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Record W4285333813 · doi:10.51952/9781447362494.ch003

Prisons of the world

2021· book-chapter· en· W4285333813 on OpenAlexaboutno aff

Bibliographic record

VenuePolicy Press eBooks · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

From the outset of my career in the Prison Service, in my search to understand the principles which underpinned the concept of imprisonment, I had developed an interest in prison matters beyond the United Kingdom and read all that I could find about the history of prisons and about the philosophical, social and judicial traditions on which it was based. My first direct experience of prisons outside the United Kingdom came in 1984 when I was awarded a Winston Churchill Memorial Trust Travelling Fellowship which enabled me to spend several months in North America studying the management of long-term prisoners in Canada and the United States. That circle was rounded some 30 years and over 70 countries later when I was asked to provide support to a number of legal initiatives to reduce the current excessive use of solitary confinement in prisons in those two countries. The experience of preparing expert evidence for court cases in California, British Columbia and Ontario over the last decade brought home to me forcefully that, while there had been many developments and some improvements in the treatment of prisoners since my first encounters with prisons in the region, some fundamental issues had not been resolved and may even have regressed, notwithstanding the fact that these two countries were among the most advanced in the world, prided themselves on being at the forefront of what was now described as ‘corrections’ management and were home to some of the world’s leading academic writers and teachers on criminal justice. These two sets of different experiences decades apart could be considered as a paradigm for the circuitous and often repetitive nature of all discussions about prisons and imprisonment and form a useful introduction to the description which follows in succeeding chapters about the prisons of the world.

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)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.045
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.010
Scholarly communication0.0110.009
Open science0.0010.009
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0450.004

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 head0.071
GPT teacher head0.330
Teacher spread0.259 · 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
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

Citations0
Published2021
Admission routes1
Has abstractyes

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