MétaCan
Menu
Back to cohort
Record W2114391479 · doi:10.1111/lasr.12136

A Neo-Institutional Account of Prison Diffusion

2015· article· en· W2114391479 on OpenAlexaff
Ashley T. Rubin

Bibliographic record

VenueLaw & Society Review · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPrisonRealmFrontierField (mathematics)Political scienceLawSociologyCriminologyPolitical economy

Abstract

fetched live from OpenAlex

Interest in legal innovations, particularly in the criminal law realm, often centers on an innovation's emergence, but not its subsequent diffusion. Typifying this trend, existing accounts of the prison's historical roots persuasively explain the prison's “birth” in Jacksonian-Era northern coastal cities, but not its subsequent rapid, widespread, and homogenous diffusion across a culturally, politically, and economically diverse terrain. Instead, this study offers a neo-institutional account of the prison's diffusion, emphasizing the importance of national, field-level pressures rather than local, contextual factors. This study distinguishes between the prison's innovation and early adoption, which can be explained by the need to replace earlier proto-prisons, and its subsequent adoption, particularly in the South and frontier states, which was driven by the desire to conform to increasingly widespread practices. This study further attributes the isomorphic nature of the diffusion to institutional pressures, including uncertainty surrounding the new technology, pseudoprofessional penal reformers and their claims about competing models of confinement, and contingent historical factors that reinforced these institutional pressures. This study illustrates the importance of distinguishing between the motivations that initiate criminal law innovations and those that advance their diffusion.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Review
Teacher disagreement score0.840
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.057
GPT teacher head0.354
Teacher spread0.297 · 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 teacher head, 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

Citations1
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueLaw & Society ReviewSame topicCriminal Justice and Corrections AnalysisFrench-language works237,207