The (Long) Nose doesn’t have it: Nose Length as a Factor in Salt and Pepper Passage
Bibliographic record
Abstract
This paper contains expected abstract and report of results that would confirm Minér et al’s (2016) proposed experiment on salt passage. Eighty female undergraduates completed questionnaire with snacks and drinks, along with a salt shaker and a pepper shaker available. They were asked to pass salt or pepper by another female or a male who also worked on questionnaire, but who was in league with the experimenter. These confederates had either very long nose or normal-sized (short) nose (le nez normal). Participants complied to both requests, but were slower to respond to pepper request than to salt request and to the person with the long nose. Response times were particularly slow when the request was made by male with long nose (homme avec le nez long). Implications for similarity theory and attraction theory are discussed and suggestions are made for the future research going forward.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".