The changes in zoological publication rates and focal subdisciplines between 1960 and 2022
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Since ancient times, zoology, as the branch of biology dealing with animals, has been a cornerstone of natural science and has developed substantially over the last century. We conducted a bibliometric analysis using structural topic modeling (STM) to determine changes in the representation of principal zoological subdisciplines in the literature between 1960 and 2022. We collated a corpus of 217 414 articles from 88 top‐ranked zoology journals and identified three main fields: (i) ecology, (ii) evolution, and (iii) applied research. Within these, we identified 10 major subdisciplines. The number of studies published per year grew from 118 in 1960 to 6635 in 2022. Macroscale‐related subdisciplines increased while classical and traditional subdisciplines decreased. Mammals (34.4%) and insects (18.1%) were the dominant taxa covered, followed by birds (15.2%) and fish (8.0%). Research on mammals, insects, and fish involved a broad range of subdisciplines, whereas studies of birds focused on ecological subdisciplines. Most publications were from the United States, followed by the United Kingdom, Germany, Canada, Australia, China, and Japan, with two developing countries, China and South Africa among the top 15 countries. There were different subdiscipline biases between countries, and the gross domestic product of each country correlated positively with its publication output ( R 2 = 0.681). We discuss our findings in the context of advances in technological innovations and computing power, as well as the emergence of ecology as a formal sister discipline, driven by changing environmental pressures and societal values. We caution that valuable publications from traditional zoological fields must not be completely supplanted by more contemporary topics and increasingly sophisticated analyses.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it