Environmental harshness does not affect the propensity for social learning in great tits, Parus major
Bibliographic record
Abstract
According to the harsh environment hypothesis, natural selection should favour cognitive mechanisms to overcome environmental challenges. Tests of this hypothesis to date have largely focused on asocial learning and memory, thus failing to account for the spread of information via social means. Tests in specialized food-hoarding birds have shown strong support for the effects of environmental harshness on both asocial and social learning. Whether the hypothesis applies to non-specialist foraging species remains largely unexplored. We evaluated the relative importance of social learning across a known harshness gradient by testing generalist great tits, Parus major, from high (harsh)- and low (mild)-elevation populations in two social learning tasks. We showed that individuals use social learning to find food in both colour-associative and spatial foraging tasks and that individuals differed consistently in their use of social learning. However, we did not detect a difference in the use or speed of implementing socially observed information across the elevational gradient. Our results do not support predictions of the harsh environment hypothesis suggesting that context-dependent costs and benefits as well as plasticity in the use of social information may play an important role in the use of social learning across environments. Finally, this study adds to the accumulating evidence that the harsh environment hypothesis appears to have more pronounced effects on specialists compared to generalist species.
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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 | 0.000 | 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 | 0.000 | 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".