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<scp>N</scp> ew <scp>Y</scp> ork ( <scp>A</scp> uburn) Prison System

2017· other· en· W2914162188 on OpenAlexaff
Ashley T. Rubin

Bibliographic record

VenueThe Encyclopedia of Corrections · 2017
Typeother
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPrisonSentencePlan (archaeology)Spanish Civil WarEngineeringLawOrganised crimeCriminologyPolitical scienceSociologyHistoryComputer scienceArtificial intelligenceArchaeology

Abstract

fetched live from OpenAlex

Abstract The New York, or Auburn, system was a distinctive plan for prison organization developed early in the nineteenth century. Under this plan, prisoners worked in factory‐like settings during the day and retreated to solitary cells at night. The collection of prisoners in large rooms led some commentators to call it the “congregate system,” in contrast to its main competitor, the Pennsylvania System, which kept prisoners in solitary or “separate” confinement for the duration of their sentence. Other commentators called the Auburn System the “silent system” because prisoners were forbidden from talking with, or even looking at, one another during the work day. Emerging in the early 1820s in response to a rash of prison riots and chaos, the Auburn system came to dominate American prisons by the time of the Civil War. Although the postwar period experienced some fracturing of penal facilities, some version of the Auburn System continued to dominate and even formed the basis for the Big House prisons of the 1920s and 1930s, forever shaping America's imagination of what prisons look like until, perhaps, recently.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.224
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.017
GPT teacher head0.284
Teacher spread0.267 · 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.

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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