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Introduction

2021· article· en· W3213806322 on OpenAlexaff
João Velloso, Vívian Ferreira Paes

Bibliographic record

VenueOñati Socio-legal Series · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Penology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCorporate governanceSocial controlConversationCriminalizationPolitical scienceSociologyState (computer science)Public administrationHumanitiesLawManagementPhilosophyComputer science

Abstract

fetched live from OpenAlex

This special issue is composed by six papers whose first versions were presented at the Oñati workshop Social Control, Judicialization of Social Problems and Governance of Security in Comparative Perspectives held at the IISL in July 2019. They are preceded by this introduction, where we contextualize the development of social control studies, pointing how they were originally framed as criminalization in the Global North and how the new millennium brought us an increasing number of studies discussing both criminalizations (in the plural!) and forms of judicialization and governance operating through regulatory, administrative, civil and hybrid legal regimes. By putting together articles about different contexts and jurisdictions into conversation, we hope to illuminate how legal orders (State-based or not) are mobilized to govern security and social problems, creating more nuanced categories and analytical tools to help thinking and resisting to penalization processes of any kind, anywhere, anytime.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.537
Threshold uncertainty score0.766

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0090.005
Open science0.0020.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.4630.302

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 head0.019
GPT teacher head0.305
Teacher spread0.286 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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