"Deutschlands Einzige Kolonie ist das Meer!" Die Deutsche Hochseefischerei und die Fischereikonflikte des 20. Jahrhunderts
Bibliographic record
Abstract
In the 20th century, the seas off Iceland, Greenland and Newfoundland were the main areas of the German deep-sea fishing fleet for many decades. The fishers and fishing vessels were often only a few nautical miles away from the coasts of the North Atlantic Islands, which was increasingly a source of conflict. On the one hand, the good catches in the North Atlantic created the economic boom of the fishing towns on the German coast. On the other hand, the islands separated from their former European colonial motherland and developed their own interest - not only political but also economic On the sovereignty over the resource fish. The principle of "freedom of the seas" had reached its limits, and fishing conflicts between the European nations and the shores of the fishing areas arose. In the 1970s, they culminated in the so-called "Cod-war" with Iceland. The present study analyzes the German role in these conflicts for the first time on a scientific basis and shows the consequences of the conflicts for the German coastal regions. At the same time, she explained that the drastic reduction of the German deep-sea fishing fleet had not been an unpredictable development since the 1980s, but that its rapid growth almost a century earlier was based exclusively on the colonial status of the shore areas. [From www.dsm.museum]
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.018 |
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".