Virtuous victims: Disability claimants who over- and under-report
Bibliographic record
Abstract
Objective: The present study was the first to investigate the test performance and symptom reports of individuals who engage in both over-reporting (i.e., exaggerating or fabricating symptoms) and under-reporting (i.e., exaggerating positive qualities or denying shortcomings) in the context of a forensic evaluation. We focused on comparing individuals who over- and under-reported (OR + UR) with those who only over-reported (OR-only) on the MMPI-3. Method: Using a disability claimant sample referred for comprehensive psychological evaluations (n = 848), the present study first determined the rates of possible over-reporting (MMPI-3 F ≥ 75 T, Fp ≥ 70 T, Fs ≥ 100 T, or FBS or RBS ≥ 90 T) with (n = 42) and without (n = 332) under-reporting (L ≥ 65 T). Next, we examined group mean differences on MMPI-3 substantive scale scores and scores on several additional measures completed by the disability claimant sample during their evaluation. Results: The small group of individuals identified as both over-reporting and under-reporting (OR + UR) scored meaningfully higher than the OR-only group on several over- and under-reporting symptom validity tests, as well as on measures of emotional and cognitive/somatic complaints, but lower on externalizing measures. The OR + UR group also performed significantly worse than the OR-only group on several performance validity tests and measures of cognitive ability. Conclusions: The present study indicated that disability claimants who engage in simultaneous over- and under-reporting portray themselves as having greater levels of dysfunction but fewer externalizing tendencies relative to claimants who only over-report; however, these portrayals are likely less accurate reflections of their true functioning.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".