fix(repo): Rename all references to data and output dir

README.md

@@ -4,14 +4,14 @@
 This repository contains all data, modelling and processing source code and the complete textual content to reproduce the scoping review study.
 The most up-to-date version of this repository can always be found [here](https://git.martyoeh.me/professional/wow-inequalities).
 
-Raw, intermediate and processed data can all be found in the `02-data/` directory:
+Raw, intermediate and processed data can all be found in the `data/` directory:
 Raw data include the unmodified database queries using the scoping review search terms.
 Intermediate data are made up of the bibtex file produced by Zotero, after tagging and sorting in a Zotero library, ready to be re-imported into the application.
 Processed data include the fully extracted studies which make up the main sample for the review.
 
 The full article text and code can be found in the `scoping_review.qmd` file.
 It makes use of supplementary processing code which resides in the `src/` directory,
-mainly to load processed data from the `02-data/` directory and turn it into `.csv` data,
+mainly to load processed data from the `data/` directory and turn it into `.csv` data,
 as well as pre-processing those for visualization and validity ranking within the study.
 
 ## Execution and Reproduction
@@ -35,6 +35,6 @@ Now, by invoking `make` the project can be rendered:
 make
 ```
 
-Make will by default extract the processed data and use it to render the full project into a pdf, an html and a docx version of the review, which are deposited in the `04-outputs/` directory.
+Make will by default extract the processed data and use it to render the full project into a pdf, an html and a docx version of the review, which are deposited in the `outputs/` directory.
 
 You can invoke any of the `extract`, `render`, `release` steps manually instead by executing e.g. `make extract`.

_quarto-article.yml

@@ -16,11 +16,11 @@ format:
     theme: darkly
   docx:
     filters:
-      # - pandoc-to-zotero-live
+      - pandoc-to-zotero-live
       - docx-landscape
     echo: false
     number-sections: true
-    reference-doc: 02-data/supplementary/justified.docx
+    reference-doc: data/supplementary/justified.docx
   elsevier-pdf:
     echo: false
     number-sections: true

_quarto-workingpaper.yml

@@ -1,6 +1,4 @@
 project:
-  title: "Key terms and definitions"
-  output-dir: 04-outputs
   render:
     - presentation_summary.md
     - notes.qmd
@@ -21,7 +19,7 @@ format:
   docx:
     echo: false
     number-sections: true
-    reference-doc: 02-data/supplementary/justified.docx
+    reference-doc: data/supplementary/justified.docx
     filters:
       - pandoc-to-zotero-live
       - docx-landscape

_quarto.yml

@@ -1,8 +1,8 @@
 project:
-  output-dir: 04-outputs
+  output-dir: output
   execute-dir: project
 
-bibliography: 02-data/intermediate/zotero-library.bib
+bibliography: data/intermediate/zotero-library.bib
 csl: /home/marty/documents/library/utilities/styles/APA-7.csl
 zoterolive:
   library: wow-inequalities

article.qmd

@@ -102,7 +102,7 @@ with a focus on the narrowing criteria specified in @tbl-inclusion-criteria.
 ::: {#tbl-inclusion-criteria}
 
 ```{python}
-inclusion_criteria = pd.read_csv("02-data/supplementary/inclusion-criteria.tsv", sep="\t")
+inclusion_criteria = pd.read_csv("data/supplementary/inclusion-criteria.tsv", sep="\t")
 Markdown(tabulate(inclusion_criteria, showindex=False, headers="keys", tablefmt="grid"))
 ```
 
@@ -152,7 +152,7 @@ ultimately resulting in the process represented in the PRISMA chart in @fig-pris
 ```{mermaid}
 %%| label: fig-prisma
 %%| fig-cap: PRISMA flowchart for scoping process
-%%| file: 02-data/processed/prisma.mmd
+%%| file: data/processed/prisma.mmd
 ```
 
 All relevant data concerning both their major findings and statistical significance are then extracted from the individual studies into a collective results matrix.
@@ -225,7 +225,7 @@ def strength_for(val):
     ]
 
 
-findings_institutional = pd.read_csv("02-data/supplementary/findings-institutional.csv")
+findings_institutional = pd.read_csv("data/supplementary/findings-institutional.csv")
 
 outp = Markdown(
     tabulate(
@@ -695,7 +695,7 @@ Another reason could be the actual implementation of different policy programmes
 ::: {#appatbl-wow-terms}
 
 ```{python}
-terms_wow = pd.read_csv("02-data/supplementary/terms_wow.csv")
+terms_wow = pd.read_csv("data/supplementary/terms_wow.csv")
 Markdown(tabulate(terms_wow.fillna(""), showindex=False, headers="keys", tablefmt="grid"))
 ```
 
@@ -706,7 +706,7 @@ World of work term cluster
 ::: {#appatbl-intervention-terms}
 
 ```{python}
-terms_policy = pd.read_csv("02-data/supplementary/terms_policy.csv")
+terms_policy = pd.read_csv("data/supplementary/terms_policy.csv")
 # different headers to include 'social norms'
 headers = ["General", "Institutional", "Structural", "Agency & social norms"]
 Markdown(tabulate(terms_policy.fillna(""), showindex=False, headers=headers, tablefmt="grid"))
@@ -719,7 +719,7 @@ Policy intervention term cluster
 ::: {#appatbl-inequality-terms}
 
 ```{python}
-terms_inequality = pd.read_csv("02-data/supplementary/terms_inequality.csv")
+terms_inequality = pd.read_csv("data/supplementary/terms_inequality.csv")
 Markdown(tabulate(terms_inequality.fillna(""), showindex=False, headers="keys", tablefmt="grid"))
 ```
 

documentation/findings-per-policy-area.md

@@ -1,6 +1,6 @@
 # Summary of study findings
 
-written into 02-data/supplementary/findings-*.csv tables
+written into data/supplementary/findings-*.csv tables
 
