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feat(notes): Update inclusion criteria and query

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Marty Oehme 2023-11-02 22:46:25 +01:00
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@ -371,16 +371,16 @@ Policy *areas*, identified by @ILO2022b:
## Inclusion criteria
| Parameter | Inclusion criteria | Exclusion criteria |
| --- | --- | --- |
| Language | study written in English | study not written in English |
| Time frame | study published in or after 2000 | study published before 2000 |
| Study type | primary research | opinion piece, editorial, commentary, news article, literature review |
| | most recent publication of study | gray literature superseded by white literature publication |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 |
| | 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 |
| Parameter | Inclusion criteria | Exclusion criteria |
| --- | --- | --- |
| Language | study written in English | study not written in English |
| Time frame | study published in or after 2000 | study published before 2000 |
| Study type | primary research | opinion piece, editorial, commentary, news article, literature review |
| | most recent publication of study | gray literature superseded by white literature publication |
| Study focus | inequalities/ inequalities in labour market outcomes as primary outcome (dependent variable) | neither inequality nor labour market 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 |
: Study inclusion and exclusion scoping criteria {#tbl-inclusion-criteria}
@ -948,16 +948,16 @@ TS=
disparity OR
disparities
)
AND
NEAR/5
(
(
income OR
Palma ratio OR
Gini coefficient OR
"Palma ratio" OR
"Gini coefficient" OR
class OR
fertility OR
bottom percentile OR
top percentile
"bottom percentile" OR
"top percentile"
)
OR
(
@ -973,12 +973,12 @@ TS=
rural OR
urban OR
mega-cities OR
small cities OR
peripheral cities OR
"small cities" OR
"peripheral cities" OR
age OR
nationality OR
ethnicity OR
health status OR
"health status" OR
disability OR
characteristics
)
@ -986,6 +986,45 @@ TS=
)
```
# Findings and Updates from query
## Preliminary source pool
- initial query pool (no deduplication): 1643
- snowballing pool (from 29 reviews): 530
## Additional concept research
- utilizing Joanna Briggs Institute JBI Scoping Review methodology
## Preliminary findings income
- potential drivers: (Zhuan2023)
- inverted-U hypothesis (Kuznets, 1955)/ dual economy model (Lewis, 1954)
- technological progress
- globalization
- deregulation/market-oriented reform
- financialization
- population aging
- widening spatial inequality between subsistence/growth economy (i.e. dual economy)
- growing gap to super-rich (top 1 percentile)
- potential channels:
- declining labor income share/ growing capital income share
- widening skilled/non-skilled wage differentials
- growing spatial inequality
- limited taxation/transfer income redistribution
## Potential additional search terms
- Matthew effect (lower socio-economic position households send fewer children to formal childcare in HIC)
- issue: currently in many cases looking at *health* and *health inequality* outcomes
## Issues raised by ILO
- only english: Query itself is English only. If Spanish/French fall into grid, may include
- no purely qualitative: might prove too much; how to ensure rigour?
- no pre-2000: Can include?
\pagebreak
# Relevant references