A Review of the Civil Society Role in Exposing COVID-19 Corruption in Zimbabwe
Bibliographic record
Abstract
The paper examines the role of civil society in Exposing COVID-19 corruption in Zimbabwe. The essence is in the possibility of learning how civil society can adequately act as a watchdog against corrupt practices in the management of COVID-19 in Zimbabwe. As such, the paper presents documentary reviews and analyses of the connection between civil society and COVID-19-induced corruption. Using reviews of various literature, this paper analyses the role of civil society in challenging COVID-19 linked corruption in Zimbabwe since the advent of the pandemic in the country. The paper concludes that civil society was critical in exposing corrupt practices within government and the Health Ministry in particular. Principal among these cases was the Drax Scandal, the Jaji Scandal and the private hospital's scandal. However, the extent of success varies with the type of corruption exposed and challenged. Relatedly, the endemic corruption problems in Zimbabwe explain why some civil societies aren't simply proactive in exposing corrupt officeholders both in public and private health sectors via a nationwide campaign.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".