 ## Institutional
 

documentation/validity_tool.md

@@ -1,6 +1,6 @@
 # Validity estimators
 
-For a general concept description see ../03-documentation/terms_of_reference-key_terms.md#validity
+For a general concept description see ../documentation/terms_of_reference-key_terms.md#validity
 
 From Maitrot2017 -> Section 4, Figure 3 and Appendix table notes
 They rank *only* quasi-experimental/experimental

final_document/meeting_eoy.html

@@ -3757,7 +3757,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 });
 </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>
-<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="an">bibliography:</span><span class="co"> 02-data/intermediate/zotero-library.bib</span></span>
+<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>
 <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>
@@ -3788,7 +3788,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <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">&quot;whitegrid&quot;</span>)</span>
 <span id="cb1-34"><a href="#cb1-34" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb1-35"><a href="#cb1-35" aria-hidden="true" tabindex="-1"></a>DATA_DIR<span class="op">=</span>Path(<span class="st">&quot;./02-data&quot;</span>)</span>
+<span id="cb1-35"><a href="#cb1-35" aria-hidden="true" tabindex="-1"></a>DATA_DIR<span class="op">=</span>Path(<span class="st">&quot;./data&quot;</span>)</span>
 <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">&quot;raw&quot;</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">&quot;intermediate&quot;</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">&quot;processed&quot;</span>)</span>
@@ -3860,7 +3860,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <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">&quot;done::extracted&quot;</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">&quot;`&quot;</span> <span class="op">*</span> <span class="dv">3</span></span>
-<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 02-data/supplementary undeduplciated counts to get database starting and snowballing counts</span></span>
+<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>
 <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&quot;&quot;&quot;</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>

final_document/notes.html

@@ -5125,7 +5125,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 });
 </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="cb2" data-shortcodes="false"><pre class="sourceCode markdown code-with-copy"><code class="sourceCode markdown"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co">---</span></span>
-<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="an">bibliography:</span><span class="co"> 02-data/intermediate/zotero-library.bib</span></span>
+<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="an">bibliography:</span><span class="co"> data/intermediate/zotero-library.bib</span></span>
 <span id="cb2-3"><a href="#cb2-3" 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="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a><span class="an">papersize:</span><span class="co"> A4</span></span>
 <span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a><span class="an">linestretch:</span><span class="co"> 1.5</span></span>
@@ -5148,7 +5148,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb2-24"><a href="#cb2-24" aria-hidden="true" tabindex="-1"></a><span class="in">```{python}</span></span>
 <span id="cb2-25"><a href="#cb2-25" aria-hidden="true" tabindex="-1"></a><span class="co">#| echo: false</span></span>
 <span id="cb2-26"><a href="#cb2-26" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> pathlib <span class="im">import</span> Path</span>
-<span id="cb2-27"><a href="#cb2-27" aria-hidden="true" tabindex="-1"></a>DATA_DIR<span class="op">=</span>Path(<span class="st">&quot;./02-data&quot;</span>)</span>
+<span id="cb2-27"><a href="#cb2-27" aria-hidden="true" tabindex="-1"></a>DATA_DIR<span class="op">=</span>Path(<span class="st">&quot;./data&quot;</span>)</span>
 <span id="cb2-28"><a href="#cb2-28" aria-hidden="true" tabindex="-1"></a>RAW_DATA<span class="op">=</span>DATA_DIR.joinpath(<span class="st">&quot;raw&quot;</span>)</span>
 <span id="cb2-29"><a href="#cb2-29" aria-hidden="true" tabindex="-1"></a>WORKING_DATA<span class="op">=</span>DATA_DIR.joinpath(<span class="st">&quot;intermediate&quot;</span>)</span>
 <span id="cb2-30"><a href="#cb2-30" aria-hidden="true" tabindex="-1"></a>PROCESSED_DATA<span class="op">=</span>DATA_DIR.joinpath(<span class="st">&quot;processed&quot;</span>)</span>
@@ -5522,7 +5522,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb2-400"><a href="#cb2-400" aria-hidden="true" tabindex="-1"></a><span class="co">#| label: tbl-inclusion-criteria</span></span>
 <span id="cb2-401"><a href="#cb2-401" aria-hidden="true" tabindex="-1"></a><span class="co">#| tbl-cap: Study inclusion and exclusion scoping criteria {#tbl-inclusion-criteria}</span></span>
 <span id="cb2-402"><a href="#cb2-402" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb2-403"><a href="#cb2-403" aria-hidden="true" tabindex="-1"></a>inclusion_criteria <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/inclusion-criteria.tsv&quot;</span>, sep<span class="op">=</span><span class="st">&quot;</span><span class="ch">\t</span><span class="st">&quot;</span>)</span>
+<span id="cb2-403"><a href="#cb2-403" aria-hidden="true" tabindex="-1"></a>inclusion_criteria <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/inclusion-criteria.tsv&quot;</span>, sep<span class="op">=</span><span class="st">&quot;</span><span class="ch">\t</span><span class="st">&quot;</span>)</span>
 <span id="cb2-404"><a href="#cb2-404" aria-hidden="true" tabindex="-1"></a>md(tabulate(inclusion_criteria, showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span><span class="st">&quot;keys&quot;</span>, tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span>
 <span id="cb2-405"><a href="#cb2-405" aria-hidden="true" tabindex="-1"></a><span class="in">```</span></span>
 <span id="cb2-406"><a href="#cb2-406" aria-hidden="true" tabindex="-1"></a></span>

