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Record W7128212273 · doi:10.3138/ccar.v10i1-2.7

Beyond the Courtroom: Access to Justice, Privatization, and the Future of Class Action Research

2015· article· en· W7128212273 on OpenAlexaff
Michael Molavi

Bibliographic record

VenueCanadian Class Action Review · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsYork University
Fundersnot available
KeywordsExpansiveEconomic JusticeScholarshipPoliticsClass (philosophy)Class actionPublic policy

Abstract

fetched live from OpenAlex

This article critically assesses the role of class actions in enhancing access to justice from a socio-political perspective. Considering the broad social, cultural, and political implications of access to justice as both a theoretical principle and a policy objective, this article proposes that evaluations of class actions in light of access to justice must situate the procedure within its proper socio-political context. To this end, a critical framework is developed that focuses on the relationship of access to justice to developments in public policy and budgeting, including efficiency-based privatization, with a view to how these political dimensions affect poor and historically marginalized groups. The article proceeds in five interrelated stages. First, an overview of access to justice scholarship is presented through the lens of class actions. Second, a critical analysis of the role of class actions in enhancing access to justice is offered. Third, privatization and the figure of the private attorney general is discussed. Fourth, efforts at institutionalizing funding for class actions are addressed. Fifth, a preliminary research agenda is developed with an emphasis on socio-political variables such as public budgeting constraints, the influence of ideology, and the role of legal consciousness. Highlighting the social, cultural, and political dimensions of class actions in facilitating access to justice, the article concludes by proposing that an expansive understanding of access to justice demands an expansive approach to its study.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.797
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.136
GPT teacher head0.379
Teacher spread0.243 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2015
Admission routes1
Has abstractyes

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