Bibliographic record
Abstract
Climate change and food security are among the world’s biggest challenges. A growing population and climate change means that vulnerable regions such as the Caribbean, will continue to face unique strains. The effects of climate change are associated with poverty and a decrease in food security because of the decline in food production and access to a sufficient amount of nutritious food. Trade liberalization increases the number of challenges experienced by notably, the local Caribbean agricultural sector and has devastating effects on food security and rural livelihoods. Reductions in crop diversity and production mixed with low household incomes results in changed diets. These changes have increased the prevalence of non-communicable diseases (NCDs) such as diabetes and hypertension as well as obesity and other long-term health problems. Current and proposed strategies to aid with the challenges of climate change include further research on the creation of heat tolerant cattle breeds, technological developments, micro-insurance interventions, and the expansion of greenhouse farming. The traditional and acquired knowledge and skills of individuals in the agricultural sector is fundamental in creating strategies to adapt to the impacts of climate change and it is essential to ensure the strengthening of food security and food sovereignty. Financial resources in the Caribbean are inadequate and therefore, it is imperative that the Global North pay their dues in shouldering the responsibility of reducing the economic and environmental vulnerabilities in the Caribbean.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".