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Record W4393208846 · doi:10.31261/ppk.2023.07.01.06

The common law approaches to identity theft: Implications for Hungarian law reform

2023· article· en· W4393208846 on OpenAlexaboutno aff
Dávid Tóth, Balázs Gáti

Bibliographic record

VenueProblemy Prawa Karnego · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Criminal Justice and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsLawLaw reformPolitical scienceIdentity (music)Common lawPhilosophy

Abstract

fetched live from OpenAlex

The incidence of identity theft is escalating, especially in international contexts. Owing to the advancement of information technology, crimes associated with this issue are borderless and can manifest anywhere. The objective of this study is to scrutinize the regulatory frameworks concerning identity theft in foreign jurisdictions. The essay not only considers theoretical aspects but also practical and criminological dimensions of the issue in question. As an outcome of the examination of these regulatory models, it is hoped that proposals de lege ferenda (‘regarding future law’) can be articulated for the Hungarian legislature.The initial segment of the article grapples with defining the phenomenon. There is no universally accepted definition of identity theft. Various terms are employed in foreign literature to describe the very phenomenon, including “identity theft” and “identity fraud.” Subsequent to the conceptual introduction, the study surveys the potential forms of identity theft.In the subsequent sections of the article, the regulatory models of identity theft in common law jurisdictions are analyzed. The regulatory frameworks of the United States, the United Kingdom, Canada, and Australia are subject to examination.In the concluding section of the study, recommendations for future legislation (de lege ferenda) are proposed.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.985
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.274
GPT teacher head0.375
Teacher spread0.101 · 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 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
Published2023
Admission routes1
Has abstractyes

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