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Record W3087211078 · doi:10.1177/0002764220956698

The Complexities of Criminal Responsibility and Persons With Intellectual and Developmental Disabilities: How Can Therapeutic Jurisprudence Help?

2020· article· en· W3087211078 on OpenAlexaffabout
Voula Marinos, Lisa Whittingham

Bibliographic record

VenueAmerican Behavioral Scientist · 2020
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsBrock University
Fundersnot available
KeywordsTherapeutic jurisprudenceConceptualizationJurisprudenceImprisonmentCriminologyPsychologyLawMental healthIntellectual disabilityCriminal responsibilityDiminished responsibilityPsychiatryPolitical scienceCriminal law

Abstract

fetched live from OpenAlex

This article examines issues regarding legal capacity and criminal responsibility relating to persons with intellectual and developmental disabilities (IDD). We examined the case of a 28-year-old male identified as having the mental age of an 8-year-old, accused of four counts of possessing child pornography in Ontario, Canada. If convicted, the offenses carried a minimum mandatory sentence of 1-year imprisonment. The defense attorney argued that since persons are not criminally responsible when they are chronologically less than 12 years old, the same ought to be extended to those with a mental age of less than 12. The Crown prosecutor asserted that the defense’s connection of disability to a lack of capacity reverts our conceptualization of persons with IDD back to a time when they were infantilized. Using therapeutic jurisprudence as a framework, we examined whether problem-solving courts (e.g., mental health court) could be used to address the needs of a person with IDD and offer a different understanding and potential solution to nonjudicial decision makers that satisfies the principles of both criminal responsibility and public safety.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.996

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 studies0.0000.006
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 head0.101
GPT teacher head0.386
Teacher spread0.284 · 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 designQualitative
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

Citations4
Published2020
Admission routes2
Has abstractyes

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