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Record W28779522 · doi:10.1115/1.4037549

ADHD and Canadian youth: an evaluation of the neurocognitive disorder’s impact on criminal justice assessment, management, and policy

2008· dissertation· en· W28779522 on OpenAlexaboutno aff
Adrienne M. F. Peters

Bibliographic record

VenueJournal of Biomechanical Engineering · 2008
Typedissertation
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Biomedical Imaging and BioengineeringUniversity of Minnesota
KeywordsNeurocognitivePsychologyCriminologyCriminal justiceEconomic JusticePolitical sciencePsychiatryLawCognition

Abstract

fetched live from OpenAlex

Attention-deficit/hyperactivity disorder (ADHD) is the most commonly diagnosed disorder among Canadian youth today.The disorder is particularly visible in young offenders, highlighting the overrepresentation of this disorder in this population.Troublingly, the screening process for ADHD is virtually non-existent within our criminal justice system.In light of these circumstances, is the youth criminal justice system in Canada doing enough to provide care for young offenders who have ADHD?This research presents the findings of an exploratory analysis which included a Canadian youth court case analysis and 14 personal interviews.Results reveal that in order to adequately follow the guidelines of the Youth CriminalJustice Act a new approach to youth with mental health issues is necessary.This research proposes that a potential new approach should be based on a provincial model of funding, consisting of increased education and communication for professionals working in the youth criminal justice system.

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)0.002
metaresearch head score (Gemma)0.010
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 score0.051
Threshold uncertainty score0.371

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.384
Teacher spread0.322 · 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
Published2008
Admission routes1
Has abstractyes

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