final_document/scoping_review.html

@@ -5378,7 +5378,7 @@ Table 1: ILO focus areas for inequality reduction
 <p>To identify potential studies and create an initial sample, relevant terms for the clusters of world of work, inequality and policy interventions have been extracted from the existing reviews as well as the ILO definitions. Identified terms comprising the world of work can be found in <a href="#tbl-wow-terms" class="quarto-xref">Table 2</a>, with the search query requiring a term from the general column and one other column.</p>
 <details class="code-fold">
 <summary>Code</summary>
-<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>terms_wow <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/terms_wow.csv&quot;</span>)</span>
+<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>terms_wow <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/terms_wow.csv&quot;</span>)</span>
 <span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a>md(tabulate(terms_wow.fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span><span class="st">&quot;keys&quot;</span>, tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div id="tbl-wow-terms" class="quarto-float anchored">
@@ -5483,7 +5483,7 @@ Table 2: World of work term cluster
 <p>For the policy intervention cluster, a variety of terms have been identified both from the ILO policy areas and guidelines as well as existing reviews, as can be seen in <a href="#tbl-intervention-terms" class="quarto-xref">Table 3</a>. Where terms have been identified from previous reviews outside the introduced ILO policy guidelines, there source has been included in the table. For the database query, a single term from the general category is required to be included in addition to one term from <em>any</em> of the remaining categories.</p>
 <details class="code-fold">
 <summary>Code</summary>
-<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>terms_policy <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/terms_policy.csv&quot;</span>)</span>
+<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>terms_policy <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/terms_policy.csv&quot;</span>)</span>
 <span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="co"># different headers to include &#39;social norms&#39;</span></span>
 <span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>headers <span class="op">=</span> [<span class="st">&quot;General&quot;</span>, <span class="st">&quot;Institutional&quot;</span>, <span class="st">&quot;Structural&quot;</span>, <span class="st">&quot;Agency &amp; social norms&quot;</span>]</span>
 <span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a>md(tabulate(terms_policy.fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span>headers, tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -5622,7 +5622,7 @@ Table 3: Policy intervention term cluster
 <div class="cell" data-execution_count="4">
 <details class="code-fold">
 <summary>Code</summary>
-<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>terms_inequality <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/terms_inequality.csv&quot;</span>)</span>
+<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>terms_inequality <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/terms_inequality.csv&quot;</span>)</span>
 <span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a>md(tabulate(terms_inequality.fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span><span class="st">&quot;keys&quot;</span>, tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div id="tbl-inequality-terms" class="cell quarto-float anchored" data-execution_count="4">
@@ -5759,7 +5759,7 @@ Table 4: Inequality term cluster
 <p>An overview of the respective criteria used for inclusion or exclusion can be found in <a href="#tbl-inclusion-criteria" class="quarto-xref">Table 5</a>. It restricts studies to those that comprise primary research published after 2000, with a focus on the narrowing criteria specified in <a href="#tbl-inclusion-criteria" class="quarto-xref">Table 5</a>.</p>
 <details class="code-fold">
 <summary>Code</summary>
-<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>inclusion_criteria <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/inclusion-criteria.tsv&quot;</span>, sep<span class="op">=</span><span class="st">&quot;</span><span class="ch">\t</span><span class="st">&quot;</span>)</span>
+<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>inclusion_criteria <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/inclusion-criteria.tsv&quot;</span>, sep<span class="op">=</span><span class="st">&quot;</span><span class="ch">\t</span><span class="st">&quot;</span>)</span>
 <span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a>md(tabulate(inclusion_criteria, showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span><span class="st">&quot;keys&quot;</span>, tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div id="tbl-inclusion-criteria" class="quarto-float anchored">
@@ -9294,7 +9294,7 @@ Figure 4: Available studies by primary type of intervention
 <span id="cb8-8"><a href="#cb8-8" aria-hidden="true" tabindex="-1"></a><span class="kw">def</span> strength_for(val):</span>
 <span id="cb8-9"><a href="#cb8-9" aria-hidden="true" tabindex="-1"></a>    <span class="cf">return</span> <span class="bu">list</span>(study_strength_bins.keys())[<span class="bu">list</span>(study_strength_bins.values()).index(val)]</span>
 <span id="cb8-10"><a href="#cb8-10" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb8-11"><a href="#cb8-11" aria-hidden="true" tabindex="-1"></a>findings_institutional <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/findings-institutional.csv&quot;</span>)</span>
+<span id="cb8-11"><a href="#cb8-11" aria-hidden="true" tabindex="-1"></a>findings_institutional <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/findings-institutional.csv&quot;</span>)</span>
 <span id="cb8-12"><a href="#cb8-12" aria-hidden="true" tabindex="-1"></a>fd_df <span class="op">=</span> validity.add_to_findings(findings_institutional, by_intervention, study_strength_bins)</span>
 <span id="cb8-13"><a href="#cb8-13" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb8-14"><a href="#cb8-14" aria-hidden="true" tabindex="-1"></a>md(tabulate(fd_df[[<span class="st">&quot;area of policy&quot;</span>,  <span class="st">&quot;internal_validity&quot;</span>, <span class="st">&quot;external_validity&quot;</span>, <span class="st">&quot;findings&quot;</span>, <span class="st">&quot;channels&quot;</span>]].fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span>[<span class="st">&quot;area of policy&quot;</span>, <span class="st">&quot;internal strength&quot;</span>, <span class="st">&quot;external strength&quot;</span>, <span class="st">&quot;main findings&quot;</span>, <span class="st">&quot;channels&quot;</span>], tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -9558,7 +9558,7 @@ Table 6: Summary of main findings for institutional policies
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb9"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> src.model <span class="im">import</span> validity</span>
 <span id="cb9-2"><a href="#cb9-2" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></a>findings_structural <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/findings-structural.csv&quot;</span>)</span>
+<span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></a>findings_structural <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/findings-structural.csv&quot;</span>)</span>
 <span id="cb9-4"><a href="#cb9-4" aria-hidden="true" tabindex="-1"></a>fd_df <span class="op">=</span> validity.add_to_findings(findings_structural, by_intervention, study_strength_bins)</span>
