The legacy of Johan Hjort: challenges and critical periods—past, present, and future
Bibliographic record
Abstract
Abstract The 150th anniversary of Johan Hjort’s birth was celebrated by a symposium held in Bergen on 12–14 June 2019 to take a broad perspective on the origins of, and developments in, fisheries science and thereby examine current issues in fisheries science from different perspectives. To establish this type of non-traditional forum, historians of marine science and marine researchers from around the world met to explore potential new directions. The many transdisciplinary panel discussions, especially on subjects such as “the making of fisheries scientists”, revealed the pervading influence of family, educators, role models, and social circumstances. The 11 articles included in this symposium issue present a series of advancements in modern fisheries science, highlighting the contributions of Hjort and his contemporaries, Fyodor Baranov and Harald Dannevig. As expected, the effects of changing ocean climate were a dominant theme, which connected this symposium, and complemented, the 2014 symposium in honour of Johan Hjort's influential treatise released in 1914. Although no ground-breaking paradigms were presented, several new research directions were proposed in a creative atmosphere generated by participants. The social context of science had a key influence in Hjort’s day and continues to do so today and into the future.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".