Flipping the Script: Measuring Both Performance Validity and Cognitive Ability with the Forced Choice Recognition Trial of the RCFT
Bibliographic record
Abstract
In this study we attempted to replicate the classification accuracy of the newly introduced Forced Choice Recognition trial (FCR) of the Rey Complex Figure Test (RCFT) in a clinical sample. We administered the RCFT FCR and the earlier Yes/No Recognition trial from the RCFT to 52 clinically referred patients as part of a comprehensive neuropsychological test battery and incentivized a separate control group of 83 university students to perform well on these measures. We then computed the classification accuracies of both measures against criterion performance validity tests (PVTs) and compared results between the two samples. At previously published validity cutoffs (≤16 & ≤17), the RCFT FCR remained specific (.84–1.00) to psychometrically defined non-credible responding. Simultaneously, the RCFT FCR was more sensitive to examinees’ natural variability in visual-perceptual and verbal memory skills than the Yes/No Recognition trial. Even after being reduced to a seven-point scale (18-24) by the validity cutoffs, both RCFT recognition scores continued to provide clinically useful information on visual memory. This is the first study to validate the RCFT FCR as a PVT in a clinical sample. Our data also support its use for measuring cognitive ability. Replication studies with more diverse samples and different criterion measures are still needed before large-scale clinical application of this scale.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".