Fishing through the cracks: The unregulated nature of global squid fisheries
Bibliographic record
Abstract
While most research has focused on the legality of global industrial fishing, unregulated fishing has largely escaped scrutiny. Here, we evaluate the unregulated nature of global squid fisheries using AIS data and nighttime imagery of the globalized fleet of light-luring squid vessels. We find that this fishery is extensive, fishing 149,000 to 251,000 vessel days annually, and that effort increased 68% over the study period 2017-2020. Most vessels are highly mobile and fish in multiple regions, largely (86%) in unregulated areas. While scientists and policymakers express concerns over the declining abundance of squid stocks globally and regionally, we find a net increase in vessels fishing squid globally and spatial expansion of effort to novel areas. Since fishing effort is static in areas with increasing management, and rising in unmanaged areas, we suggest actors may take advantage of fragmented regulations to maximize resource extraction. Our findings highlight a profitable, but largely unregulated fishery, with strong potential for improved management.
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 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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".