Impact of High Seas Closure on Food Security in Low Income Fish Dependent Countries
Bibliographic record
Abstract
We investigate how high seas closure will affect the availability of commonly consumed food fish in 46 fish reliant, and/or low income countries. Domestic consumption of straddling fish species (fish that would be affected by high seas closure) occurred in 54% of the assessed countries. The majority (70%) of countries were projected to experience net catch gains following high seas closure. However, countries with projected catch gains and that also consumed the straddling fish species domestically made up only 37% of the assessed countries. In contrast, much fewer countries (25%) were projected to incur net losses from high seas closure, and of these, straddling species were used domestically in less than half (45%) of the countries. Our findings suggest that, given the current consumption patterns of straddling species, high seas closure may only directly benefit the supply of domestically consumed food fish in a small number of fish reliant and/or low income countries. In particular, it may not have a substantial impact on improving domestic fish supply in countries with the greatest need for improved access to affordable fish, as only one third of this group used straddling fish species domestically. Also, food security in countries with projected net catch gains but where straddling fish species are not consumed domestically may still benefit indirectly via economic activities arising from the increased availability of non-domestically consumed straddling fish species following high seas closure. Consequently, this study suggests that high seas closure can potentially improve marine resource sustainability as well as contribute to human well-being in some of the poorest and most fish dependent countries worldwide. However, caution is required because high seas closure may also negatively affect fish availability in countries that are already impoverished and fish insecure.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".