Community engagement in rural and urban marginalized communities in Jamaica: Building community resilience in crisis
Bibliographic record
Abstract
In the Caribbean, Jamaica mobilized strategies to ensure that the most vulnerable were protected against the threats and fears of COVID-19 and other crises over time. One strategy involved wide-scale collaboration with public and private sectors, non-governmental and community-based organizations, and volunteers. This study describes the approach taken by stakeholders in response to the needs of vulnerable residents in marginalized communities, and to highlight the experiences building community resilience during COVID-19. Three questions guided the research: 1) What major issues that affected the community during the COVID-19 crisis? 2) What measures have been implemented to help communities manage and adapt coping mechanism during this crisis? and 3) How has the community shown resilience and recovery in mitigating crises? A descriptive research design was employed comprising focus groups and interviews. We sampled 28 participants from 7 non-governmental organizations and 12 communities in rural and urban Jamaica. The analysis generated policy recommendations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".