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Record W2792557315 · doi:10.15173/ijrr.v1i1.3355

Point prevalence of adults with intellectual developmental disorder in forensic psychiatric inpatient services in Ontario, Canada

2018· article· en· W2792557315 on OpenAlexaffabout
Marc Woodbury‐Smith, Ivana Furimsky, Gary Chaimowitz

Bibliographic record

VenueInternational Journal of Risk and Recovery · 2018
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsForensic sciencePsychiatryCriminal justiceDemographicsMental healthForensic psychiatryEconomic JusticeMedicinePsychologyDemographyCriminologyPolitical scienceLawSociology

Abstract

fetched live from OpenAlex

A significant minority of people with Intellectual Developmental Disorder (IDD) may come into contact with the criminal justice system as a result of criminal behaviours, and many of these who are deemed Unfit to stand trial or Not Criminally Responsible (NCR) will be transferred to forensic psychiatric facilities. Although the perception is that the frequency is increasing, the exact number is unclear, prompting us to conduct a provisional survey of forensic facilities across the province of Ontario to determine (i) point prevalence of IDD and (ii) the characteristics of such individuals. Detainees with IDD were identified in forensic mental health facilities across the Province of Ontario, and information was collected regarding their demographics, characteristics of their index offence and length of stay. We calculated a point prevalence (December 2012) of 19%, and identified that individuals with IDD stayed, on average, longer in these facilities than their non-IDD peers. We argue for the need to set up a working group to begin to address forensic care pathways for adults with IDD

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.393

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 head0.004
GPT teacher head0.219
Teacher spread0.215 · 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.

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

Citations9
Published2018
Admission routes2
Has abstractyes

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