not account for inhabitants moving",,minimum wage,1,0,0,income,0.0,0.0,poverty,within three months of minimum wage increases poverty declined by 2.8%,,-1.0,2.0,5.0,3.0
Sotomayor2021,"Sotomayor, Orlando J.",2021,Can the minimum wage reduce poverty and inequality in the developing world? Evidence from Brazil,World Development,https://doi.org/10.1016/j.worlddev.2020.105182,article,economics,Brazil,1995-2015,12.0,implicit,workers,national administrative surveys Monthly Employment survey (PME),quasi-experimental,difference-in-difference estimator,40000.0,household,"national, census",1.0,,"survey data limited to per dwelling, can not account for inhabitants moving",,minimum wage,1,0,0,income,0.0,1.0,Gini coeff,inequality declined by 2.4%; decreasing impact over time; diminishing returns when minimum is high relative to median earnings,unemployment costs (job losses) overwhelmed by benefits (higher wages); but inelastic relationship of increase and changes in poverty,-1.0,2.0,5.0,3.0
Al-Mamun2014,"Al-Mamun, A., Wahab, S. A., Mazumder, M. N. H., & Su, Z.",2014,Empirical Investigation on the Impact of Microcredit on Women Empowerment in Urban Peninsular Malaysia,Journal of Developing Areas,https://doi.org/10.1353/jda.2014.0030,article,development,Malaysia,2011,2.0,implicit,women,structured face-to-face interviews,quasi-experimental,"cross-sectional stratified random sampling; OLS, multiple regression analysis",242.0,individual,"subnational, urban",1.0,"household economic portfolio model (Chen & Dunn, 1996)",can not establish full experimental design,,microcredit; training,0,0,1,gender; income,1.0,0.0,empowerment index (personal savings; personal income; asset ownership),increase in household decision-making for women; increase in economic security for women; constrained by inability for individuals to obtain loans,individual access to finance; collective agency increase through meetings and training,1.0,2.0,3.0,2.0
@@ -69,4 +65,8 @@ Shin2006,"Shin, J., & Moon, S.",2006,"Fertility, relative wages, and labor marke
Alexiou2023,"Alexiou, C., & Trachanas, E.",2023,The impact of trade unions and government party orientation on income inequality: Evidence from 17 OECD economies,Journal of Economic Studies,https://doi.org/10.1108/JES-12-2021-0612,article,economics,Australia; Austria; Belgium; Canada; Denmark; Finland; France; Germany; Italy; Japan; Netherlands; New Zealand; Norway; Spain; Sweden; United Kingdom; United States,2000-2016,,,,Standardized World Income Inequality Database (SWIID) OECD panel data,quasi-experimental,"panel fixed effects approach, Driscoll and Kraay non-parametric covariance matrix estimator",18.0,country,regional,1.0,power resources theory,"can not account for individual drivers such as collective bargaining, arbitration, etc",,collective action (trade unionization),1,1,0,income; gender,0.0,1.0,"Gini coeff (equivalized household disposable income, market income, manufacturing pay)",unionization strongly related with decreasing income inequality; right-wing institutional contexts related with increased income inequality,redistribution of political power under unions; weak unionization increases post-redistribution inequality,-1.0,2.0,4.0,2.0
Mun2018,"Mun, E., & Jung, J.",2018,"Policy generosity, employer heterogeneity, and women’s employment opportunities: The welfare state paradox reexamined",American Sociological Review,https://doi.org/10.1177/0003122418772857,article,sociology,Japan,1992-2009,84.0,explicit,working mothers,Japan Company Handbook for Job Searchers,quasi-experimental,potential outcomes framework; fixed-effects analysis,600.0,enterprise,national,0.0,welfare state paradox (over-representation of women in low-authority jobs in progressive welfare states),limited generalizability with unique Japanese LM institutional features; limited ability to explain voluntary effects as lasting or as symbolic compliance and impression management,,paid leave (childcare),1,0,0,gender,1.0,0.0,job quality,"no change for promotions for firms not previously providing leave, positive promotion impact for firms already providing leave; incentive-based policies may lead to larger effects",voluntary compliance to maintain positive reputations,1.0,1.0,4.0,2.0
