Socially Desirable Responding on the Web: Investigating the Candor Hypothesis
Bibliographic record
Abstract
The investigation presented here explores the hypothesis that participants are less likely to respond in a socially desirable fashion on self-report questionnaires completed on the Web relative to those completed in the laboratory--the candor hypothesis. A battery of social desirability questionnaires (i.e., Balanced Inventory of Desirable Responding [Paulhaus, 1984], Marlowe-Crowne Social Desirability Scale [Crowne & Marlowe, 1964], Eysenck Personality Questionnaire-Revised Lie Scale [Eysenck & Eysenck, 1994]) was administered to 3 groups: 2 groups consisted of undergraduate participants who were randomly assigned to complete the measures either in the laboratory (n = 60) or on the Web (n = 60), and 1 group consisted of self-selected participants who visited our experimental Web page and completed the measures online (n = 284). This design allowed us to assess the role of Web administration while controlling for differences in sample type, an oft-neglected issue in the Web literature. Results do not support the claim that administering self-report measures over the Web results in a decrease in socially desirable responding. Furthermore, these findings highlight the problems associated with confounding sample and medium. Implications for the use of Web as a research tool are discussed.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".