Data · dataset · 2023
G²LM|LIC - The Effects of Employer Responses to COVID-19 on Female Garment Workers in Bangladesh
Listed in IDSC Dataverse
This study developed and implemented a mobile-phone-based survey of garment workers in Bangladesh, providing insights about COVID-19 responses in their workplace and the effects on workers.
Description
The study asked about factory shutdowns, the rate of safety measures like masks and increased distance between workspaces, late payment and earnings, working conditions, time out of the labor force, beliefs and aspirations, and physical and mental health, both during the pandemic and retrospectively in January 2020.
Because of the possibility that the pandemic caused separations (either voluntary or involuntary) from the garment sector, the project defined a garment worker as someone who was working in the garment industry in January 2020, even if they were no longer doing so at the time of the survey. For those workers no longer in the industry, the survey also asked about their reasons for separation and any alternate economic activity they were engaged in.
Links
Where it is published
- Dataverse dataset page dataverse.iza.org/dataset.xhtml?persistentId=doi%3A10.15185%2Fglmlic.710.1 ↗
landing page · from dataverse iza org
- DOI doi.org/10.15185/glmlic.710.1 ↗
DOI / persistent id · from dataverse iza org
Catalogue records · 1
- Dataverse API dataverse.iza.org/api/datasets/:persistentId/?persistentId=doi%3A10.15185%2Fglml… ↗
metadata API · from dataverse iza org
Topics
- Stated by source
- Social Sciences
- From keywords
- Economics & Finance · Medicine & Health · Social Science
- Inferred from text
- Epidemiology 72%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| IDSC Dataverse | doi:10.15185/glmlic.710.1 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4202 | enrichment · dataverse iza org | taxonomy-embedding@1.0.0 | title+keywords+description (72%) |
| concepts[field].dataverse_subject:social-sciences | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /subjects |
| created_date | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | |
| description | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /description |
| publication_date | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | |
| title | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | /name |
| updated_date | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 | |
| version_label | source · dataverse iza org | connector:dataverse_iza_org@1.0.0 |