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Record W7005603709

Reforming Nova Scotia's Secure Care Model: Gender Bias and Calls to Action

2024· article· en· W7005603709 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaNova (rocket)PaternalismLegislationFoster careLaw reformAction (physics)
DOInot available

Abstract

fetched live from OpenAlex

The following paper is a critical analysis of Nova Scotia’s secure care model which is legislated under ss. 55-56 of the Children and Family Services Act. Under these provisions, children who are in the care of the Minister of Community Services or Mi’kmaw Family & Children’s Services of Nova Scotia may be confined against their will at the Wood Street Centre in Truro, Nova Scotia. This paper makes two critical arguments. The first is that the legislation concerning secure care in this province is notably overbroad, leaving children who are in crisis vulnerable to being subjected to what is akin to a carceral sentence at Wood Street. The second is that girls and adolescent women are particularly vulnerable to being confined in this facility due to lingering paternalistic attitudes toward female behavior, sexual autonomy, and mental health. Upon my review of recorded secure treatment application hearings in Nova Scotia, I found that judicial comments and legal reasoning appeared to demonstrate a bias toward female youth when compared to their male counterparts. This paper ultimately urges law makers to consider the harmful impacts of secure treatment and argues that law reform for secure care in Nova Scotia is necessary to protect and already extremely vulnerable subset of our population.

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)0.016
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.113
Threshold uncertainty score0.598

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.015
Scholarly communication0.0100.002
Open science0.0020.005
Research integrity0.0050.010
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 head0.025
GPT teacher head0.301
Teacher spread0.276 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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