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Record W2990663109

The Institutions of Innocence Review: A Comparative Sociological Perspective

2018· article· en· W2990663109 on OpenAlexaboutno aff
Jessica Roth

Bibliographic record

VenueeYLS (Yale Law School) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsnot available
Fundersnot available
KeywordsInnocenceAdversarial systemLawCriminal justiceSociologyConsciousnessPerspective (graphical)Criminal lawPolitical scienceComparative lawLaw and economicsCriminologyEpistemology
DOInot available

Abstract

fetched live from OpenAlex

The last three decades have seen the rise of an international innocence movement that has forced participants in diverse criminal justice systems to confront their systems’ fallibility, previously thought more theoretical than real. The public acknowledgment of that fallibility has led to the creation of new institutional mechanisms to re-examine old convictions. This short essay prepared for a symposium issue of the Rutgers University Law Review on the theory of criminal law reform compares the error correction institutions created in the United Kingdom, Canada, and the United States, three English-speaking countries with common law roots and an adversarial structure, through the lens of sociological theory. It finds that, consistent with what that literature suggests, the institutions created in each country reflect the circumstances in which “innocence consciousness” arose therein and the pre-existing institutional arrangements and cultural frames. This analysis offers valuable insights for reformers around the world who are considering how to address wrongful convictions.

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)0.030
metaresearch head score (Gemma)0.080
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 score0.030
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.080
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0150.016
Science and technology studies0.0070.033
Scholarly communication0.0210.017
Open science0.0020.007
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.111
GPT teacher head0.408
Teacher spread0.298 · 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
Published2018
Admission routes1
Has abstractyes

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