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Record W4322737674 · doi:10.1080/10282580.2023.2181285

Teaching and doing anti-criminology: An autoethnography of transgressive pedagogies

2022· article· en· W4322737674 on OpenAlex
Claudio Colaguori, Stephen L. Muzzatti

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueContemporary Justice Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsAutoethnographySociologyPower (physics)Critical pedagogyEconomic JusticeClass (philosophy)PedagogyRestorative justiceSpace (punctuation)CriminologyGender studiesEpistemologyLawPolitical science

Abstract

fetched live from OpenAlex

As both first-generation, working-class Canadians from Italian immigrant families we were very much outsiders to the academy when we began our respective university studies in the late 1980s. Today, as third-generation critical criminologists, we strive to bring an intersectional perspective to the classroom and to likewise enable marginalized students to find their voice and position themselves as active subjects, not objects of others’ inquiry. From sharing the insights offered by Left Realism and Zemiology the authors offer an autoethnographic account of teaching crime and justice. In keeping with hooks’ observation that the reality of class differences is starkly revealed in educational settings, this paper seeks to explore the intersections between teaching and learning as a process that involves existential self-reflection towards a critical pedagogy aimed at creating an inclusive teaching and learning space that challenges myths, demythologize power relations, and promotes social justice.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.888
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.238
GPT teacher head0.437
Teacher spread0.200 · 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