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Record W2908254244 · doi:10.60082/0829-3929.1322

Law, Judges and Authorized Gambling in Italy: A Tale of Contradictions

2018· article· en· W2908254244 on OpenAlexvenueno aff
Nadia Coggiola

Bibliographic record

VenueJournal of Law and Social Policy · 2018
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCivil codeBusinessConsumer protectionLawService (business)Law and economicsPolitical scienceEconomicsMarketing

Abstract

fetched live from OpenAlex

To date, notwithstanding the large number of scholarly investigations into the legal implications of gambling, little attention has been paid to the interaction between contract law, and the negative moral or social labelling which traditionally affects gambling contracts in many Western countries. The purpose of this article is to investigate how Italian civil courts have applied Civil code and Consumer code rules on abusive clauses to cases involving authorized gambling and betting contracts. These rules should apply to authorized gambling and betting contracts, which generally involve an individual player and a professional service provider, either because the player adheres to a standard contract or because she should be considered a consumer. Unfortunately, Italian judges often refrain from applying these protective rules to cases involving gaming and betting contracts, to the detriment of players. This article critically investigates these cases to explore how judges justify this differential treatment of players of this form of legal game, highlighting the harmful effects of this discriminatory treatment on consumers and society in general.

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: Empirical
Teacher disagreement score0.882
Threshold uncertainty score0.396

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.107
GPT teacher head0.438
Teacher spread0.331 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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