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Record W7128189067 · doi:10.3138/ccar.v10i1-2.185

The Evolution and Devolution of Aggregate Damages as a Common Issue

2015· article· en· W7128189067 on OpenAlexaboutno aff
James Sayce

Bibliographic record

VenueCanadian Class Action Review · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsnot available
Fundersnot available
KeywordsDamagesClass actionPunitive damagesDevolution (biology)Aggregate (composite)Economic JusticeEminent domainClass (philosophy)

Abstract

fetched live from OpenAlex

The certification of aggregate damages is an important step in pushing a class action toward resolution. If aggregate damages are certified, the common issues trial represents a figurative “gun to the head” of the defendant. If aggregate damages are not certified, pressure on the defendant is relieved, and the class is faced with a far less certain path. Even if the class is successful at the common issues trial, individual damages hearings may devolve into complex and lengthy miniature trials, where access to justice and judicial efficiency are sacrificed. Over the past decade, Canadian courts have been of two minds when it comes to aggregate damages. Initially, courts applied a strict interpretation of section 24 of the Class Proceedings Act, 1992, but subsequently they relaxed their interpretation, resulting in a wider array of scenarios where aggregate damages were certified. More recently, courts have returned to the more restrictive approach. This recent trend has led to some potentially unexpected results and a situation where aggregate damages are available only in the clearest of cases. This trend represents an inflexible and non-purposive reading of the CPA, and appellate guidance is needed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.912

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)0.0000.000

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 head0.035
GPT teacher head0.282
Teacher spread0.246 · 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
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
Published2015
Admission routes1
Has abstractyes

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