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Record W4413244146 · doi:10.3138/ccar.v16i2.117

United we Stand, Divided we Fall: Class Actions and Corporate Hegemony

2021· article· en· W4413244146 on OpenAlexaboutno aff
Rebecca Meharchand

Bibliographic record

VenueCanadian Class Action Review · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsClass actionHegemonyNeoliberalism (international relations)RedressPlaintiffSociologyLawMarxist philosophyPolitical scienceLaw and economicsCollective actionSupreme courtPoliticsState (computer science)

Abstract

fetched live from OpenAlex

Abstract: This paper examines the changes to Ontario’s Class Proceedings Act resulting from Bill 161 through a Marxist lens, with the aim of understanding class action proceedings as a tool for challenging corporate power by providing access to justice to plaintiffs and behaviour modification incentives for corporations. This paper argues that a class action proceeding is a form of collective action that can act as an effective way to challenge corporate hegemony under Neoliberalism. This essay commences with a brief background on corporate hegemony and Marxist theory, and then moves to an examination of consumer protection and collective rights under Neoliberalism. Finally, the bulk of this essay addresses how class action proceedings can be understood as an excellent tool for combating corporate hegemony and demanding consumer protection in a political and legal landscape that would seek to see vast numbers of plaintiffs denied meaningful redress. By situating this discussion within Marxist theory and a Neoliberal climate, the final section outlines the ways the changes made in Bill 161 not only further the agenda of corporate interests while potentially denying redress to plaintiffs, but also fail to follow the three main objectives of class action proceedings, as iterated by the Supreme Court of Canada.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.561
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.131
GPT teacher head0.271
Teacher spread0.140 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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