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Record W3009375972 · doi:10.24908/jcri.v7i1.13140

I didn’t do that! Contested Definitions of Racialized Immigrant Youth in the Extra-Judicial Sanctions Program: Uncovering Hidden Voices.

2020· article· en· W3009375972 on OpenAlexaffvenueabout
Monetta Bailey

Bibliographic record

VenueJournal of Critical Race Inquiry · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsAmbrose University
Fundersnot available
KeywordsCONTESTSanctionsImmigrationSociologyEthnographyEthnic groupContext (archaeology)Gender studiesIdentity (music)CriminologyPolitical scienceLawAnthropology

Abstract

fetched live from OpenAlex

The social organization of knowledge focuses on how knowledge is created, enacted and shared by individuals in order to coordinate people’s actions. Using the frameworks of Institutional Ethnography (IE) and Critical Race Theory (CRT), this paper will look at the process of hearing the cases of racialized immigrant youth who are referred to the Extra-judicial Sanctions program in Calgary. I investigate how cultural knowledge impacts the way in which the youth’s cases are adjudicated. In particular, looking at how knowledge about various racialized and ethnic groups is gained in an environment of popular discourse, and how this influences the cases of racialized immigrant youth. I then look at how this racialized knowledge impacts the process of the youth and their families attempting to contest the definitions that are assigned to them during the hearing process. I suggest that in the context of a neo-liberal, “colour-blind” Canadian society and policy, workers in the EJS process draw on their own cultural understandings in order to interpret the interactions with racialized immigrant youth, which then impacts the ability of the youth to truly have their voices heard.

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)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.170
GPT teacher head0.428
Teacher spread0.257 · 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.

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

Citations2
Published2020
Admission routes3
Has abstractyes

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