Going beyond Natural Local Ecosystems, II
Bibliographic record
Abstract
Late medieval Europeans extended exploitation of fish stocks to marine frontiers previously little affected by intense human predation. Driven by demand since the twelfth century and supported by waves of innovative capture and preservation methods, herring fisheries in the North Sea and Baltic fed millions of northern Europeans with the largest medieval catches known. Stockfish (naturally freeze-dried cod) from arctic Norway went from a regional subsistence product c .1100 to an export trade profiting fishers and merchants alike. Elsewhere entrepreneurs caught, preserved, and exported pike and other fish from the eastern Baltic, hake and conger from the Channel approaches and Bay of Biscay, and migratory bluefin tuna off Sicily and the Gulf of Cadiz, all for consumption a thousand and more kilometers away. Transforming local abundances for distant tables at unprecedented scale drove new capitalized forms of organization and market behaviour. Consumers, merchants, and fishers saw fish as economic objects disconnected from any familiar nature and free for competitive exploitation. Yet besides prospects of infinite abundance the new frontier fisheries posed risks, and not simply those of hazardous access or human conflict. Heavily fished local stocks of herring successively crashed to commercial insignificance when further stressed by environmental changes in the pulsating arrival of the Little Ice Age. But the almost accidental discovery of virgin cod stocks off Newfoundland in the 1490s confirmed the mythic belief that abundance always lay over the next horizon. Thoughts of limits vanished at the eve of modernity.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".