Adults show selective responses to unreliability based on the strength of counterevidence
Bibliographic record
Abstract
Adults can reflectively revise their beliefs and selectively respond to unreliable informants, despite often forming and revising beliefs unreflectively without assessing their reasons. This study investigates how the strength of counterevidence coming from an informant affects adults' ability to infer that the informant is unreliable through acquiring and responding to undermining defeaters (i.e., evidence suggesting that something was wrong with how the belief was formed). Participants (N = 120) watched videos of two informants acting on two locations: one whose actions reliably indicated the reward location, and one whose actions did not. The strength of feedback participants received after making a choice was manipulated across two conditions. In the Strong feedback condition, participants received positive feedback when they found the reward and explicit negative feedback when they did not, along with information about the reward's true location. In the Weak feedback condition, they received positive feedback, but incorrect choices simply resulted in no reward. Participants responded selectively to unreliability, following the Unreliable informant's evidence less often than that of the Reliable informant. This effect was stronger in the Strong feedback condition and was observed after only two to three misleading trials. In subsequent trials where informants were pitted against each other, participants in the Strong feedback condition, but not in the Weak feedback condition, consistently preferred the Reliable informant. These findings suggest that adults' ability to infer informants' reliability depends on the strength of counterevidence. Additionally, exploratory analyses reveal a key distinction between acquiring and responding to undermining defeaters.
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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 | 0.001 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".