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Record W4391300856 · doi:10.18192/jpp.v33i1.7018

Standing at the Intersection of Identity and Convict Criminology: A Brief Exercise in Reflexivity

2023· article· en· W4391300856 on OpenAlexvenueno aff
J. Renee Trombley

Bibliographic record

VenueJournal of Prisoners on Prisons · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsConvictReflexivityIdentity (music)Intersection (aeronautics)CriminologySociologyGender studiesPsychologyEngineeringSocial scienceArtAesthetics

Abstract

fetched live from OpenAlex

The fi rst Convict Criminology (CC) session took place in 1997 at the American Society of Criminology's (ASC) annual meeting.The session was organized by members with personal experiences with the correctional system as formerly incarcerated (FI), as well as their allies.There was consensus among the group that many of the teachers in corrections had little, if any, experience in jails or prisons and lacked knowledge of what really took place behind their walls.In 2001, Richards and Ross defi ned the purpose and practice of CC, suggesting that those with fi rst-hand knowledge can provide an informed perspective on the functions and eff ects of prisons and jails.Merging insider knowledge, personal experience, and academic research related to criminal justice provides a paradigmatic approach that off ers distinct and relevant perspectives (Richards and Ross, 2001;Ross and Richards, 2003).In 2020, the Division of Convict Criminology (DCC) offi cially became part of the ASC.The original CC group was not particularly diverse, but over the last decade, the membership of CC has become more diverse in gender, sexuality, race and ethnicity, and FI background.The intersection of these identities among the members further increases the perspective and diversity of this group.As a CC member and the fi rst vice-chair of the DCC, supporting the mission and goals of the organization -including building diversity -are particularly important to me.Diverse experiences and voices support CC's mission to support justice-impacted scholars in providing rigorous research that examines all aspects of the criminal justice system, including policing, courts, and corrections, from those who have lived experiences within the fi eld (Tietjen, 2019).The DCC has explicitly addressed this issue, arguing that those in academia have largely ignored research from those who are formerly incarcerated or have had direct contact with the system.Acknowledging that the relevance of research conducted by incarcerated or FI individuals is often overlooked is signifi cant to the DCC's (2021) purpose: …to provide an intellectual home for all scholars/scientists who are interested in the study of Convict Criminology.The members of the

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.110
GPT teacher head0.390
Teacher spread0.280 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2023
Admission routes1
Has abstractyes

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