Mun2018,"Mun, E., & Jung, J.",2018,"Policy generosity, employer heterogeneity, and women’s employment opportunities: The welfare state paradox reexamined",American Sociological Review,https://doi.org/10.1177/0003122418772857,article,sociology,Japan,1992-2009,84.0,explicit,working mothers,Japan Company Handbook for Job Searchers,quasi-experimental,potential outcomes framework; fixed-effects analysis,600.0,enterprise,national,0.0,welfare state paradox (over-representation of women in low-authority jobs in progressive welfare states),limited generalizability with unique Japanese LM institutional features; limited ability to explain voluntary effects as lasting or as symbolic compliance and impression management,,paid leave (childcare),1,0,0,gender,1.0,0.0,employment,no increase in hiring discrimination against women reflected as decreased employment probability,decreases may be due to supply-side mechanisms based on individual career planning and reinforced existing gender division of household labour,0.0,0.0,4.0,2.0
+Thoresen2021,"Thoresen, S. H., Cocks, E., & Parsons, R.",2021,Three year longitudinal study of graduate employment outcomes for Australian apprentices and trainees with and without disabilities,International journal of disability development and education,https://doi.org/10.1080/1034912X.2019.1699648,article,education,Australia,2011-204,36.0,explicit,disabled,experimental survey,quasi-experimental,"quantitative survey (n=489); qualitative semi-structured face-to-face interviews (n=30); annual postal survey, baseline and 2 follow-ups; generalised estimating equation GEE",489.0,individual,local,0.0,,"non-representative sample, over-representation of learning disability; limited generalisability through sample LFP bias and attrition bias; small control sample size",Disaggregated results for female participants overall more unequal,training,0,1,1,disability; income,1.0,0.0,hours worked,"slightly lower for disabled group initially, increase to no significant difference with non-disabled group at last survey",significant but small overall increase (3.1 hours to 1 hour difference); fluctuations for non-disability group,1.0,2.0,2.0,4.0
+Thoresen2021,"Thoresen, S. H., Cocks, E., & Parsons, R.",2021,Three year longitudinal study of graduate employment outcomes for Australian apprentices and trainees with and without disabilities,International journal of disability development and education,https://doi.org/10.1080/1034912X.2019.1699648,article,education,Australia,2011-204,36.0,explicit,disabled,experimental survey,quasi-experimental,"quantitative survey (n=489); qualitative semi-structured face-to-face interviews (n=30); annual postal survey, baseline and 2 follow-ups; generalised estimating equation GEE",489.0,individual,local,0.0,,"non-representative sample, over-representation of learning disability; limited generalisability through sample LFP bias and attrition bias; small control sample size",Disaggregated results for female participants overall more unequal,training,0,1,1,disability; income,1.0,0.0,hourly/weekly income,wages of disability group substantially lower than non-disability; increases to be non-significant over time; lower for female and disability-pension recipient groups,strong initial diff means disability group potentially more often initially employed at junior rates or skewed through attrition bias,1.0,2.0,2.0,4.0
+Wang2016,"Wang, J., & Van Vliet, O.",2016,"Social Assistance and Minimum Income Benefits: Benefit Levels, Replacement Rates and Policies Across 26 Oecd Countries, 1990-2009",European Journal of Social Security,https://doi.org/10.1177/138826271601800401,article,economics,global,1990-2009,,implicit,low-income,"World Bank CPI indicators & Penn World Table; Social Assistance and Minimum Income Protection Dataset (Nelson, 2013)",observational,cross-country comparative analysis,26.0,country,regional,0.0,,some effects may stem from exchange rate/PPP changes instead,due to data availability indicator for real minimum benefits and replacement rates could be constructed for 26 OECD countries,direct transfers (social assistance),1,1,0,income,0.0,1.0,real wage; replacement rate,"real benefit levels increased in most countries, benefit levels increasing more than consumer prices; income replacement rates mixed outcomes with decreases in some countries where real benefit levels increased",bulk of increases comes from deliberate policy changes; but benefit levels not linked to wages and policy changes not taking into account changes in wages,1.0,,4.0,0.0
