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Record W2026528873 · doi:10.1076/clin.16.4.495.13909

How'd They Do It? Malingering Strategies on Symptom Validity Tests

2002· article· en· W2026528873 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Clinical Neuropsychologist · 2002
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsBC Children's HospitalUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMalingeringPsychologyTest (biology)Memory testSession (web analytics)AudiologyClinical psychologyPsychiatryCognitionMedicineComputer science

Abstract

fetched live from OpenAlex

Twenty-five undergraduate students were instructed to feign believable impairment following a brain injury from a car accident and 27 students were told to perform like they had recovered from such an injury. Three forced-choice tests, the Test of Memory Malingering (TOMM), Victoria Symptom Validity Test (VSVT), and Word Memory Test (WMT) were given. Test-taking strategies were evaluated by means of a questionnaire given at the end of the test session. The results revealed that all the tasks differentiated between groups. Using conventional cut-scores, the WMT proved most efficient while the VSVT captured the most participants in the definitive below-chance category. Individuals instructed to feign injury were more likely to prepare prior to the experiment, with feigning of memory loss as the most frequently reported strategy. Regardless, preparation effort did not translate into believable performance on the tests.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.494
GPT teacher head0.489
Teacher spread0.005 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it