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Transformation & Resistance in the Interfaith Classroom

2021· article· en· W3170704714 on OpenAlexaffabout
Elizabeth Fisher, Amy Panton

Bibliographic record

VenueThe Wabash Center Journal on Teaching · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHumilityResistance (ecology)BuddhismOpenness to experienceContext (archaeology)Spiritual careInterfaith dialogueSociologyPedagogySpiritualityPsychologySocial psychologyIslamTheologyPhilosophyMedicine

Abstract

fetched live from OpenAlex

Although Canada is a religiously plural society, interfaith theological learning remains uncommon. This reflective paper explores the experience of team-teaching at Emmanuel College’s Master of Pastoral Studies Program. The Master of Pastoral Studies is a professional degree with Christian, Muslim, and Buddhist streams that trains students to become chaplains, psycho-spiritual therapists and spiritual care providers in the Canadian context. Using anecdotes from our classroom experiences, this paper reflects on three values central to inter-religious learning: cultivating a vulnerable “open stance” in dialogue, understanding interfaith teaching as active resistance that contributes to spiritual transformation, and placing ourselves as instructors as the “guide within the group.” Interfaith learning calls us to risk and courage, believing that spiritual transformation happens as we encounter difference with openness and humility. As teachers, we model for our students how to engage with one another to build peace in response to individual and societal trauma and discord.

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)0.006
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 score0.094
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0310.024
Scholarly communication0.0110.005
Open science0.0020.013
Research integrity0.0020.008
Insufficient payload (model declined to judge)0.0090.001

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 head0.046
GPT teacher head0.358
Teacher spread0.311 · 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
Published2021
Admission routes2
Has abstractyes

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