“Are We All in This Together?”: The Socioeconomic Impacts and Inequalities of the COVID-19 Pandemic in Ghana’s Informal Economy
Bibliographic record
Abstract
This paper examines the challenges posed by the COVID-19 pandemic on the existing health inequalities disproportionately affecting vulnerable populations. It explores the impact of COVID-19 pandemic response measures to “curb the spread” on informal sector workers in Ghana. In Ghana, like many other developing countries, the informal sector was impacted by a higher risk of exposure to the COVID-19 infection and the slew of pandemic response measures, for example, lockdowns and stay-at-home orders, as well as guidelines around social distancing implemented by their governments. Given the high level of precarity that undergirds work in the informal sector and the intersectional forces that contribute to and maintain their marginality—class, race, ethnicity, gender, religion, and geographic location—this paper creates a space for dialogue about the unintended consequences of pandemic response measures on the livelihood security of informal sector workers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".