Journal Publication Trends Regarding Cetaceans Found in Both Wild and Captive Environments: What do we Study and Where do we Publish?
Bibliographic record
Abstract
Scientists conducting research on cetaceans have a variety of publication outlets. However, a formal assessment of those options has not been conducted. To better understand the trends in publications regarding dolphins and whales, we surveyed peer-reviewed articles from 9 different databases. Our survey produced 1,628 unique articles involving 16 cetaceans found both in the wild and in captivity. Each article was coded a variety of information: habitat, geographic location, genus, topic, research design, and journal type. The analyses indicated that 68% studies were conducted with wild populations and 29% were performed with captive populations. A quarter of the journals publishing research on dolphins or whales published almost 80% of all the articles selected for this study. Studies were conducted across many different geographic locations and topics. Other major findings elucidated relationships between various variables. As expected, specific topics were more likely associated with certain research designs, habitats, and journal types. One of the most important findings of this study is the limited publication of research conducted with captive cetaceans. While it is important to continue to examine animals in their natural environments, there is much to be learned from studies conducted with animals in captivity. As a group, we must become cognizant of the publication trends which currently describe our research progress as we integrate our knowledge from captivity and the wild.
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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 | 0.029 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.055 | 0.066 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".