+Wang2020,"Wang, C., Deng, M., & Deng, J.",2020,Factor reallocation and structural transformation implications of grain subsidies in China,Journal of Asian Economics,https://doi.org/10.1016/j.asieco.2020.101248,article,economics,China,2007-2016,108.0,implicit,rural workers,TERMCN-Land database; Chinese Input-Output Table 2007,simulation,historical and TERMCN-Land structural simulation model,,sector,,0.0,,aggregate national employment exogenous to model; strong correlation to Chinese economic characteristics makes generalisability difficult,,subsidy (firm-level),0,1,0,income; spatial,1.0,1.0,income ratio,the rural-urban income inequality is exacerbated if grain subsidies are removed; over the long term this increase attenuates but income ratio remains decreased for rural labour,"displacement of rural unskilled labour; unskilled labour supply increase, labour difficult to absorb into manufacturing/service sectors; low income/price elasticity for agr. products lower rural income",1.0,2.0,0.0,0.0
diff --git a/05-final_paper/notes.docx b/05-final_paper/notes.docx
index 98f4d99..38de92d 100644
Binary files a/05-final_paper/notes.docx and b/05-final_paper/notes.docx differ
diff --git a/05-final_paper/notes.html b/05-final_paper/notes.html
index 2e23178..ae48bb7 100644
--- a/05-final_paper/notes.html
+++ b/05-final_paper/notes.html
@@ -2,7 +2,7 @@
@@ -3706,13 +3768,17 @@ generally, [from UN, 2023, A call to action to save SDG10, Policy Brief], separa
3.1 Inclusion criteria
-
-
-
-
Table 1: Study inclusion and exclusion scoping criteria
+
+
+
+Table 1: Study inclusion and exclusion scoping criteria {#tbl-inclusion-criteria}
+
+
+
+
-
+
@@ -3739,21 +3805,26 @@ generally, [from UN, 2023, A call to action to save SDG10, Policy Brief], separa
gray literature superseded by white literature publication
-
Study focus
-
inequality or labour market outcomes as primary outcome (dependent variable)
-
neither inequality nor labour market outcomes as dependent variable
+
Study data
+
evidence-based study or based on empirical approach
+
no empirical approach or not clearly based on evidential data
+
Study focus
+
effects on inequality/equality as primary outcome (dependent variable)
+
neither inequality nor equality outcomes as dependent variable
+
+
policy measure or strategy as primary intervention (independent variable)
no policy measure/strategy as intervention or relationship unclear
-
+
specifically relates to some dimension of world of work
exists outside world of work for both independent and dependent variables
-
+
focus on dimension of inequality in analysis
no focus on mention of inequality in analysis
@@ -3762,6 +3833,8 @@ generally, [from UN, 2023, A call to action to save SDG10, Policy Brief], separa
+
+
not currently used as criteria: - we are probably including qualitative studies (to be tagged) - perhaps studies <2000 (to be tagged) to count quantity?
@@ -4524,7 +4597,7 @@ generally, [from UN, 2023, A call to action to save SDG10, Policy Brief], separa
7 Relevant references
-
+
Chang, Y.-S., Harger, L., Beake, S., & Bick, D. (2021). Women’s and Employers’ Experiences and Views of Combining Breastfeeding with a Return to Paid Employment: A Systematic Review of Qualitative Studies. Journal of Midwifery Womens Health, 66(5), 641–655. https://doi.org/10.1111/jmwh.13243
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if (showAllCode) {
showAllCode.addEventListener("click", toggleCodeHandler(true));
}
- function tippyHover(el, contentFn) {
+ var localhostRegex = new RegExp(/^(?:http|https):\/\/localhost\:?[0-9]*\//);
+ var mailtoRegex = new RegExp(/^mailto:/);
+ var filterRegex = new RegExp('/' + window.location.host + '/');
+ var isInternal = (href) => {
+ return filterRegex.test(href) || localhostRegex.test(href) || mailtoRegex.test(href);
+ }
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+ for (var i=0; i {
+ // Strip column container classes
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+ el.classList.remove("page-full", "page-columns");
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+ stripColumnClz(child);
