The best catch data that can possibly be? Rejoinder to Ye et al. “FAO's statistic data and sustainability of fisheries and aquaculture”
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Here we reply to a commentary by Ye et al. (Mar. Policy 2017; Ye et al.) on our article (Pauly and Zeller, 2017 [2]) commenting on FAO's interpretation of current fisheries trends in SOFIA 2016 (The State of World Fisheries and Aquaculture). We show how arguments such as FAO's catch statistics being "the best they can possibly be", and other manifestations of FAO's difficulties in constructively engaging with comments compromises FAO's stated goal to engage with academia and civil society. This is particularly serious in an age where the value of an open scientific discourse is increasingly under threat, as is the food security of many poor countries in which fish supplied by domestic fisheries constitutes a strong component of local diets.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.016 |
| 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 it