If Maritime Historians Are in Danger of “being left with their journals and not much else” (Lewis Fischer), What Can Those Journals Tell Us about Ourselves? A Ten-Year Study
Bibliographic record
Abstract
This article examines the width and variety of contemporary maritime history - a concern of Skip Fischer in his later years, and which gives the article its title. Maritime history can provide a major template for understanding change, but it can only achieve this by actively investigating the multiple ways in which human beings relate to the sea. The author listed 30 categories that would reflect this possible diversity and then coded all the articles in the four major English maritime history journals for the period 2009-2018 (N=774 papers by 897 authors). The results were clearcut. Papers on nations’ navies accounted for 43.3 percent and papers on mercantile matters 44.8 percent, highlighting a lack of diversity in research topics and leading the author to fear for the future of maritime history. Cet article traite de l’ampleur et de la diversité de l’histoire maritime contemporaine, une des préoccupations de Skip Fischer au cours des dernières années de sa vie. L’histoire maritime peut servir de modèle permettant de comprendre le changement, mais elle ne peut y parvenir qu’en analysant avec diligence les maintes façons dont les êtres humains exploitent la mer. L’auteur a répertorié 30 catégories qui représentent cette diversité d’usage, puis il a codé tous les articles dans les quatre grandes revues d’histoire maritime de langue anglaise pour la période 2009-2018 (N = 774 articles par 897 auteurs). Les résultats sont clairs. Les articles sur les marines des nations représentent 43,3 pour cent, tandis que les articles sur les questions mercantiles représentent 44,8 pour cent du total. Ces résultats soulignent un manque de diversité au niveau des sujets de recherche, entraînant chez l’auteur des craintes à l’égard de l’avenir de l’histoire maritime.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".