‘I bet you know more and are nicer too!’: what children infer from others’ accuracy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research has shown that preschoolers monitor others' prior accuracy and prefer to learn from individuals who have the best track record. We investigated the scope of preschoolers' attributions based on an individual's prior accuracy. Experiment 1 revealed that 5-year-olds (but not 4-year-olds) used an individual's prior accuracy at labelling to predict her knowledge of words and broader facts; they also showed a 'halo effect' predicting she would be more prosocial. Experiment 2 confirmed that, overall, 4-year-olds did not make explicit generalizations of knowledge. These findings suggest that an individual's prior accuracy influences older preschoolers' expectations of that individual's broader knowledge as well as their impressions of how she will behave in social interactions.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it