Overt Honesty Measures Predicting Admissions: An Index of Validity or Reliability
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
Honesty questionnaires are often validated against a paper-and-pencil criterion in which respondents are asked to admit to past incidents of dishonesty. However, substantial overlap in the methods of assessment and in item content between predictor and criterion suggest that it is not validity that is being assessed, but rather a form of reliability. In this study, the relations between two overt measures of honesty (the Phase II Profile and the Workplace Productivity Questionnaire) and an admissions criterion were evaluated. The results suggest that the strong correlations between the Phase II Profile and the admissions criterion (r = -.67) and between scores on the Workplace Productivity Questionnaire and the admissions criterion (r = -.62) may be largely due to overlapping item content.
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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 | 0.020 | 0.584 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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