 <span id="cb9-5"><a href="#cb9-5" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb9-6"><a href="#cb9-6" aria-hidden="true" tabindex="-1"></a>md(tabulate(fd_df[[<span class="st">&quot;area of policy&quot;</span>,  <span class="st">&quot;internal_validity&quot;</span>, <span class="st">&quot;external_validity&quot;</span>, <span class="st">&quot;findings&quot;</span>, <span class="st">&quot;channels&quot;</span>]].fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span>[<span class="st">&quot;area of policy&quot;</span>, <span class="st">&quot;internal strength&quot;</span>, <span class="st">&quot;external strength&quot;</span>, <span class="st">&quot;main findings&quot;</span>, <span class="st">&quot;channels&quot;</span>], tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -9794,7 +9794,7 @@ Table 7: Summary of main findings for structural policies
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb10"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> src.model <span class="im">import</span> validity</span>
 <span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a>findings_agency <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/findings-agency.csv&quot;</span>)</span>
+<span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a>findings_agency <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/findings-agency.csv&quot;</span>)</span>
 <span id="cb10-4"><a href="#cb10-4" aria-hidden="true" tabindex="-1"></a>fd_df <span class="op">=</span> validity.add_to_findings(findings_agency, by_intervention, study_strength_bins)</span>
 <span id="cb10-5"><a href="#cb10-5" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb10-6"><a href="#cb10-6" aria-hidden="true" tabindex="-1"></a>md(tabulate(fd_df[[<span class="st">&quot;area of policy&quot;</span>,  <span class="st">&quot;internal_validity&quot;</span>, <span class="st">&quot;external_validity&quot;</span>, <span class="st">&quot;findings&quot;</span>, <span class="st">&quot;channels&quot;</span>]].fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span>[<span class="st">&quot;area of policy&quot;</span>, <span class="st">&quot;internal strength&quot;</span>, <span class="st">&quot;external strength&quot;</span>, <span class="st">&quot;main findings&quot;</span>, <span class="st">&quot;channels&quot;</span>], tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -22545,7 +22545,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb26-39"><a href="#cb26-39" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb26-40"><a href="#cb26-40" aria-hidden="true" tabindex="-1"></a>sns.set_style(<span class="st">&quot;whitegrid&quot;</span>)</span>
 <span id="cb26-41"><a href="#cb26-41" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb26-42"><a href="#cb26-42" aria-hidden="true" tabindex="-1"></a>DATA_DIR<span class="op">=</span>Path(<span class="st">&quot;./02-data&quot;</span>)</span>
+<span id="cb26-42"><a href="#cb26-42" aria-hidden="true" tabindex="-1"></a>DATA_DIR<span class="op">=</span>Path(<span class="st">&quot;./data&quot;</span>)</span>
 <span id="cb26-43"><a href="#cb26-43" aria-hidden="true" tabindex="-1"></a>RAW_DATA<span class="op">=</span>DATA_DIR.joinpath(<span class="st">&quot;raw&quot;</span>)</span>
 <span id="cb26-44"><a href="#cb26-44" aria-hidden="true" tabindex="-1"></a>WORKING_DATA<span class="op">=</span>DATA_DIR.joinpath(<span class="st">&quot;intermediate&quot;</span>)</span>
 <span id="cb26-45"><a href="#cb26-45" aria-hidden="true" tabindex="-1"></a>PROCESSED_DATA<span class="op">=</span>DATA_DIR.joinpath(<span class="st">&quot;processed&quot;</span>)</span>
@@ -22835,7 +22835,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb26-331"><a href="#cb26-331" aria-hidden="true" tabindex="-1"></a><span class="in">```{python}</span></span>
 <span id="cb26-332"><a href="#cb26-332" aria-hidden="true" tabindex="-1"></a><span class="co">#| label: tbl-wow-terms</span></span>
 <span id="cb26-333"><a href="#cb26-333" aria-hidden="true" tabindex="-1"></a><span class="co">#| tbl-cap: World of work term cluster</span></span>
-<span id="cb26-334"><a href="#cb26-334" aria-hidden="true" tabindex="-1"></a>terms_wow <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/terms_wow.csv&quot;</span>)</span>
+<span id="cb26-334"><a href="#cb26-334" aria-hidden="true" tabindex="-1"></a>terms_wow <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/terms_wow.csv&quot;</span>)</span>
 <span id="cb26-335"><a href="#cb26-335" aria-hidden="true" tabindex="-1"></a>md(tabulate(terms_wow.fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span><span class="st">&quot;keys&quot;</span>, tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span>
 <span id="cb26-336"><a href="#cb26-336" aria-hidden="true" tabindex="-1"></a><span class="in">```</span></span>
 <span id="cb26-337"><a href="#cb26-337" aria-hidden="true" tabindex="-1"></a></span>
@@ -22857,7 +22857,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb26-355"><a href="#cb26-355" aria-hidden="true" tabindex="-1"></a><span class="in">```{python}</span></span>
 <span id="cb26-356"><a href="#cb26-356" aria-hidden="true" tabindex="-1"></a><span class="co">#| label: tbl-intervention-terms</span></span>
 <span id="cb26-357"><a href="#cb26-357" aria-hidden="true" tabindex="-1"></a><span class="co">#| tbl-cap: Intervention term cluster</span></span>
-<span id="cb26-358"><a href="#cb26-358" aria-hidden="true" tabindex="-1"></a>terms_policy <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/terms_policy.csv&quot;</span>)</span>
+<span id="cb26-358"><a href="#cb26-358" aria-hidden="true" tabindex="-1"></a>terms_policy <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/terms_policy.csv&quot;</span>)</span>
 <span id="cb26-359"><a href="#cb26-359" aria-hidden="true" tabindex="-1"></a><span class="co"># different headers to include &#39;social norms&#39;</span></span>
 <span id="cb26-360"><a href="#cb26-360" aria-hidden="true" tabindex="-1"></a>headers <span class="op">=</span> [<span class="st">&quot;General&quot;</span>, <span class="st">&quot;Institutional&quot;</span>, <span class="st">&quot;Structural&quot;</span>, <span class="st">&quot;Agency &amp; social norms&quot;</span>]</span>
 <span id="cb26-361"><a href="#cb26-361" aria-hidden="true" tabindex="-1"></a>md(tabulate(terms_policy.fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span>headers, tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span>
@@ -22873,7 +22873,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb26-373"><a href="#cb26-373" aria-hidden="true" tabindex="-1"></a><span class="in">```{python}</span></span>
 <span id="cb26-374"><a href="#cb26-374" aria-hidden="true" tabindex="-1"></a><span class="co">#| label: tbl-inequality-terms</span></span>
 <span id="cb26-375"><a href="#cb26-375" aria-hidden="true" tabindex="-1"></a><span class="co">#| tbl-cap: Inequality term cluster</span></span>
-<span id="cb26-376"><a href="#cb26-376" aria-hidden="true" tabindex="-1"></a>terms_inequality <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/terms_inequality.csv&quot;</span>)</span>
+<span id="cb26-376"><a href="#cb26-376" aria-hidden="true" tabindex="-1"></a>terms_inequality <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/terms_inequality.csv&quot;</span>)</span>
 <span id="cb26-377"><a href="#cb26-377" aria-hidden="true" tabindex="-1"></a>md(tabulate(terms_inequality.fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span><span class="st">&quot;keys&quot;</span>, tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span>
 <span id="cb26-378"><a href="#cb26-378" aria-hidden="true" tabindex="-1"></a><span class="in">```</span></span>
 <span id="cb26-379"><a href="#cb26-379" aria-hidden="true" tabindex="-1"></a></span>
@@ -22897,7 +22897,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb26-399"><a href="#cb26-399" aria-hidden="true" tabindex="-1"></a><span class="in">```{python}</span></span>
 <span id="cb26-400"><a href="#cb26-400" aria-hidden="true" tabindex="-1"></a><span class="co">#| label: tbl-inclusion-criteria</span></span>
 <span id="cb26-401"><a href="#cb26-401" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb26-402"><a href="#cb26-402" aria-hidden="true" tabindex="-1"></a>inclusion_criteria <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/inclusion-criteria.tsv&quot;</span>, sep<span class="op">=</span><span class="st">&quot;</span><span class="ch">\t</span><span class="st">&quot;</span>)</span>
