wow-inequalities/docs/meeting_2024-02-09.md

48 lines
2.6 KiB
Markdown
Raw Permalink Normal View History

# Meeting Miguel 2024-02-09
achieved:
2024-02-09 15:53:50 +00:00
- [ ] remaining study batch screened
- added active labour market policy studies
- starting to wrangle synthesis:
- better categorization for some and did dual categorizations, e.g. job search assistance or subsidized employment/wages partly into ALMP
- Moved away again a little from strict framework adherence to make more sense for the synthesis -> workfware programmes
- [ ] focus now:
2024-02-09 15:53:50 +00:00
- table reviewing main findings
- screen the remaining 200 studies
- improve the writing on the synthesis itself
- to adhere a little closer to
- [ ] questions:
- logistical:
- create extraction matrices with main/statistical findings
- are we going to put those in the main Appendix?
or do we just pass on the CSV extraction as the data?
- is there a specific length I am going for for the end result?
- is it fine if for now I leave intro/conclusion more vague to fit in with rest of the document
- writing:
- categories overlap sometimes, of course
- a study on NREGS in India which has minimum wage effects as primary channel
- a study on vocational training which fuses it with workfare program (ALMP)
2024-02-09 15:53:50 +00:00
- I would put the focus on 'per-area' conclusions, not the 'per-study'
- validity visualizations
- built a simple scoring rubric of 0-not fulfilled, 1-implicitly fulfilled, 2-explicitly fulfilled
- internal: (design + method) - (selection bias + measurement bias + confounding bias + performance bias)
- external: (representativeness) - (generalizability concerns + population invalidity + ecological invalidity)
- internal:
- design (observational/qualitative, correlational, causal(quasi-experimental/experimental))
- confounding variable control (no mention, limits mentioned, limits mentioned and explicitly discussed)
- data collection (not mentioned, sources mentioned, sources/sample size/observation-length given)
- statistical control (no robustness checks, data robustness mentioned, explicit robustness checks)
- biases (no mention, possible biases mentioned, explicitly controlled for/influcence explained)
- external:
- generalizability (no mention, implicitly generalizable, explicitly generalizable)
- representativeness of sample (no mention/sub-national, national, regional/global)
- ecological validity (no mention, implicit policy implication, explicit policy implication)
- [ ] TODO
- main findings table still remaining
- write it out
- shorten?