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Record W2903803214 · doi:10.22329/csw.v19i2.5680

Responding to Neoliberalism

2018· article· en· W2903803214 on OpenAlexaffvenueabout
Sarah Woods, Tina Nadia Gopal, Purnima George

Bibliographic record

VenueCritical Social Work · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsToronto Metropolitan UniversityUniversity of Windsor
Fundersnot available
KeywordsNeoliberalism (international relations)SociologySituatedPolitical sciencePrisonEconomic growthPublic administrationPolitical economyCriminologyEconomics

Abstract

fetched live from OpenAlex

Amadeusz is a non-profit organization in Toronto, Canada, focused on fostering the opportunity among young people who experience incarceration and/or are vulnerable to the involvement in violence, and/or crime to create positive change in their lives and communities. As a non-profit organization situated in the third sector (i.e., voluntary sector), Amadeusz did experience the impacts of neoliberalism. However, it was able to successfully respond to neoliberalism and carry on with its agenda of change by adopting a dual strategy in the form of two important initiatives: The Look at My Life Project (TLMLP) and Project Quiet Storm (PQS). This article narrates the story of Amadeusz’s response to neoliberalism within prison, highlighting ways in which resistance was carried out along with embracing the current neoliberal practices, policies, and institutional culture that prevents access to education for young people on remand.

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)0.015
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0290.055
Scholarly communication0.0120.006
Open science0.0020.017
Research integrity0.0080.016
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.395
Teacher spread0.355 · 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 designTheoretical or conceptual
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

Citations4
Published2018
Admission routes3
Has abstractyes

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