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Record W7057186763

How Reliable Are Psychopathy Checklist-Revised Scores in Applied Settings? A Replication and Extension

2023· dissertation· en· W7057186763 on OpenAlexaboutno aff

Bibliographic record

VenueOakTrust (Texas A&M University Libraries) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsInter-rater reliabilityPsychopathyReliability (semiconductor)Replication (statistics)Consistency (knowledge bases)Variance (accounting)Poison controlAdversarial system
DOInot available

Abstract

fetched live from OpenAlex

The Psychopathy Checklist-Revised (PCL-R) has been described by some as the “gold standard” for assessing psychopathy and is generally accepted as a “reliable and valid” assessment tool. Despite its widespread use, a growing body of research suggests the PCL-R may not be particularly reliable in applied and adversarial settings. Studies suggest the interrater reliability of the PCL-R in field settings (intraclass correlation coefficients [ICCs] ranging .33 to .59) may be lower than posited in the instrument’s manual (ICC = .86 and higher); however, a large portion of these studies were conducted within Sexually Violent Predators evaluations, had small sample sizes, or both. The current study conducted a widescale case law review examining the interrater reliability of PCL-R scores in Canadian criminal justice proceedings. Additionally, potentially differing levels of reliability were evaluated as it pertains to variables such as retaining side, case type (sexual offense versus non-sexual offenses), independence of PCL-R ratings, and demographic information (gender, race/ethnicity, and province). \n\nA total of 176 cases were identified to have multiple PCL-R scores from different examiners. The single-rater ICC was .61 for the total sample, suggesting that nearly 40% of variance was due to error. ICC values were higher for sexual offense cases (.72) than non-sexual cases (.54), suggesting that issues of interrater reliability were not localized to SVP or sexual offending cases. There was evidence of adversarial allegiance such that experts from opposing sides produced lower ICC values (.60-.77), with Crown-retained experts consistently producing higher scores. Independently conducted evaluations demonstrated greater rater agreement (.68) than examiners who were aware of other PCL-R scores (.43), suggesting that awareness of other scores did not increase reliability but in fact lowered it. Rater agreement for Indigenous defendants (.45) was lower than non-Indigenous defendants (.64), suggesting that PCL-R scores may be more reliable for those reflective of the instrument’s early validation samples (i.e., Caucasian samples). Taken together, the PCL-R's low reliability raises concerns about its use, particularly in high-stakes situations. It is recommended that legal/clinical decision-makers consider limitations of the PCL-R and ensure that interpretations are made within the scope of the instrument’s applied reliability.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.221
Teacher spread0.211 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

Explore more

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