MétaCan
Menu
← Back to cohort
Record W3039035876 · doi:10.22215/etd/2019-13846

Carrying Disaster Lightly: Assessment of Resilience in Two Populations with Psychopathic Features

2019· dissertation· en· W3039035876 on OpenAlexaff
J. Sebastian Baglole

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychopathyPsychologyPsychological resilienceAntisocial personality disorderRecidivismDevelopmental psychologyResilience (materials science)Juvenile delinquencyClinical psychologyPoison controlSocial psychologyInjury preventionPersonalityMedicine

Abstract

fetched live from OpenAlex

Psychopathic traits are typically associated with antisocial and offending outcomes.In contrast, resilience (adaptive functioning despite risks) has been found helpful for pursuing positive outcomes (e.g., desistance).To determine the relationship between psychopathy, resilience, and antisocial or offending outcomes, two studies were conducted using two diverse samples: youngadult university students (N = 488) and youth offenders (N = 1,354).In the student young-adult sample, resilience mediated the relationship between psychopathy and antisocial behaviour.In the criminal youth sample, psychopathy had a stable relationship (i.e., consistent predictive validity) with offending over time; resilience was dynamic, its effect deteriorating over longer periods.Agency-related (internal) resilience was found to be more prevalent in females than males and significantly predicted desistance.This runs counter to relational-cultural theory, given that Social-related (external) resilience did not predict desistance in females.Future research should continue to examine gendered effects of internal and external resilience traits.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.027
GPT teacher head0.408
Teacher spread0.381 · 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
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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same topicPsychopathy, Forensic Psychiatry, Sexual Offending→French-language works237,207→