Results From Three Performance Validity Tests (PVTs) in Adults With Intellectual Deficits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous studies of performance on the Word Memory Test (WMT; Green, 2003 Green, P. (2003). Green's Computerized Word Memory Test for Windows. User's manual. Edmonton, AB, Canada: Green's Publishing. [Google Scholar]; Green & Astner, 1995 Green, P., & Astner, K. (1995). Oral Word Memory Test: User's manual. Raleigh, NC: Cognisyst. [Google Scholar]) in adults with very low intelligence have provided conflicting evidence. Most studies suggest that a Full-Scale IQ (FSIQ) less than 70 cannot explain failure on the WMT, but Shandera et al. (2010 Shandera, A., Berry, D., Clark, J., Schipper, L., Graue, L., & Harp, J. (2010). Detection of malingered mental retardation. Psychological Assessment, 22, 50–56.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) suggest that many adults with mental retardation (MR) cannot pass the WMT. If so, we would expect adults with such low intelligence to fail the WMT at a high rate, even if they were motivated to perform well. In the current study, parents with an FSIQ of 70 or less, who were seeking custody of their children, rarely failed the WMT or the Medical Symptom Validity Test (MSVT; Green, 2004 Green, P. (2004). Green's Medical Symptom Validity Test: User's manual. Edmonton, AB, Canada: Green's Publishing. [Google Scholar]). They did not fail the WMT or MSVT any more often than adults of higher intelligence. On the other hand, adults with an external incentive to appear impaired scored significantly lower on the WMT and MSVT than did parents with an incentive to look good. The data strongly suggest that MR with an FSIQ in the range of 46 to 70 is not sufficient to explain failure on these performance validity tests by adults.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it