Confirmatory Factor Analyses of Scores From Full and Short Versions of the Marlowe–Crowne Social Desirability Scale
Bibliographic record
Abstract
Self‐report measures are much used in social psychology. However, such measures are susceptible to response bias. The 33‐item Marlowe–Crowne Social Desirability scale (Crowne & Marlowe, 1960) is widely used to detect social desirability in responding. This study used confirmatory factor analyses and item and scale analyses to evaluate different, time‐saving, short versions of the scale. The results from 633 management undergraduates showed that all the short versions and the 2‐factor model are a significant improvement in fit over the full scale. There were no gender differences on the 14 measures. It is recommended that when the full scale is used, the separate attribution and denial scores are also used. Researchers who decide to use a short version should seriously consider Ballard's (1992) Scale 1 or composite versions because the present study identified these as the best short versions.
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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 | 0.015 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".