chore(notes): Update tables and term lists
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notes.md
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notes.md
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@ -375,7 +375,8 @@ Policy *areas*, identified by @ILO2022b:
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| --- | --- | --- |
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| Language | study written in English | study not written in English |
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| Time frame | study published in or after 2000 | study published before 2000 |
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| Study type | primary research, literature review | opinion piece, editorial, commentary, news article |
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| Study type | primary research | opinion piece, editorial, commentary, news article, literature review |
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| | most recent publication of study | gray literature superseded by white literature publication |
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| Study focus | inequality or labour market outcomes as primary outcome (dependent variable) | neither inequality nor labour market outcomes as dependent variable |
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| | policy measure or strategy as primary intervention (independent variable) | no policy measure/strategy as intervention or relationship unclear |
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| | specifically relates to some dimension of world of work | exists outside world of work for both independent and dependent variables |
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@ -412,16 +413,17 @@ Tagging:
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| url/doi | |
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| ?discipline? | The overall discipline the study falls under |
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| Context info | Description |
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| --- | --- |
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| country | What is the primary/are the primary country/countries under analysis in the study? (set:txt) |
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| country_world_region | Which ILO region does the country belong to? (set:txt) |
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| country_income_class | Which UN Bank income category does the country belong to? (set:txt) |
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| period_of_analysis | What is the main period of analysis for the study (in years, e.g. 2010-2012)? (timedelta) |
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| length_of_study | What is the main length of observation for the study, if mentioned (in months, e.g. 14 months)? (timedelta) |
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| explicit_targeting | is intervention specifically (explicitly) targeted at population/group? (bool:0/1) |
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| target_group | who is the intervention targeted at (explicitly/implicitly)? (list:txt) |
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| data | What dataset/database/collection does the data stem from, if mentioned? (list:txt) |
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| Context info | Description |
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| --- | --- |
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| country | What is the primary/are the primary country/countries under analysis in the study? (set:txt) |
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| country_world_region | Which ILO region does the country belong to? (set:txt) |
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| country_income_class | Which UN Bank income category does the country belong to? (set:txt) |
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| period_of_analysis | What is the main period of analysis for the study (in years, e.g. 2010-2012)? (timedelta) |
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| observation_length | What is the main length of observation for the study, if mentioned (in months)? (timedelta) |
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| observation_length_max | What is the max length of observation for the study, if it diverges from the average length (in months)? (timedelta) |
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| explicit_targeting | is intervention specifically (explicitly) targeted at population/group? (bool:0/1) |
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| target_group | who is the intervention targeted at (explicitly/implicitly)? (list:txt) |
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| data | What dataset/database/collection does the data stem from, if mentioned? (list:txt) |
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| Results info | Description |
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| --- | --- |
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@ -448,6 +450,7 @@ Tagging:
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| significance | What is the main level of statistical significance? (2: significant, 1: marginally significant, 0: non significant) |
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- annotation, quick 100-300wd written summary of major properties found above for each study
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-> ~34 observations per study
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## Search Term clusters
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@ -478,35 +481,7 @@ Tagging:
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- formality
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- (unpaid) care work
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### inequality cluster
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- ILO:
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- inequality/-ies
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- barrier(s)
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- (dis)advantaged
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- discriminated
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- disparity/-ies
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- horizontal / vertical inequality
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### vertical inequalities cluster
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- ILO/UN [@DFI2023]
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- income:
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- Palma ratio
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- Gini coefficient
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### horizontal inequalities cluster
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- ILO:
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- visible identity
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- demographic inequalities
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- gender, colour or beliefs
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- racial, ethnic inequalities
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- migrants and nationals
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- spatial inequalities (rural/urban/large mega-cities/small/peripheral cities)
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- gender, age, nationality, ethnicity, health status, disability, characteristics
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### outcome cluster
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### LM outcome cluster
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- ILO:
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- employment outcomes
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@ -526,16 +501,16 @@ Tagging:
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- labour force exit
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- retrurning to work issues
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### policy cluster
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### intervention cluster
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- general terms:
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- intervention (@ILO2022b)
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- policy (@ILO2022b)
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- participation (@ILO2022b)
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- targeting/targeted (@ILO2022b)
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- distributive (@ILO2022b)
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- equitable income dist (@ILO2022b)
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- redistributive (@ILO2022b)
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- regulatory (@ILO2022b)
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### policy cluster
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- institutional promotion:
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- institutional support for childcare (@Perez2022)
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@ -584,6 +559,53 @@ Tagging:
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- work organization (@Nevala2015)
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- special transportation (@Nevala2015)
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### inequality cluster
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- ILO:
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- inequality/-ies
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- barrier(s)
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- (dis)advantaged
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- discriminated
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- disparity/-ies
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- horizontal / vertical inequality
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### vertical inequalities cluster
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- income:
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- Palma ratio [@DFI2023]
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- Gini coefficient [@DFI2023]
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- class @Kalasa2021
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- fertility @Kalasa2021
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- NOT identified by previous reviews, need to find sources:
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- bottom percentile
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- top percentile
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### horizontal inequalities cluster
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identified by ILO:
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- identity
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- demographic inequalities
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- demographic markers
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- gender
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- colour
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- beliefs
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- racial
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- ethnic
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- migrant
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- spatial
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- rural
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- urban
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- mega-cities
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- small cities
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- peripheral cities
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- age
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- nationality
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- ethnicity
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- health status
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- disability
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- characteristics
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# Notes on previous reviews
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## Perez2022
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