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Record W7104662673 · doi:10.4324/9781003615620-7

#Blackvoicesmatter

2025· book-chapter· en· W7104662673 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsLived experienceReflexivityNarrativeCriminal justiceDiversity (politics)Politics

Abstract

fetched live from OpenAlex

Re-entry for formerly incarcerated Black people in Canada has become an urgent social and political issue over the past decade, especially in Toronto. From 2020 to 2021, 9% of people under federal jurisdiction, whether in custody or being supervised in the community, were Black, despite only consisting of about 4% of Canadian adults (OCI, 2022). As such, the Black narrative surrounding lived experience is invaluable. Albeit at times viewed as homogenous in nature, the Black experience is truly one of a kind. So much diversity lies in the community in which we find ourselves co-existing. To define lived experience means capturing the tones of diversity , priority and collaboration . Lived experiences in the Black community are varied but can be categorized according to personal and vicarious experiences. Personal experience can be defined as an individual having a firsthand account of being incarcerated. Conversely, vicarious experiences are relational, whereby one&s;s lived experience is based on secondhand accounts or observations of the impacts of the criminal justice system. At times, vicarious lived experience is more than just a point of reference for storytelling. Rather, there is, at times, a physiological and psychological trauma response that is elicited when someone sees or hears of the repeated impacts of the criminal justice system. Priority means stepping back when shining light on personal lived experience . At times, it is tempting for academics with no personal lived experience to over-participate in the narrative about incarceration. As a reflexive scholar, I am mindful of this tendency. As such, we use the term priority to place value on the lived-experiences that are most enriching to the conversation, which is personal lived experience . Collaboration captures the fact that these two voices co-exist in space to provide a comprehensive understanding of lived experience . Co-authors Kadija Osei and Christopher Husbands are living examples of how we define vicarious and personal lived experience , respectively.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.892
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.8920.632

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 head0.024
GPT teacher head0.309
Teacher spread0.284 · 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.

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
Published2025
Admission routes1
Has abstractyes

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