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Record W2960490214 · doi:10.18192/jpp.v27i1.3342

A Little Less Conversation, A Lot More Action

2018· article· en· W2960490214 on OpenAlexvenueno aff
Jarrod Shook

Bibliographic record

VenueJournal of Prisoners on Prisons · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Leadership and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsConversationAction (physics)Political scienceLaw and economicsComputer sciencePsychologyCommunicationSociologyPhysics

Abstract

fetched live from OpenAlex

In our conclusion to Volume 26, Number 1&2 -Dialogue on Canada's Federal Penitentiary System and the Need for Penal Reform -we at the Journal of Prisoners on Prisons (JPP) left off with the following hope:… that our readers, and in particular Prime Minister Justin Trudeau and his Minister of Justice and Attorney General of Canada Jody Wilson-Raybould who was mandated to review criminal justice, laws, policies and practices enacted during the 2006-2015 period under the previous government, will take seriously the voices of prisoners (Shook and McInnis, 2017, p. 300).To encourage this process, the 19 October 2017 launch of the JPP included a press release summarizing the recommendations for penitentiary reform made by those who participated in the dialogue.Copies of the journal (Shook et al., 2017a), the press release, along with an article summarising the project (Shook and McInnis, 2017), and information about where the journal can now be accessed online (see www.jpp.org) were also sent directly to Prime Minister Trudeau, Minister of Justice and Attorney General Jody Wilson Raybould, Minister of Public Safety Ralph Goodale, former CSC Commissioner Don Head, Members of Parliament on the Standing Committee on Public Safety & National Security, as well as the Standing Committee on Justice and Human Rights.These materials were also provided to members of the Senate Committee on Human Rights, the Offi ce of the Correctional Investigator, the research offi ces of CSC and Public Safety Canada's, major media outlets, and a network of university colleagues whom we requested that they consider incorporating the special issue into their course content and required course reading lists.Promoting the dialogue in this way (also see Piché, 2015), created space for a variety of important newsmaking and policy conversations related

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)0.004
metaresearch head score (Gemma)0.019
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 score0.036
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0110.008
Scholarly communication0.0090.007
Open science0.0020.009
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0360.014

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 head0.149
GPT teacher head0.435
Teacher spread0.287 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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