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Record W4238894806 · doi:10.3138/utlj.60.2.687

CONSUMER CREDIT REDUX

2010· article· en· W4238894806 on OpenAlexvenueno aff
Anthony Duggan

Bibliographic record

VenueUniversity of Toronto Law Journal · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Contract Law
Canadian institutionsnot available
Fundersnot available
KeywordsIntervention (counseling)Government (linguistics)Economic interventionismEconomicsPolitical scienceConsumer protectionLaw and economicsLawPolitics

Abstract

fetched live from OpenAlex

Consumer credit law was a hot topic for legal scholars during the 1970s and 1980s, but its attraction waned in the next two decades, no doubt due in part to the dampening effect of the law and economics movement on government intervention and its advocacy. However, the last five years have seen a resurgence of scholarly interest in consumer credit law. This is partly because recent market developments have given academics a range of interesting new issues to address and partly because the new generation of legal scholars is economically literate and has been able to draw successfully on developments in law and economics, behavioural economics, and other new theoretical perspectives to enrich the debate over the case for regulation. This essay surveys the recent literature on three topics – sub-prime lending, credit cards, and payday loans – with particular reference to the challenges developments in these areas pose for truth-in-lending laws and policies that, at least until very recently, had remained largely unchanged since the heyday of consumer credit law reform.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.077
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0070.003
Open science0.0010.002
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0770.009

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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2010
Admission routes1
Has abstractyes

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