Mixed-species groups and the question of dominance in the social ecosystem
Bibliographic record
Abstract
Dominance interactions and hierarchies are of long-standing interest in the field of animal behaviour. Currently, dominance hierarchies are viewed as complex social structures formed by repeated interactions between individuals. Most studies on this phenomenon come from single-species groups. However, animals are constantly surrounded by and interact with individuals of other species. Behaviour and social interactions of individuals can be shaped by the presence or behaviour of other species in their social ecosystem, which has important implications for social behaviour in groups. Given how ubiquitous mixed-species animal groups are, deeper study of the relationships between mixed-species group (MSG) structure and dominance will be key to understanding constraints on individual behaviour and decision making. Here we call for more research into dominance interactions among individuals in MSGs. Greater understanding of the dynamics of dominance relationships among individuals in MSGs, whose size and composition can change considerably over shorter and longer term time frames, will be crucial to understanding their structure and functioning. This article is part of the theme issue 'Mixed-species groups and aggregations: shaping ecological and behavioural patterns and processes'.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".