Constraints and flexibility in mammalian social behaviour: introduction and synthesis
Bibliographic record
Abstract
This paper introduces a Theme Issue presenting the latest developments in research on the interplay between flexibility and constraint in social behaviour, using comparative datasets, long-term field studies and experimental data from both field and laboratory studies of mammals. We first explain our focus on mammals and outline the main components of their social systems, focusing on variation within- and among-species in numerous aspects of social organization, mating system and social structure. We then review the current state of primarily ultimate explanations of this diversity in social behaviour. We approach the question of how and why the balance between behavioural flexibility and continuity is achieved by discussing the genetic, developmental, ecological and social constraints on hypothetically unlimited behavioural flexibility. We introduce the other contributions to this Theme Issue against this background and conclude that constraints are often crucial to the evolution and expression of behavioural flexibility. In exploring these issues, the enduring relevance of Tinbergen's seminal paper 'On aims and methods in ethology', with its advocacy of an integrative, four-pronged approach to studying behaviour becomes apparent: an exceptionally fitting tribute on the 50th anniversary of its publication.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".