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Record W7019530833

Il ruolo dell'organizzazione criminale nel contrasto al traffico illecito di tabacchi lavorati esteri

2019· book-chapter· en· W7019530833 on OpenAlexaboutno aff

Bibliographic record

VenueNova Science Publishers (Nova Science Publishers, Inc.) · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCriminal Law and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSanctionsLegislationCollateralCriminal lawOrganised crimeLaw enforcementQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

the paper intends to analyze the features of the Italian criminal law on cigarette smuggling. The domestic system faces the illicit tobacco trade in a very peculiar way, especially if compared with the criminal law of other European countries (e.g. Germany, Greece, Portugal and Spain). The Italian strict regulation (artt. 291 bis, ter, quarter T.U.D.) could appear also unreasonable if set side by side with the domestic legislation on smuggling of goods. Indeed, the latter is characterized by a large use of administrative sanctions instead of the severe criminal penalties related to the cigarette smuggling. The paper aims at demonstrating that the domestic firm method is based on the will to obstruct the powerful criminal organizations, and it wants to underline the issues related to this peculiar approach. The above mentioned need shapes all the criminal provisions related to cigarette smuggling and it could entail relevant and collateral effects on the side of the citizens rights.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.004

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 head0.060
GPT teacher head0.325
Teacher spread0.265 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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