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Record W2036296572 · doi:10.1177/1073191104273515

Susceptibility of the MMPI-2 Clinical, Restructured Clinical (RC), and Content Scales to Overreporting and Underreporting

2005· review· en· W2036296572 on OpenAlexaff
Martin Sellbom, Yossef S. Ben‐Porath, John R. Graham, Paul A. Arbisi, R. Michael Bagby

Bibliographic record

VenueAssessment · 2005
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychologyMinnesota Multiphasic Personality InventoryClinical psychologyContent (measure theory)Social psychologyPersonality

Abstract

fetched live from OpenAlex

The authors examined and compared the susceptibility of three Minnesota Multiphasic Personality Inventory-2 (MMPI-2) scale sets (Clinical, Restructured Clinical [RC], and Content) to over- and underreporting using five analog samples. Two samples of 85 and 191 undergraduate students, respectively, took the MMPI-2 under underreporting versus standard instructions. Three samples consisting of 42 undergraduates, 73 psychiatric inpatients, and 84 medical patients took the MMPI-2 under overreporting versus standard instructions. A comparison of the effect sizes across the three sets of scales indicated that Clinical Scale scores are not less susceptible to distortion than the Content or RC Scales. An apparent lesser susceptibility to underreporting for the Clinical Scales was an artifact of the subtle items' effect on these scales.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.826
GPT teacher head0.644
Teacher spread0.182 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

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".

Quick stats

Citations25
Published2005
Admission routes1
Has abstractyes

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