Bibliographic record
Abstract
For my doctoral research I examined social decision-making in a cooperatively breeding cichlid fish, Neolamprologus pulcher with a focus on affiliation and aggression. I investigated the role that the nonapeptide hormone, isotocin, plays in modulating social decisions in these contexts. I show that N. pulcher males prefer to join larger groups regardless of the rank at which they will join, whereas females prefer larger groups only when they can join a group in a high rank (Chapter 2). I examined decision-making during resource contests in (Chapter 3) and found that N. pulcher are sensitive to the size of their opponents, making fighting decisions depending on their opponents’ body size. I also found that smaller N. pulcher are more motivated to persist within contests, showing a shorter latency to resume fighting following interruption (Chapter 4). In Chapters 5 and 6, I explored the role of isotocin (the teleost fish homologue of oxytocin) in regulating social behaviour. I discovered that an increase in isotocin increased responsiveness to social information. Fish treated with isotocin were more sensitive to their opponent’s size in contests and were more submissive to dominant individuals within their social group (Chapter 5). Unexpectedly, I found that exogenous isotocin reduced sociality in N. pulcher, and that an isotocin receptor antagonist increased it (Chapter 6). These results suggest that the relationship between isotocin and social behaviour is both complex and context specific. In my final data chapter, I used social network analysis to explore the role of dominance interactions in determining the structure of N. pulcher social groups. I found that N. pulcher dominance hierarchies are highly linear, but that dominance interactions are not predicted by sex or body size asymmetry (Chapter 7). I found that conflict within N. pulcher social groups is greatest at the top of the dominance hierarchy. Taken together the results of my thesis helps to elucidate the behavioural and hormonal basis of social decision-making in a cooperatively breeding vertebrate and help to illuminate the evolution of social behaviour.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".