Confounding social and mating systems predictably lead to biased results when examining the evolution of cooperative breeding in cichlids: A response to Tanaka et al.
Bibliographic record
Abstract
Abstract In 2017, we demonstrated that transitions to cooperative breeding in Lamprologine cichlid fishes were not related to a species’ social mating system (Dey et al. 2017. Nature Ecology & Evolution , 1 , 137). This contrasted previous evidence that monogamy (and a low degree of promiscuity) promoted transitions to cooperative breeding in other taxa. Recently, Tanaka et al. (2018. Ethology , 124 , 777–789) critiqued our study and argued that a re‐analysis of the data shows transitions to cooperative breeding are promoted by non‐monogamous mating systems. Here, we show that Tanaka et al.'s critique contains numerous inaccuracies. In addition, we show that the results put forth by Tanaka et al. emerge only under the extreme scenario in which all cooperative breeding species are classified as non‐monogamous, which we argue arises because Tanaka et al. confound social systems and mating systems. While we agree that there is uncertainty regarding the mating system of some Lamprologine species, we argue this uncertainty was sufficiently addressed through the extensive sensitivity analyses conducted in our original study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".