Filling a blank on the map: 60 years of fisheries in Equatorial Guinea
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
Abstract Despite a scarcity of pertinent information, it has been possible to reconstruct time series of marine fisheries catches for Equatorial Guinea from 1950 to 2010 using per capita fish consumption and population numbers for small‐scale fisheries, catch rates and number of vessels for industrial fisheries and discard rates to estimate the discarded bycatch. Small‐scale fisheries, industrial large‐scale fisheries, domestic and legal and illegal foreign fisheries and their discards are all included. Total catches were estimated at 2.7 million tonnes over the time period considered, of which 653 000 t were caught domestically compared to 187 000 t reported by FAO . This shows that fisheries have more importance for Equatorial Guinea's food security than the official data suggest. In contrast to what is suggested by official figures, fisheries were shown to be strongly impacted by civil and political unrest; notably, they declined overall because of civil and political conflicts, socio‐demographic dynamics, and a growing role of the newly discovered oil resources, which directly and indirectly threaten the food security of the people of Equatorial Guinea.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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