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Record W2620997730 · doi:10.60082/0829-3929.1256

“Don’t Want to Get Exposed”: Law’s Violence and Access to Justice

2017· article· en· W2620997730 on OpenAlexvenueaboutno aff
Sarah Bühler

Bibliographic record

VenueJournal of Law and Social Policy · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticeCriminologyPolitical scienceLawSociology

Abstract

fetched live from OpenAlex

For many members of marginalized communities, law is all too often an author of oppression, and the justice system is a site not of justice but of threat and harm. Yet most access to justice projects in Canada devote themselves to the task of rendering law and the justice system more available to the public without a serious consideration of these critical and troubling community-held insights. In this article, I draw on qualitative interviews conducted with community members in Saskatoon and the literature on law’s violence to argue that those who are concerned about access to justice must come to terms with harms done through law and legal processes upon members of marginalized communities. This requires a commitment by those working within the justice system to take seriously the perspectives and experiences of members of marginalized communities who are affected by law and justice systems, and to engage non-defensively with these insights. I argue that this engagement may lead to new ways of thinking about, and engaging with, access to justice. Specifically, I propose that it may lead to a de-emphasis on the current focus on “access” and a renewed emphasis on learning with and from communities about what it would take to move towards 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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.052
GPT teacher head0.396
Teacher spread0.344 · 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 designTheoretical or conceptual
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

Citations8
Published2017
Admission routes2
Has abstractyes

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