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Record W7132908565

My Prison Academia: A Comparative Curriculum Analysis of US Canadian Prison Post-secondary Education (PPSE) Programs Inside-out Walls to Bridges

2022· dissertation· W7132908565 on OpenAlexaboutno aff
Nolan Fontaine

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPrisonCurriculumSolitary confinementDialecticState (computer science)Space (punctuation)Plan (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

As the prison-industrial complex in the US and Canada continues expanding (Davis & Roswell, 2013), prison abolitionists continue to find covert, novel pathways to make “non-reformist reforms” (Wilson-Gilmore, 2012) or transformational changes within intuitions and occasionally super-structures. A more recent, compulsory way in which educators in the United States of America (US) and Canada began this shift is through prison post-secondary education programs (PPSE’s). Before the time of COVID-19, discourse about inside folks being released en masse in the US and Canada (Gostin, Friedman, Wetter, 2020; R v. TK, 2020) would have been deemed as farfetched; consider that 800 million jobs will be lost worldwide (BBC, 2017) due to automation displacement. This dialectical antagonism between workers and the state is one of many aspects of which we can shape the discourse and create a counter-narrative shifting towards an abolitionist framework (Davis, 2005, Wilson-Gilmore, 2012, Kaba, 2013, Roberts, 2019). This can be done by ensuring that prison post-secondary education program curriculums are undergirded with an anti-war/anti-imperial, abolitionist (ibid) and queer of color lens (Ferguson, 2006). For the purpose of this non-probability, exploratory, comparative, convenience research design, this paper will use a curriculum analysis to explore whether PPSE’s in the U.S. and Canada – primarily Inside-Out Prison Exchange and Walls to Bridges Prison Collective – incorporate an abolitionist or queer of color lens.With American and Canadian PPSE’s, the prison immersion training both outside and inside of the carceral space with the inside prison think-tank (Inside-Out) and the inside prison collective (Walls to Bridges) serve as spaces where facilitators are trained. Training inside of the carceral space was crucial to undertaking this work. Using a historical materialist and radical queer lens, this research will look at the pedagogical and andragogic praxis’ that prison instructors learn in the carceral space; this research will also give an unbiased explanation of how Walls to Bridges, former “Inside-Out: Canada” evolved from Inside-Out Prison Exchange. This research will also compare and contrast the pedagogical and andragogic praxis when inside the carceral space. Limitations of this study are also explored given the current historical moment. Recommendations will direct how this study will build upon future research design(s), as well as inform how this dissertation-in-practice’s final product is scaffolded. Data analysis from the dissertation-in-practice will inform the final product, which will be an Alternative Spring Break (ASB) prison post-secondary education curriculum for US and Canadian students interested in pre-prison immersion to be rooted in an abolitionist praxis.

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)0.005
metaresearch head score (Gemma)0.016
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.938

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.015
Science and technology studies0.0290.010
Scholarly communication0.0080.004
Open science0.0030.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.000

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 head0.029
GPT teacher head0.399
Teacher spread0.370 · 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
Published2022
Admission routes1
Has abstractyes

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