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Record W4402109722 · doi:10.55016/ojs/jet.v53i1.71095

Reconciliatory Pedagogy: Teacher Perspectives and Practices

2020· article· en· W4402109722 on OpenAlexaboutno aff
Clancy Evans, Sarah Charlebois

Bibliographic record

VenueJournal of educational thought. · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Character Development
Canadian institutionsnot available
Fundersnot available
KeywordsPedagogySociologyMathematics educationPsychologyEngineering ethicsEngineering

Abstract

fetched live from OpenAlex

The release of the Canadian Truth and Reconciliation Report in 2015 has prompted research and pedagogy that focuses on Indigenous education, updated teaching standards, and re-designed curriculum; however, experiences of teachers who have been called to act in the service of reconciliation have received minimal research attention. This study found that although the majority of educators believe in the necessity of this work, few are taking steps towards reconciliation through their work as educators. This study utilized an explanatory mixed method approach to gather survey and interview data into the reconciliatory practices, challenges, and successes experienced by grades 4-9 teachers. Overall, findings of this research suggest that educators who are committed to reconciliation, self-reflection, and collaboration are more likely to incorporate aspects of reconciliatory pedagogy into their teaching. This study informs teacher practice, pre-service teacher training, professional development, and ultimately aims to move the dialogue about reconciliation forward within Canadian education.

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)0.017
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.037
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0200.012
Scholarly communication0.0090.006
Open science0.0020.010
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.088
GPT teacher head0.437
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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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