Aquatic mammal science in Latin America: a bibliometric analysis for the first eight years of the Latin American Journal of Aquatic Mammals (2002-2010)
Bibliographic record
Abstract
We conducted a meta-analysis of the publication statistics for Vols. 1-8 of the Latin American Journal of Aquatic Mammals (LAJAM), the joint scholarly publication of the Sociedad Latinoamericana de Especialistas en Mamíferos Acuáticos and the Sociedad Mexicana de Mastozoología Marina, with the following purposes: (a) identifying the main patterns in the authorship and content published between 2002 and 2010, and (b) assessing the contributions of these scientific societies in the Latin American and global contexts. With the caveat that the results are only representative of the researchers that chose to publish in LAJAM during the period covered by the study, the metadata from 168 articles indicated that most of the research was conducted on small odontocetes (Sotalia, Pontoporia, Tursiops) and pinnipeds (Arctocephalus, Otaria, Mirounga) of coastal habits. Rorqual whales (Balaenoptera, Megaptera) and oceanic odontocetes (Stenella, Mesoplodon, Orcinus, Delphinus) also were well represented. Studies of distribution (including first records) were the most common, followed by those related to feeding, strandings, health and bycatch. Seventeen countries were represented in the primary affiliation of the lead author, but just five dominated the contribution: Brazil (52%), Argentina (10%), México (7%), Uruguay (5%) and USA (5%). Among institution types, a university was reported as the primary affiliation type by 50% of the authors, while 26% reported a NGO, 17% a government agency and 7% another type of organization. A social network analysis of 404 authors identified a large, well-connected cluster of 263 authors. Within this cluster, 13 authors from Brazil, Perú, Argentina and Colombia were among the most collaborative. The female to male ratio was 1:1.6 among lead authors and 1:3.2 among lead authors that published more than one article, suggesting a gender disparity within this scientific community. According to Google Scholar™, 91 articles in LAJAM were cited in other publications through January 2012, with an average of 7.5 citations per article. The 15 most cited articles had between 13 and 15 citations, were predominantly from Brazil, and were mainly about small cetaceans.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.078 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".