Welfare Employment and Its Impact on the Agricultural Sector Workforce in Trinidad, West Indies
Bibliographic record
Abstract
The agricultural sector in Trinidad and Tobago is characterized by a labor shortage. A qualitative research design was used to investigate the impact of a national welfare employment program, on the agriculture labor sector. The study recruited n = 19 Community-Based Environmental Protection and Enhancement Program (CEPEP) employees, n = 10 farmers and n = 7 agricultural professionals for in-depth interviews and focus group sessions. A review was conducted of newspaper articles and national budget statements for content related to CEPEP and agriculture. A thematic analysis was conducted to establish themes from the data gathered from the participants and from the media review. The themes emerged were “CEPEP’s benefits to agriculture”, “Labor shortages in Agriculture”, “Convenience Employment” and “Challenges to CEPEP in Agriculture”. The study concludes that welfare employment can be incorporated into the development agenda for agriculture in Trinidad and Tobago once the issues of capacity building, retooling and mentorship, wage adjustments are factored into a structured program.
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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 | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".