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Record W7128225383 · doi:10.3138/ccar.v11i2.321

Developing A Consistent Approach to Balance Distributions in Quebec

2016· article· en· W7128225383 on OpenAlexaboutno aff
Chris Trivisonno

Bibliographic record

VenueCanadian Class Action Review · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsnot available
Fundersnot available
KeywordsClass (philosophy)Class actionDamagesDistribution (mathematics)Order (exchange)Human settlementBalance (ability)Settlement (finance)Jurisprudence

Abstract

fetched live from OpenAlex

Similar to cy près distributions in common law Canada and the United States, Quebec courts distribute the balances of damages in class actions to third party charity organizations. This is a crucial step in the class action procedure as it is the judge's final opportunity to protect absent class members’ rights by ensuring that these distributions serve class members’ interests. Despite the frequncy of this practice, the Quebec jurisprudence has not developed a consistent approach to choosing recipients, and judges rarely provide written reasons on the issue. This makes it difficult for absent class members to understand how distributions serve their interests and, in some circumstances, could even create the perception that litigation actors put their own interests ahead of those of the class. This paper provides an empirical survey of balance distributions in Quebec, and emphasizes the importance of providing written reasons for choosing recipients, in order to demonstrate how a distribution specifically serves class members’ interests and to develop a consistent approach to choosing distribution recipients. Such an approach should consider the interests of the class members as well as the objectives of the class action: access to justice, behaviour modification, and judicial economy. The approach should also minimize settlements with fixed third party distributions, ensure that recipients are unrelated to the litigation actors, and aim to distribute funds to specific projects or services that may serve class members.

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 score0.891
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.057
GPT teacher head0.273
Teacher spread0.216 · 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
Published2016
Admission routes1
Has abstractyes

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