Introducing a forced choice recognition trial to the Hopkins Verbal Learning Test – Revised
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
OBJECTIVE: This study was designed to replicate previous research on embedded validity indicators (EVIs) in the Hopkins Verbal Learning Test - Revised (HVLT-R) and introduce a new forced choice recognition trial (FCR). METHOD: = 14.5 years, 85% female) to either the control or experimental malingering condition, and were administered a brief battery of neuropsychological tests. RESULTS: Recognition memory based EVIs (both existing and newly introduced) effectively discriminated credible and non-credible response sets. An FCR ≤11 produced .59 sensitivity and perfect specificity to invalid responding. A Recognition Discrimination (RD) score ≤8 also produced a good combination of sensitivity (.35) and specificity (.96). The FCR trial made unique contributions to performance validity assessment above and beyond previously published EVIs. CONCLUSIONS: RD achieved ≥.90 specificity at higher cutoffs than previously reported. The newly introduced FCR trial has the potential to enhance the existing arsenal of EVIs within the HVLT-R. However, it must demonstrate its ability to differentiate genuine impairment from non-credible responding before it can be recommended for clinical use.
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 | 0.003 | 0.090 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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