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Record W4405352984

THE PERSONALITY ASSESSMENT INVENTORY (PAI): A SYSTEMATIC REVIEW OF ITS USE IN THE LEGAL FIELD

2021· review· en· W4405352984 on OpenAlexaboutno aff
Karin Arbach, Soraya Bazán, Marcelo Vaiman

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typereview
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsnot available
Fundersnot available
KeywordsPersonality Assessment InventoryField (mathematics)PsychologyPersonalityClinical psychologyApplied psychologySocial psychologyMathematics
DOInot available

Abstract

fetched live from OpenAlex

This systematic review study summarizes the available evidence on the use of the Personality Assessment Inventory in legal contexts, both with samples composed of accused and convicted persons, as well as with victims and plaintiffs. Following the PRISMA-P protocol, 131 articles that met the eligibility criteria were analyzed according to the subjects and psychometric properties investigated. Productivity was concentrated in a limited number of authors, institutions, countries, and journals. Most of the articles refer to the use of the PAI to analyze general personality and psychopathological characteristics, or psychometric properties of the instrument, in samples of middle-aged men in prisons in the United States and Canada. Research studies that use the PAI in samples of victims and women, and in Spanish-speaking legal contexts, emerge from this review as promising areas for future investigation. The development of these areas depends to a large extent on the cooperative capacity that legal, correctional, and security services achieve with academic research groups.

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 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)0.017
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.502
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0060.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.508
GPT teacher head0.647
Teacher spread0.139 · 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 teacher head, not a consensus.

Study designSystematic review
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

Citations0
Published2021
Admission routes1
Has abstractyes

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