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Plea Bargaining, Conviction Without Trial, and the Global Administratization of Criminal Convictions

2020· article· en· W3010526667 on OpenAlexfundno aff
Máximo Langer

Bibliographic record

VenueAnnual Review of Criminology · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsnot available
FundersMcGill University
KeywordsPleaConvictionLawPolitical scienceCriminal trialCriminal procedureCriminal justiceCriminologyCriminal ConvictionCriminal lawPhenomenonPsychology

Abstract

fetched live from OpenAlex

This article documents the diffusion of plea bargaining and other mechanisms to reach criminal convictions without a trial and argues that their spread implies what this article terms an administratization of criminal convictions in many corners of the world. Criminal convictions have been administratized in two ways: ( a) Trial-avoiding mechanisms have given a larger role to nonjudicature, administrative officials in the determination of who gets convicted and for which crimes, and ( b) these decisions are made in proceedings that do not include a trial with its attached defendants’ rights. The article also proposes a way this phenomenon could be quantitatively measured by articulating the rate of administratization of criminal convictions, a metric to allow for comparison among different jurisdictions. The article then presents cross-national data from 26 jurisdictions on their rate of administratization of criminal convictions and different hypotheses that may help explain variation across jurisdictions on this rate.

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)0.007
metaresearch head score (Gemma)0.022
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: Review · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0020.014
Scholarly communication0.0060.006
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.083
GPT teacher head0.294
Teacher spread0.211 · 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
GenreReview

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

Citations56
Published2020
Admission routes1
Has abstractyes

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