chore(script): Add table captions
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@ -318,6 +318,7 @@ with the search query requiring a term from the general column and one other col
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```{python}
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#| label: tbl-wow-terms
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#| tbl-cap: World of work term cluster
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terms_wow = pd.read_csv("02-data/supplementary/terms_wow.csv")
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md(tabulate(terms_wow.fillna(""), showindex=False, headers="keys", tablefmt="grid"))
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```
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@ -339,6 +340,7 @@ For the database query, a single term from the general category is required to b
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```{python}
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#| label: tbl-intervention-terms
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#| tbl-cap: Intervention term cluster
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terms_policy = pd.read_csv("02-data/supplementary/terms_policy.csv")
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# different headers to include 'social norms'
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headers = ["General", "Institutional", "Structural", "Agency & social norms"]
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@ -1735,12 +1737,12 @@ print(f"""
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## Validity rankings {#sec-appendix-validity-rankings}
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| Representativeness | Ranking |
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| --- | --- |
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| non-representative survey | 2.0 |
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| subnationally representative survey | 3.0 |
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| nationally representative survey | 4.0 |
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| census-based dataset | 5.0 |
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| Representativeness | Ranking |
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| --- | --- |
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| non-representative survey/dataset | 2.0 |
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| subnationally representative survey/dataset | 3.0 |
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| nationally representative survey/dataset | 4.0 |
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| census-based dataset | 5.0 |
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: External validity ranking. Adapted from @Maitrot2017.
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@ -1756,4 +1758,12 @@ print(f"""
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: Internal validity ranking. Adapted from @Maitrot2017.
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## Extraction matrix
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```{python}
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#| label: tbl-extraction-matrix
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#| tbl-cap: Extraction matrix
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bib_df
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```
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{{< pagebreak >}}
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