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Record W4415294787 · doi:10.1080/03626784.2025.2529817

Indigenous students homeplacing against carcerality

2025· article· en· W4415294787 on OpenAlexaff
Fadi Ennab, Janet Nowatzki

Bibliographic record

VenueCurriculum Inquiry · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndigenousTraditional knowledgeIndigenous educationEthnic groupEthnography

Abstract

fetched live from OpenAlex

To promote collective liberation and social transformation, Indigenous students need educational spaces where they can think and act in caring ways; they need space to direct care towards each other and against policing that criminalizes their movements and spaces. In this article, we draw on bell hooks’s (Citation2007) notion of homeplace as an analytic prism to highlight the need for educational spaces for Indigenous families that are grounded in care and resistance against policing. We examine interviews conducted with Indigenous families on their experiences with policing and safety in schools (Ennab, Citation2022). In this article, we make four interrelated points. First, there is a need for spaces and relationships that allow youth to be free to express themselves and develop friendships based on mutual reciprocity, which we call practicing freedom. Second, the racial targeting of Indigenous students’ homeplaces (or homeplacing activities) forces them to engage in fugitive practices. Third, Indigenous students need educational spaces in which they can be critical of the role of policing in their lives. Fourth and finally, we argue that because schools are structured to reproduce racism, it is important to promote homeplacing practices to support Indigenous students to work toward an abolitionist praxis aimed at dismantling existing institutions and building caring relationships and communities.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.005
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.023
GPT teacher head0.372
Teacher spread0.349 · 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 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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