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Record W4411475779 · doi:10.25071/1916-4467.40810

The Transeunt Listener: Towards Futurities of Re-learning in Truth and Reconciliation Curriculum and Teacher Education

2025· article· en· W4411475779 on OpenAlexaffvenue
Patrick Phillips

Bibliographic record

VenueJournal of the Canadian Association for Curriculum Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCurriculumSituatedReading (process)SociologyPilgrimPedagogyConsciousnessPost truthPower (physics)EpistemologyPsychologyPhilosophyLawLinguisticsPolitical science

Abstract

fetched live from OpenAlex

What does it mean to read, write and act towards reconciliation in curriculum and teacher education? To answer this question, I perform a situated literature review of Truth and Reconciliation teacher education research. I borrow from Lisa Farley’s (2010) concept of the reluctant pilgrim. While Farley reflects on a physical journey to understand how belief can withstand historical loss and immersion in ongoing systems of colonial power, I engage with her concept psychically; I attend to the words and listen for the implied hopes of the authors I read. Also attentive to my own beliefs and hopes as I read them, I become what I term a transeunt listener. I discuss how I became a transeunt listener through a form of reading-as-encounter and how it enabled me to understand how teacher education might address what I see as three tensions in truth and reconciliation teacher education discourse: 1) belonging; 2) disruption of settler consciousness; and 3) an expanded ethical capacity in teachers and curriculum theorists.

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)0.031
metaresearch head score (Gemma)0.046
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: none
Teacher disagreement score0.990
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.046
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0100.047
Scholarly communication0.0220.033
Open science0.0020.011
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0040.001

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 head0.038
GPT teacher head0.356
Teacher spread0.318 · 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 routes2
Has abstractyes

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