Employment-Related Motivational Distortion: Its Nature, Measurement, and Reduction
Bibliographic record
Abstract
The behavioral variable employment-related motivational distortion (EMD) was defined and measured. In Study 1, a sample of 250 undergraduates completed the California Psychological Inventory (CPI), Form 434, on two separate occasions in which they responded (a) honestly and (b) as if applying for a job they valued. Four different change measures indexed participants’ response changes between the two conditions on a CPI-based scale measuring counter productivity (CPI-Cp). A composite of these four measures provided an EMD criterion, which enabled the development, in Study 2, of a 56-item CPI-based EMD predictor scale. On the basis of eight samples comprising a total Nof 2,074, internal consistency and test-retest reliability estimates for the CPI-EMD scale ranged between .72 and .86. Correlations with NEO PI-R domain and facet scales provided construct information about EMD. In Study 3, CPI-Cp scale scores adjusted for EMD manifested (a) reliability ranging from .71 to .87 over eight samples and (b) somewhat different correlations than for the unadjusted scale with Big Five personality scales. In addition, some evidence was found for gains in criterion correlations with EMD adjustments.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".