Asymmetry across international borders: Research, fishery and management trends and economic value of the giant sea bass (<i>Stereolepis gigas</i>)
Bibliographic record
Abstract
Abstract Co‐operation in the management of shared fish stocks is often necessary to achieve sustainability and reduce uncertainty. The United States of America (USA) and Mexico share a number of fish stocks and marine ecosystems, while there is some binational co‐operation in scientific research, unilateral management decisions are generally the rule. We present a case study using the giant sea bass ( Stereolepis gigas , Polyprionidae) to highlight how these management and research asymmetries can skew national perceptions of population status for a fully transboundary species. Scientific publications and annual funding related to giant sea bass are 7x and 25x higher in the USA, respectively, despite the fact that 73% of the species’ range occurs in Mexico. Conversely, annual fishery production and consumptive value of giant sea bass in Mexico are 19x and 3.5x higher than in the USA, respectively, while the non‐consumptive value related to dive ecotourism is 76x higher in the USA. These asymmetries have generated a distorted view of the population status of the giant sea bass across its entire range. This and other factors related to historical fishery dynamics and policy must be accounted for when assessing population status, and subsequent appropriate management responses, across geopolitical boundaries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".