+<span id="cb26-402"><a href="#cb26-402" aria-hidden="true" tabindex="-1"></a>inclusion_criteria <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/inclusion-criteria.tsv&quot;</span>, sep<span class="op">=</span><span class="st">&quot;</span><span class="ch">\t</span><span class="st">&quot;</span>)</span>
 <span id="cb26-403"><a href="#cb26-403" aria-hidden="true" tabindex="-1"></a>md(tabulate(inclusion_criteria, showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span><span class="st">&quot;keys&quot;</span>, tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span>
 <span id="cb26-404"><a href="#cb26-404" aria-hidden="true" tabindex="-1"></a><span class="in">```</span></span>
 <span id="cb26-405"><a href="#cb26-405" aria-hidden="true" tabindex="-1"></a></span>
@@ -22948,7 +22948,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb26-452"><a href="#cb26-452" 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">&quot;done::extracted&quot;</span> <span class="kw">in</span> kw])</span>
 <span id="cb26-453"><a href="#cb26-453" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb26-454"><a href="#cb26-454" aria-hidden="true" tabindex="-1"></a>t3 <span class="op">=</span> <span class="st">&quot;`&quot;</span> <span class="op">*</span> <span class="dv">3</span></span>
-<span id="cb26-455"><a href="#cb26-455" aria-hidden="true" tabindex="-1"></a><span class="co"># </span><span class="al">FIXME</span><span class="co"> use 02-data/supplementary undeduplciated counts to get database starting and snowballing counts</span></span>
+<span id="cb26-455"><a href="#cb26-455" 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>
 <span id="cb26-456"><a href="#cb26-456" aria-hidden="true" tabindex="-1"></a><span class="co"># from: https://github.com/quarto-dev/quarto-cli/discussions/6508</span></span>
 <span id="cb26-457"><a href="#cb26-457" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="ss">f&quot;&quot;&quot;</span></span>
 <span id="cb26-458"><a href="#cb26-458" aria-hidden="true" tabindex="-1"></a><span class="ss">```</span><span class="sc">{</span>mermaid<span class="sc">}</span></span>
@@ -23145,7 +23145,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb26-659"><a href="#cb26-659" aria-hidden="true" tabindex="-1"></a><span class="kw">def</span> strength_for(val):</span>
 <span id="cb26-660"><a href="#cb26-660" aria-hidden="true" tabindex="-1"></a>    <span class="cf">return</span> <span class="bu">list</span>(study_strength_bins.keys())[<span class="bu">list</span>(study_strength_bins.values()).index(val)]</span>
 <span id="cb26-661"><a href="#cb26-661" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb26-662"><a href="#cb26-662" aria-hidden="true" tabindex="-1"></a>findings_institutional <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/findings-institutional.csv&quot;</span>)</span>
+<span id="cb26-662"><a href="#cb26-662" aria-hidden="true" tabindex="-1"></a>findings_institutional <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/findings-institutional.csv&quot;</span>)</span>
 <span id="cb26-663"><a href="#cb26-663" aria-hidden="true" tabindex="-1"></a>fd_df <span class="op">=</span> validity.add_to_findings(findings_institutional, by_intervention, study_strength_bins)</span>
 <span id="cb26-664"><a href="#cb26-664" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb26-665"><a href="#cb26-665" aria-hidden="true" tabindex="-1"></a>md(tabulate(fd_df[[<span class="st">&quot;area of policy&quot;</span>,  <span class="st">&quot;internal_validity&quot;</span>, <span class="st">&quot;external_validity&quot;</span>, <span class="st">&quot;findings&quot;</span>, <span class="st">&quot;channels&quot;</span>]].fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span>[<span class="st">&quot;area of policy&quot;</span>, <span class="st">&quot;internal strength&quot;</span>, <span class="st">&quot;external strength&quot;</span>, <span class="st">&quot;main findings&quot;</span>, <span class="st">&quot;channels&quot;</span>], tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span>
@@ -23378,7 +23378,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb26-894"><a href="#cb26-894" aria-hidden="true" tabindex="-1"></a><span class="co">#| label: tbl-findings-structural</span></span>
 <span id="cb26-895"><a href="#cb26-895" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> src.model <span class="im">import</span> validity</span>
 <span id="cb26-896"><a href="#cb26-896" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb26-897"><a href="#cb26-897" aria-hidden="true" tabindex="-1"></a>findings_structural <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/findings-structural.csv&quot;</span>)</span>
+<span id="cb26-897"><a href="#cb26-897" aria-hidden="true" tabindex="-1"></a>findings_structural <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/findings-structural.csv&quot;</span>)</span>
 <span id="cb26-898"><a href="#cb26-898" aria-hidden="true" tabindex="-1"></a>fd_df <span class="op">=</span> validity.add_to_findings(findings_structural, by_intervention, study_strength_bins)</span>
 <span id="cb26-899"><a href="#cb26-899" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb26-900"><a href="#cb26-900" aria-hidden="true" tabindex="-1"></a>md(tabulate(fd_df[[<span class="st">&quot;area of policy&quot;</span>,  <span class="st">&quot;internal_validity&quot;</span>, <span class="st">&quot;external_validity&quot;</span>, <span class="st">&quot;findings&quot;</span>, <span class="st">&quot;channels&quot;</span>]].fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span>[<span class="st">&quot;area of policy&quot;</span>, <span class="st">&quot;internal strength&quot;</span>, <span class="st">&quot;external strength&quot;</span>, <span class="st">&quot;main findings&quot;</span>, <span class="st">&quot;channels&quot;</span>], tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span>
@@ -23615,7 +23615,7 @@ window.document.addEventListener("DOMContentLoaded", function (event) {
 <span id="cb26-1133"><a href="#cb26-1133" aria-hidden="true" tabindex="-1"></a><span class="co">#| label: tbl-findings-agency</span></span>
 <span id="cb26-1134"><a href="#cb26-1134" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> src.model <span class="im">import</span> validity</span>
 <span id="cb26-1135"><a href="#cb26-1135" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb26-1136"><a href="#cb26-1136" aria-hidden="true" tabindex="-1"></a>findings_agency <span class="op">=</span> pd.read_csv(<span class="st">&quot;02-data/supplementary/findings-agency.csv&quot;</span>)</span>
+<span id="cb26-1136"><a href="#cb26-1136" aria-hidden="true" tabindex="-1"></a>findings_agency <span class="op">=</span> pd.read_csv(<span class="st">&quot;data/supplementary/findings-agency.csv&quot;</span>)</span>
 <span id="cb26-1137"><a href="#cb26-1137" aria-hidden="true" tabindex="-1"></a>fd_df <span class="op">=</span> validity.add_to_findings(findings_agency, by_intervention, study_strength_bins)</span>
 <span id="cb26-1138"><a href="#cb26-1138" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb26-1139"><a href="#cb26-1139" aria-hidden="true" tabindex="-1"></a>md(tabulate(fd_df[[<span class="st">&quot;area of policy&quot;</span>,  <span class="st">&quot;internal_validity&quot;</span>, <span class="st">&quot;external_validity&quot;</span>, <span class="st">&quot;findings&quot;</span>, <span class="st">&quot;channels&quot;</span>]].fillna(<span class="st">&quot;&quot;</span>), showindex<span class="op">=</span><span class="va">False</span>, headers<span class="op">=</span>[<span class="st">&quot;area of policy&quot;</span>, <span class="st">&quot;internal strength&quot;</span>, <span class="st">&quot;external strength&quot;</span>, <span class="st">&quot;main findings&quot;</span>, <span class="st">&quot;channels&quot;</span>], tablefmt<span class="op">=</span><span class="st">&quot;grid&quot;</span>))</span>