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+ stripColumnClz(note)
+ if (id === null || id.startsWith('sec-')) {
+ // Special case sections, only their first couple elements
+ const container = document.createElement("div");
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+ for (let i = 1; i < note.children.length; i++) {
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+ window.Quarto.typesetMath(container);
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+ return container.innerHTML
+ } else {
+ if (window.Quarto?.typesetMath) {
+ window.Quarto.typesetMath(note);
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+ return note.innerHTML;
+ }
+ } else {
+ // Remove any anchor links if they are present
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+ if (anchorLink) {
+ anchorLink.remove();
+ }
+ if (window.Quarto?.typesetMath) {
+ window.Quarto.typesetMath(note);
+ }
+ // TODO in 1.5, we should make sure this works without a callout special case
+ if (note.classList.contains("callout")) {
+ return note.outerHTML;
+ } else {
+ return note.innerHTML;
+ }
+ }
+ }
+ for (var i=0; i res.text())
+ .then(html => {
+ const parser = new DOMParser();
+ const htmlDoc = parser.parseFromString(html, "text/html");
+ const note = htmlDoc.getElementById(id);
+ if (note !== null) {
+ const html = processXRef(id, note);
+ instance.setContent(html);
+ }
+ }).finally(() => {
+ instance.enable();
+ instance.show();
+ });
+ }
+ } else {
+ // See if we can fetch a full url (with no hash to target)
+ // This is a special case and we should probably do some content thinning / targeting
+ fetch(url)
+ .then(res => res.text())
+ .then(html => {
+ const parser = new DOMParser();
+ const htmlDoc = parser.parseFromString(html, "text/html");
+ const note = htmlDoc.querySelector('main.content');
+ if (note !== null) {
+ // This should only happen for chapter cross references
+ // (since there is no id in the URL)
+ // remove the first header
+ if (note.children.length > 0 && note.children[0].tagName === "HEADER") {
+ note.children[0].remove();
+ }
+ const html = processXRef(null, note);
+ instance.setContent(html);
+ }
+ }).finally(() => {
+ instance.enable();
+ instance.show();
+ });
+ }
+ }, function(instance) {
+ });
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let selectedAnnoteEl;
const selectorForAnnotation = ( cell, annotation) => {
@@ -4798,6 +5013,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
}
div.style.top = top - 2 + "px";
div.style.height = height + 4 + "px";
+ div.style.left = 0;
let gutterDiv = window.document.getElementById("code-annotation-line-highlight-gutter");
if (gutterDiv === null) {
gutterDiv = window.document.createElement("div");
@@ -4823,6 +5039,32 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
});
selectedAnnoteEl = undefined;
};
+ // Handle positioning of the toggle
+ window.addEventListener(
+ "resize",
+ throttle(() => {
+ elRect = undefined;
+ if (selectedAnnoteEl) {
+ selectCodeLines(selectedAnnoteEl);
+ }
+ }, 10)
+ );
+ function throttle(fn, ms) {
+ let throttle = false;
+ let timer;
+ return (...args) => {
+ if(!throttle) { // first call gets through
+ fn.apply(this, args);
+ throttle = true;
+ } else { // all the others get throttled
+ if(timer) clearTimeout(timer); // cancel #2
+ timer = setTimeout(() => {
+ fn.apply(this, args);
+ timer = throttle = false;
+ }, ms);
+ }
+ };
+ }
// Attach click handler to the DT
const annoteDls = window.document.querySelectorAll('dt[data-target-cell]');
for (const annoteDlNode of annoteDls) {
@@ -4880,20 +5122,6 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
});
}
}
- var localhostRegex = new RegExp(/^(?:http|https):\/\/localhost\:?[0-9]*\//);
- var filterRegex = new RegExp('/' + window.location.host + '/');
- var isInternal = (href) => {
- return filterRegex.test(href) || localhostRegex.test(href);
- }
- // Inspect non-navigation links and adorn them if external
- var links = window.document.querySelectorAll('a[href]:not(.nav-link):not(.navbar-brand):not(.toc-action):not(.sidebar-link):not(.sidebar-item-toggle):not(.pagination-link):not(.no-external):not([aria-hidden]):not(.dropdown-item)');
- for (var i=0; i
Source Code
---
@@ -5821,4 +6049,5 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
+