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Record W2158690154 · doi:10.1002/ab.20353

Role of executive dysfunction in predicting frequency and severity of violence

2010· article· en· W2158690154 on OpenAlex

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

VenueAggressive Behavior · 2010
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsWestern University
Fundersnot available
KeywordsExecutive functionsPsychologyExecutive dysfunctionRehabilitationCognitionPsychiatryPoison controlHuman factors and ergonomicsInjury preventionSuicide preventionClinical psychologyMedical emergencyMedicineNeuropsychology

Abstract

fetched live from OpenAlex

The adverse consequences of violence on society are tremendous. The proportion of offenders incarcerated for violent offenses is large, and the cost of keeping these offenders incarcerated is startling. Understanding and treating the causal underpinnings of violent crime is of utmost importance for individuals and society as a whole. Several factors have been identified as potential contributors to violent crime, including cognitive deficits in executive functioning [Hoaken et al., 2007]. To investigate this further, 77 offenders from Fenbrook Institution, a federal facility, were tested on a battery of executive functioning measures. Offenders were found to have broad and pervasive dysfunction in their executive abilities. In addition, specific scores from the battery were found using regression techniques, to predict the frequency and severity of past violent offending but not nonviolent offending. This speaks of the possibility of a new type of correctional rehabilitation program, one that focuses on the rehabilitation of basic executive functions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.311
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.292
Teacher spread0.279 · 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