meeting_eoy.qmd

@@ -1,5 +1,5 @@
 ---
-bibliography: 02-data/intermediate/zotero-library.bib
+bibliography: data/intermediate/zotero-library.bib
 csl: /home/marty/documents/library/utilities/styles/APA-7.csl
 papersize: A4
 linestretch: 1.5
@@ -30,7 +30,7 @@ import bibtexparser
 
 sns.set_style("whitegrid")
 
-DATA_DIR=Path("./02-data")
+DATA_DIR=Path("./data")
 RAW_DATA=DATA_DIR.joinpath("raw")
 WORKING_DATA=DATA_DIR.joinpath("intermediate")
 PROCESSED_DATA=DATA_DIR.joinpath("processed")
@@ -102,7 +102,7 @@ nr_out_language = len([1 for kw in all_keywords if "out::language" in kw])
 nr_extraction_done = len([1 for kw in all_keywords if "done::extracted" in kw])
 
 t3 = "`" * 3
-# FIXME use 02-data/supplementary undeduplciated counts to get database starting and snowballing counts
+# FIXME use data/supplementary undeduplciated counts to get database starting and snowballing counts
 # from: https://github.com/quarto-dev/quarto-cli/discussions/6508
 print(f"""
 ```{{mermaid}}

notebooks/bibmanip.qmd

@@ -1,5 +1,5 @@
 ---
-bibliography: ../02-data/intermediate/zotero-library.bib
+bibliography: ../data/intermediate/zotero-library.bib
 csl: /home/marty/documents/library/utilities/styles/APA-7.csl
 papersize: A4
 linestretch: 1.5
@@ -22,7 +22,7 @@ subtitle: Addressing inequalities in the World of Work
 ```{python}
 #| echo: false
 from pathlib import Path
-data_dir=Path("../02-data")
+data_dir=Path("../data")
 
