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Record W2576189532 · doi:10.1017/9781316266151

Criminal Law in Liberal and Fascist Italy

2017· book· en· W2576189532 on OpenAlexaff
Paul Garfinkel

Bibliographic record

VenueCambridge University Press eBooks · 2017
Typebook
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsReinterpretationPositivismLegal cultureCriminal lawScholarshipLawPolitical scienceCriminologyLiberalismLaw reformState (computer science)SociologyPoliticsPhilosophy

Abstract

fetched live from OpenAlex

By extending the chronological parameters of existing scholarship, and by focusing on legal experts' overriding and enduring concern with 'dangerous' forms of common crime, this study offers a major reinterpretation of criminal-law reform and legal culture in Italy from the Liberal (1861–1922) to the Fascist era (1922–43). Garfinkel argues that scholars have long overstated the influence of positivist criminology on Italian legal culture and that the kingdom's penal-reform movement was driven not by the radical criminological theories of Cesare Lombroso, but instead by a growing body of statistics and legal researches that related rising rates of crime to the instability of the Italian state. Drawing on a vast array of archival, legal and official sources, the author explains the sustained and wide-ranging interest in penal-law reform that defined this era in Italian legal history while analyzing the philosophical underpinnings of that reform and its relationship to contemporary penal-reform movements abroad.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.022
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.017
Scholarly communication0.0040.001
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.244
Teacher spread0.217 · 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
GenreOther

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

Citations39
Published2017
Admission routes1
Has abstractyes

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