Socially segregated, sympatric sperm whale clans in the Atlantic Ocean
Bibliographic record
Abstract
Sperm whales (Physeter macrocephalus) are unusual in that there is good evidence for sympatric populations with distinct culturally determined behaviour, including potential acoustic markers of the population division. In the Pacific, socially segregated, vocal clans with distinct dialects coexist; by contrast, geographical variation in vocal repertoire in the Atlantic has been attributed to drift. We examine networks of acoustic repertoire similarity and social interactions for 11 social units in the Eastern Caribbean. We find the presence of two socially segregated, sympatric vocal clans whose dialects differ significantly both in terms of categorical coda types produced by each clan (Mantel test between clans: matrix correlation = 0.256; p ≤ 0.001) and when using classification-free similarity which ignores defined types (Mantel test between clans: matrix correlation = 0.180; p ≤ 0.001). The more common of the two clans makes a characteristic 1 + 1 + 3 coda, while the other less often sighted clan makes predominantly regular codas. Units were only observed associating with other units within their vocal clan. This study demonstrates that sympatric vocal clans do exist in the Atlantic, that they define a higher order level of social organization as they do in the Pacific, and suggests that cultural identity at the clan level is probably important in this species worldwide.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".