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Record W3133660564 · doi:10.48336/cytn-9h15

Restorative justice education and social dynamics in the classroom

2022· dissertation· en· W3133660564 on OpenAlexaffabout
Tina Saleh

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsIndigenousRestorative justiceContext (archaeology)PedagogyQualitative researchSocial justiceSociologyPerceptionIndigenous educationSocial sciencePsychologyCriminologyGeographyEcology

Abstract

fetched live from OpenAlex

In this research, I examine teachers’ experiences with implementing Restorative Justice Education (RJE) in schools in Newfoundland. I investigate their experiences with navigating social class and social production in the classroom, and their perceptions around the change in culture that RJE is producing in schools. Further, I look how teachers think Restorative Justice Education is contributing to reconciliation efforts in the Canadian context. I also look at how teachers think RJE is creating equitable and inclusive classroom environments, and how their responses reveal a social movement occurring in education. I examined these research questions through eighteen qualitative interviews and discuss patterns and themes that emerged inductively in the responses. My research also reveals the potential of and opportunities that lie ahead for RJE to contribute to positive social change, and to provide more in-depth, collaborative and consultative education on Indigenous history in Canada.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.483
Threshold uncertainty score0.959

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0330.049
Scholarly communication0.0100.004
Open science0.0020.013
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.073
GPT teacher head0.371
Teacher spread0.297 · 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
Published2022
Admission routes2
Has abstractyes

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