Global Fisheries Science Documents Human Impacts on Oceans: The <i>Sea Around Us</i> Serves Civil Society in the Twenty-First Century
Bibliographic record
Abstract
Fishing provides the world with an important component of its food supply, but it also negatively impacts the biodiversity of marine and freshwater ecosystems, especially when industrial fishing is involved. To mitigate these impacts, civil society needs access to fisheries data (i.e., catches and catch-derived indicators of these impacts). Such data, however, must be more comprehensive than the official fisheries statistics supplied to the Food and Agriculture Organization of the United Nations (FAO) by its member countries, which shape public policy in spite of their deficiencies, notably underestimating small-scale fisheries. This article documents the creation, based on the geographically coarse FAO data, of a database and website ( https://www.seaaroundus.org ) that provides free reconstructed (i.e., corrected) catch data by ecosystem, country, species, gear type, commercial value, etc., to any interested person, along with catch-derived indicators from 1950 to the near present for the entire world.
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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.009 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; both teacher heads agree on what is shown here.
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".