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Record W2099645748 · doi:10.1037/a0018136

An item response theory integration of normal and abnormal personality scales.

2010· article· en· W2099645748 on OpenAlex
Douglas B. Samuel, Leonard J. Simms, Lee Anna Clark, W. John Livesley, Thomas A. Widiger

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.

Bibliographic record

VenuePersonality Disorders Theory Research and Treatment · 2010
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Mental Health
KeywordsPsychologyPersonalityItem response theoryPersonality theoryCognitive psychologyClinical psychologyPsychometricsSocial psychology

Abstract

fetched live from OpenAlex

The Diagnostic and Statistical Manual of Mental Disorders (DSM–IV–TR) currently conceptualizes personality disorders (PDs) as categorical syndromes that are distinct from normal personality. However, an alternative dimensional viewpoint is that PDs are maladaptive expressions of general personality traits. The dimensional perspective postulates that personality pathology exists at a more extreme level of the latent trait than does general personality. This hypothesis was examined using item response theory analyses comparing scales from two personality pathology instruments—the Dimensional Assessment of Personality Pathology-Basic Questionnaire (DAPP-BQ; Livesley & Jackson, in press) and the Schedule for Nonadaptive and Adaptive Personality (SNAP; Clark, 1993; Clark, Simms, Wu, & Casillas, in press)—with scales from an instrument designed to assess normal range personality, the NEO Personality Inventory–Revised (NEO PI-R; Costa & McCrae, 1992). The results indicate that respective scales from these instruments assess shared latent constructs, with the NEO PI-R providing more information at the lower (normal) range and the DAPP-BQ and SNAP providing more information at the higher (abnormal) range. Nevertheless, the results also demonstrated substantial overlap in coverage. Implications of the findings are discussed with respect to the study and development of items that would provide specific discriminations along underlying trait continua.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.608
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.392
Teacher spread0.345 · 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