Can the Caribbean localize its food system?: Evidence from biomass flow accounting
Bibliographic record
Abstract
Abstract Small island economies are highly dependent on food imports. Self‐sufficiency through food localization is therefore often advocated. Can a small Caribbean island nation localize its food system? To answer this question, we conducted socio‐metabolic research on four Caribbean nations: Barbados, Dominica, Grenada, and Jamaica. Derived indicators from a diachronic biomass flow accounting from 1961 to 2019 suggest a declining trend in local food production for all cases. While in Barbados and Jamaica this decline already began in the 1960s, for Dominica and Grenada, this did not start until the late 1970s–1980s. The physical trade balance of biomass is similar across all cases: from net exporters at the start of the study period to net importers as countries developed, albeit at different time periods. By disaggregating biomass flow data to crop level, Barbados and Jamaica indicate a trend that is moving away from food localization, while Dominica and Grenada appear to be modestly moving toward localization in recent years. Given the many resource security challenges small island economies face, this study provides a biophysical perspective to the Caribbean's food security debate and questions the extent to which food localization is possible in a small island context, and whether other strategies are urgently needed.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".