 ## standard imports
 from IPython.core.display import Markdown as md

notebooks/explore.qmd

@@ -1,5 +1,5 @@
 ---
-bibliography: 02-data/intermediate/zotero-library.bib
+bibliography: data/intermediate/zotero-library.bib
 title: Grab yml
 ---
 
@@ -187,7 +187,7 @@ import bibtexparser
 
 sns.set_style("whitegrid")
 
-DATA_DIR=Path("./02-data")
+DATA_DIR=Path("./data")
 RAW_DATA=DATA_DIR.joinpath("raw")
 WORKING_DATA=DATA_DIR.joinpath("intermediate")
 PROCESSED_DATA=DATA_DIR.joinpath("processed")

notebooks/main-findings.qmd

@@ -15,7 +15,7 @@ import bibtexparser
 
 sns.set_style("whitegrid")
 
-DATA_DIR=Path("./02-data")
+DATA_DIR=Path("./data")
 RAW_DATA=DATA_DIR.joinpath("raw")
 WORKING_DATA=DATA_DIR.joinpath("intermediate")
 PROCESSED_DATA=DATA_DIR.joinpath("processed")
@@ -120,7 +120,7 @@ datavis:
 
 
 ```{python}
-findings_institutional = pd.read_csv("02-data/supplementary/findings-institutional.csv")
+findings_institutional = pd.read_csv("data/supplementary/findings-institutional.csv")
 findings_institutional
 from src.model import validity
 import math

notebooks/rank_validities.qmd

@@ -16,7 +16,7 @@ import bibtexparser
 
 sns.set_style("whitegrid")
 
-DATA_DIR=Path("./02-data")
+DATA_DIR=Path("./data")
 RAW_DATA=DATA_DIR.joinpath("raw")
 WORKING_DATA=DATA_DIR.joinpath("intermediate")
 PROCESSED_DATA=DATA_DIR.joinpath("processed")

notebooks/test-magma.qmd

@@ -1,5 +1,5 @@
 ---
-bibliography: 02-data/intermediate/zotero-library.bib
+bibliography: data/intermediate/zotero-library.bib
 csl: /home/marty/documents/library/utilities/styles/APA-7.csl
 papersize: A4
 linestretch: 1.5
@@ -28,7 +28,7 @@ zotero:
 ```{python}
 #| echo: false
 from pathlib import Path
-DATA_DIR=Path("./02-data")
+DATA_DIR=Path("./data")
 BIB_PATH = DATA_DIR.joinpath("raw/01_wos-sample_2023-11-02")
 
 ## standard imports

notes.qmd

@@ -1,5 +1,5 @@
 ---
-bibliography: 02-data/intermediate/zotero-library.bib
+bibliography: data/intermediate/zotero-library.bib
 csl: /home/marty/documents/library/utilities/styles/APA-7.csl
 papersize: A4
 linestretch: 1.5
@@ -22,7 +22,7 @@ subtitle: Conceptual Definitions and Key Terms
 ```{python}
 #| echo: false
 from pathlib import Path
-DATA_DIR=Path("./02-data")
+DATA_DIR=Path("./data")
 RAW_DATA=DATA_DIR.joinpath("raw")
 WORKING_DATA=DATA_DIR.joinpath("intermediate")
 PROCESSED_DATA=DATA_DIR.joinpath("processed")
@@ -396,7 +396,7 @@ Policy *areas*, identified by @ILO2022b:
 #| label: tbl-inclusion-criteria
 #| tbl-cap: Study inclusion and exclusion scoping criteria {#tbl-inclusion-criteria}
 
-inclusion_criteria = pd.read_csv("02-data/supplementary/inclusion-criteria.tsv", sep="\t")
+inclusion_criteria = pd.read_csv("data/supplementary/inclusion-criteria.tsv", sep="\t")
 md(tabulate(inclusion_criteria, showindex=False, headers="keys", tablefmt="grid"))
 ```
 

pyproject.toml

@@ -43,19 +43,19 @@ cmd = "nvim"
 [tool.poe.tasks.extract]
 help = "Extract the csv data from raw yaml files"
 shell = """
-python src/extract/raw_to_extracted_csv.py > 02-data/processed/extracted.csv
+python src/extract/raw_to_extracted_csv.py > data/processed/extracted.csv
 """
 [tool.poe.tasks.prisma]
 help = "Update PRISMA flowchart numbers"
 shell = """
-python src/model/prisma.py > 02-data/processed/prisma.mmd
+python src/model/prisma.py > data/processed/prisma.mmd
 """
 [tool.poe.tasks.milestone]
 help = "Extract, render, commit and version a finished artifact"
 shell = """
 quarto render --output-dir 05-final_paper
 VERSION="$(poetry version -s minor)"
-git add pyproject.toml 02-data 05-final_paper
+git add pyproject.toml data 05-final_paper
 git commit -m "Publish version $VERSION" --no-gpg-sign
 git tag -a -m "new bundle for $(date -Isecond)" "$VERSION"
 """

scoping_review.qmd

@@ -303,7 +303,7 @@ with the search query requiring a term from the general column and one other col
 ```{python}
 #| label: tbl-wow-terms
 #| tbl-cap: World of work term cluster
-terms_wow = pd.read_csv("02-data/supplementary/terms_wow.csv")
+terms_wow = pd.read_csv("data/supplementary/terms_wow.csv")
 Markdown(tabulate(terms_wow.fillna(""), showindex=False, headers="keys", tablefmt="grid"))
 ```
 
