The Conscientious Responders Scale Helps Researchers Verify the Integrity of Personality Questionnaire Data
Bibliographic record
Abstract
is a five-item embeddable validity scale that differentiates between conscientious and indiscriminate responding in personality-questionnaire data (CR & IR). This investigation presents further evidence of its validity and generalizability across two experiments. Study 1 tests its sensitivity to questionnaire length, a known cause of IR, and tries to provoke IR by manipulating psychological reactance. As expected, short questionnaires produced higher Conscientious Responders Scale scores than long questionnaires, and Conscientious Responders Scale scores were unaffected by reactance manipulations. Study 2 tests concerns that the Conscientious Responders Scale's unusual item content could potentially irritate and baffle responders, ironically increasing rates of IR. We administered two nearly identical questionnaires: one with an embedded Conscientious Responders Scale and one without the Conscientious Responders Scale. Psychometric comparisons revealed no differences across questionnaires' means, variances, interitem response consistencies, and Cronbach's alphas. In sum, the Conscientious Responders Scale is highly sensitive to questionnaire length-a known correlate of IR-and can be embedded harmlessly in questionnaires without provoking IR or changing the psychometrics of other measures.
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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 | 0.016 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".