Social Performance Cues Induce Behavioral Flexibility in Humans
Bibliographic record
Abstract
Behavioral flexibility allows individuals to react to environmental changes, but changing established behavior carries costs, with unknown benefits. Individuals may thus modify their behavioral flexibility according to the prevailing circumstances. Social information provided by the performance level of others provides one possible cue to assess the potential benefits of changing behavior, since out-performance in similar circumstances indicates that novel behaviors (innovations) are potentially useful. We demonstrate that social performance cues, in the form of previous players' scores in a problem-solving computer game, influence behavioral flexibility. Participants viewed only performance indicators, not the innovative behavior of others. While performance cues (high, low, or no scores) had little effect on innovation discovery rates, participants that viewed high scores increased their utilization of innovations, allowing them to exploit the virtual environment more effectively than players viewing low or no scores. Perceived conspecific performance can thus shape human decisions to adopt novel traits, even when the traits employed cannot be copied. This simple mechanism, social performance feedback, could be a driver of both the facultative adoption of innovations and cumulative cultural evolution, processes critical to human success.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".