@@ -319,7 +319,7 @@ For the database query, a single term from the general category is required to b
 ```{python}
 #| label: tbl-intervention-terms
 #| tbl-cap: Policy intervention term cluster
-terms_policy = pd.read_csv("02-data/supplementary/terms_policy.csv")
+terms_policy = pd.read_csv("data/supplementary/terms_policy.csv")
 # different headers to include 'social norms'
 headers = ["General", "Institutional", "Structural", "Agency & social norms"]
 Markdown(tabulate(terms_policy.fillna(""), showindex=False, headers=headers, tablefmt="grid"))
@@ -331,7 +331,7 @@ as seen in @tbl-inequality-terms.
 ```{python}
 #| label: tbl-inequality-terms
 #| tbl-cap: Inequality term cluster
-terms_inequality = pd.read_csv("02-data/supplementary/terms_inequality.csv")
+terms_inequality = pd.read_csv("data/supplementary/terms_inequality.csv")
 Markdown(tabulate(terms_inequality.fillna(""), showindex=False, headers="keys", tablefmt="grid"))
 ```
 
@@ -355,7 +355,7 @@ with a focus on the narrowing criteria specified in @tbl-inclusion-criteria.
 ```{python}
 #| label: inclusion-criteria
 
-inclusion_criteria = pd.read_csv("02-data/supplementary/inclusion-criteria.tsv", sep="\t")
+inclusion_criteria = pd.read_csv("data/supplementary/inclusion-criteria.tsv", sep="\t")
 Markdown(tabulate(inclusion_criteria, showindex=False, headers="keys", tablefmt="grid"))
 ```
 
@@ -382,7 +382,7 @@ The resulting process can be seen in @fig-prisma.
 ```{mermaid}
 %%| label: fig-prisma
 %%| fig-cap: PRISMA flowchart for scoping process
-%%| file: 02-data/processed/prisma.mmd
+%%| file: data/processed/prisma.mmd
 ```
 
 All relevant data concerning both their major findings and statistical significance are then extracted from the individual studies into a collective results matrix.
@@ -559,7 +559,7 @@ study_strength_bins = {
 def strength_for(val):
     return list(study_strength_bins.keys())[list(study_strength_bins.values()).index(val)]
 
-findings_institutional = pd.read_csv("02-data/supplementary/findings-institutional.csv")
+findings_institutional = pd.read_csv("data/supplementary/findings-institutional.csv")
 fd_df = validity.add_to_findings(findings_institutional, by_intervention, study_strength_bins)
 
 Markdown(tabulate(fd_df[["area of policy",  "internal_validity", "external_validity", "findings", "channels"]].fillna(""), showindex=False, headers=["area of policy", "internal strength", "external strength", "main findings", "channels"], tablefmt="grid"))
@@ -791,7 +791,7 @@ One limitation of the study is the modelling assumption that workers will have t
 #| label: tbl-findings-structural
 from src.model import validity
 
-findings_structural = pd.read_csv("02-data/supplementary/findings-structural.csv")
+findings_structural = pd.read_csv("data/supplementary/findings-structural.csv")
 fd_df = validity.add_to_findings(findings_structural, by_intervention, study_strength_bins)
 
 Markdown(tabulate(fd_df[["area of policy",  "internal_validity", "external_validity", "findings", "channels"]].fillna(""), showindex=False, headers=["area of policy", "internal strength", "external strength", "main findings", "channels"], tablefmt="grid"))
@@ -1028,7 +1028,7 @@ Though the intervention clearly aims at strengthening some aspect of individual
 #| label: tbl-findings-agency
 from src.model import validity
 
-findings_agency = pd.read_csv("02-data/supplementary/findings-agency.csv")
+findings_agency = pd.read_csv("data/supplementary/findings-agency.csv")
 fd_df = validity.add_to_findings(findings_agency, by_intervention, study_strength_bins)
 
 Markdown(tabulate(fd_df[["area of policy",  "internal_validity", "external_validity", "findings", "channels"]].fillna(""), showindex=False, headers=["area of policy", "internal strength", "external strength", "main findings", "channels"], tablefmt="grid"))

src/extract/load_data.py

@@ -9,7 +9,7 @@ try:
 except ModuleNotFoundError:
     import yml as yaml  # for directly running the package
 
-DEFAULT_YAML_PATH = Path("02-data/processed")
+DEFAULT_YAML_PATH = Path("data/processed")
 
 
 def to_tsv(studies: list[dict]) -> str:

src/globals.py

@@ -3,7 +3,7 @@ import os
 
 PROJECT_DIR=Path(os.getenv("QUARTO_PROJECT_DIR", "."))
 
-DATA_DIR=PROJECT_DIR.joinpath("02-data")
+DATA_DIR=PROJECT_DIR.joinpath("data")
 
 RAW_DATA=DATA_DIR.joinpath("raw")
 WORKING_DATA=DATA_DIR.joinpath("intermediate")

src/model/prisma.py

@@ -33,7 +33,7 @@ del bib_sample, bib_sample_raw_db
 if __name__ == "__main__":
     nr = PrismaNumbers()
 
-    # FIXME use 02-data/supplementary undeduplciated counts to get database starting and snowballing counts
+    # FIXME use data/supplementary undeduplciated counts to get database starting and snowballing counts
     outp = f"""
     flowchart TD;
         search_db["Records identified through database searching (n={nr.nr_database_query_raw})"] --> starting_sample;