COVID-19 Crisis and the Informal Economy: Informal Workers in Dar es Salaam, Tanzania
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
COVID-19 Crisis and the Informal Economy is a WIEGO-led 12-city longitudinal study that assesses the impact of the COVID-19 crisis on specific groups of informal workers and their households. Using a survey questionnaire and in-depth interviews, Round 1 assessed the impact of the crisis in April 2020 (the period of peak restrictions in most cities) and in July 2020 (when the survey was conducted and restrictions had been eased in most cities)1 in comparison to February 2021 (pre-COVID-19). Round 2 will assess continuing impacts versus signs of recovery in the first half of 2021, compared to the pre-COVID-19 period and Round 1. This report presents the summary findings of Round 1 of the study in Dar es Salaam, Tanzania. Researchers in Dar es Salaam surveyed 283 domestic workers who are members of the Conservation, Hotels, Domestic, Social Services and Consultancy Workers Union (CHODAWU), the local partner organization of informal workers. They also interviewed two informal worker leaders and two key informants from membership-based organizations. \n \nThe research provides a demographic profile of this workforce and documents their working conditions and the impacts of COVID-19. While Tanzania did not enforce a generalized or strict lockdown, research suggests that domestic workers’ conditions—already precarious—deteriorated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it