Modelling information exchange in worker–queen conflict over sex allocation
Bibliographic record
Abstract
We investigate the conflict between queen and worker over sex allocation, specifically the allocation of the queen's eggs between workers and reproductives and the allocation of the reproductive eggs between male and female. In contrast to previous models, we allow workers to observe and use information about the strategy of the queen. We consider three conflict models: simultaneous (no information exchange), sequential (a one-way information exchange) and negotiated (an iterated two-way information exchange). We find that the first model produces sex ratios intermediate between the classic queen (1:1) and worker (1:3) optima. The second model, in which the worker has information about the queen's decisions, produces a different result and one that is somewhat counter-intuitive in that the sex ratios are less female-biased than for the other two models, and in fact are often male-biased. The third model predicts sex ratios intermediate between the first two models. We discuss how these findings may shed new light on observed sex allocation patterns in social insects and we suggest some experimental tests.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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, 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".