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Record W1990262335 · doi:10.1080/14999013.2014.908429

Interrater Reliability and Concurrent Validity of the HCR-20 Version 3

2014· article· en· W1990262335 on OpenAlexaff
Kevin S. Douglas, Henrik Belfrage

Bibliographic record

VenueInternational Journal of Forensic Mental Health · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsInter-rater reliabilityPsychologyConcurrent validityReliability (semiconductor)Clinical psychologyRating scaleDevelopmental psychologyPsychometricsInternal consistency

Abstract

fetched live from OpenAlex

We evaluated the interrater reliability and concurrent validity of the HCR-20 Version 3 (HCR-20 V3 ). Three sets of ratings were completed by experienced clinicians for 35 forensic psychiatric patients, for both HCR-20 Versions 2 and 3. Reliability analyses focused on ratings of the presence of Version 3 risk factors, presence of Version 3 risk factor sub-items, relevance ratings for Version 3 risk factors, and Version 3 summary risk ratings for future violence. Concurrent validity analyses focused on the correlational association between Versions 2 and 3 in terms of the number of risk factors present. Findings indicated that Versions 2 and 3 were strongly correlated (.69 – .90). Interrater reliability was consistently excellent for the presence of risk factors and for summary risk ratings. The majority of relevance and sub-item ratings were in the good to excellent range, although there was a minority of such ratings in the fair or poor categories. Findings support the concurrent validity and interrater reliability of HCR-20 V3 . Implications for use of HCR-20 V3 by professionals and agencies are discussed.

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)0.043
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0430.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.492
GPT teacher head0.518
Teacher spread0.026 · 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 designNot applicable
Domainnot available
GenreEmpirical

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

Citations67
Published2014
Admission routes1
Has abstractyes

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