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Record W3124611152 · doi:10.60082/2817-5069.1175

Lessons in Access to Justice: Racialized Youths in Ontario's Safe Schools

2008· article· en· W3124611152 on OpenAlexaffvenueabout
Janet Mosher

Bibliographic record

VenueOsgoode Hall law journal · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsYork University
Fundersnot available
KeywordsEconomic JusticeContext (archaeology)SkepticismDispute resolutionFocus groupCriminologySociologyPolitical sciencePublic relationsLawEpistemology

Abstract

fetched live from OpenAlex

Access to justice is often equated with access to institutionalized dispute resolution processes, and the objective barriers that hinder such access-costs and delay most particularly-are commonly identified as the primary objects of reform efforts. In sharp contrast, when interviews and focus groups were conducted with racialized youths in Toronto regarding their experiences of access to justice in the context of school disciplinary matters, accounts of access to dispute resolution processes being impeded by costs and delay did not figure prominently. The interviews and focus groups revealed that many racialized youths scarcely ever considered accessing institutionalized dispute resolution processes largely because they lacked information that would enable them to "name" a potential legal problem, believed that "blaming" a powerful state actor was futile or would provoke retaliation, and had a deep skepticism regarding the ability of the legal system to dispense justice when "claims" are made. For the youths, understanding (as opposed to stereotyping), mutual respect, second chances, and the rule of law were the key features of access to justice.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.102
GPT teacher head0.387
Teacher spread0.285 · 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

Citations17
Published2008
Admission routes3
Has abstractyes

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