Can You Trust Who You See? The Evolution of Socially Cued Anticipatory Plasticity
Bibliographic record
Abstract
AbstractThe social environment can affect development and fitness. However, we do not know how selection acts on individuals that cue developmental pathways using features of the social environment. Socially cued anticipatory plasticity (SCAP) is a hypothetical strategy whereby juveniles use social cues to alter development to match their adult phenotype to the social environment that they expect to encounter. While intuitively appealing, the evolution of such plasticity is a puzzle, because the cue changes when individuals use it. Can socially cued plasticity evolve when such a feedback occurs? We use individual-based simulations to model evolution of SCAP in an environment that fluctuates between favoring each of two discrete phenotypes. We found that socially cued plasticity evolved, but only when strong selection acted on survival rather than on fecundity differences between adult phenotypes. In this case, the social cue reliably predicted which phenotype would be favored on maturation. Surprisingly, costs to plasticity increased the range of conditions under which it was adaptive. In the absence of costs, evolution led to a state where SCAP individuals could not effectively respond to environmental changes. Costs to plasticity lowered the proportion of the population that used SCAP, which in turn increased the reliability of the social cue and allowed individuals that used socially cued plasticity to switch between the favored phenotypes more consistently. Our results suggest that the evolution of adaptive plasticity in response to social cues may represent a larger class of problems in which evolution is hard to predict because of feedbacks among critical processes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".