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Record W3123234609

Commercial Litigation Funding: Ethical, Regulatory and Comparative Perspectives

2014· article· en· W3123234609 on OpenAlexaboutno aff
Camille Cameron, Jasminka Kalajdzic

Bibliographic record

VenueeYLS (Yale Law School) · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDispute Resolution and Class Actions
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticePolitical scienceWindsorPrincipal (computer security)CommodificationLawSociologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

There has been a proliferation of writing about commercial litigation funding (“CLF”) over the past few years, in both the academic and popular press. Too often, the literature presents a narrative of extremes. Commentators are either wholly against CLF on the basis that it gives rise to unethical behaviour and the commodification of our civil justice system, or wholly in support of it on the basis that it promotes access to justice and levels the playing field. A conference held at the University of Windsor Law School in July, 2013 brought together leading scholars, judges and lawyers from the United States, Australia and Canada to engage in a nuanced discussion about CLF that mediated between these extreme polarities. The first conference of its kind in Canada, discussion was focused on four themes: regulation, access to justice, ethics and impacts on class actions. In this article, the conference organizers, Dean Camille Cameron and Professor Jasminka Kalajdzic, survey the principal issues in the debates around CLF, summarize the key points in the conference papers, and identify the basic principles that might inform the regulation of litigation funding in Canada and elsewhere.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.038
GPT teacher head0.278
Teacher spread0.239 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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