Kenyan Baseline Report: Covid-19 and The Youth Question in Africa: Response, Impacts and Prevention Measures in the IGAD Region
Bibliographic record
Abstract
Organisation for Social Science Research in Eastern and Southern Africa (OSSREA) in collaboration with CEWARN-IGAD, Makerere University (Uganda), OSSREA Kenya Chapter and CCRDA (Ethiopia) were funded by IDRC-Canada to conduct a study entitled: COVID-19 and the Youth Question in Africa: Response, Impact and Prevention Measures in the IGAD Region. The study was conducted in three IGAD member states, namely Ethiopia, Kenya and Uganda This survey report presents the Kenyan study conducted by OSSREA Kenyan Chapter. It addressed the youth question, focusing on how they were mobilized to participate in COVID 19 response; their capacity to participate; nature and involvement level they were engaged in; policy engagement and knowledge sharing; and accountability in COVID 19 response. UNHCR recommends that one tactic to combat the spread of the virus in vulnerable communities must be to engage local youth and youth networks. This survey re-emphasizes the value government, CBOs, FBOs, CSOs and any Youth Organizations may gain by tapping into youth creativity and innovation. This survey has revealed non engagement of youth participation in COVID 19 response.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".