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Record W2750177578 · doi:10.18432/r2s91k

Review of “Arts-based Contemplative Practices in Education”: 2017 Canadian Society for Studies in Education ARTS Pre-conference

2017· article· en· W2750177578 on OpenAlexaffvenueabout
Pamela Richardson, Kathryn Ricketts

Bibliographic record

VenueArt/Research International A Transdisciplinary Journal · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsUniversity of ReginaRoyal Roads University
Fundersnot available
KeywordsContemplationThe artsTheme (computing)Arts in educationSociologySession (web analytics)Space (punctuation)Visual artsPoetryVisual arts educationMedia studiesLibrary sciencePedagogyArtLiteratureEpistemology

Abstract

fetched live from OpenAlex

This review is a poetic and photographic response to a pre-conference session convened in May 2017 by the Arts Researchers and Teachers Society (ARTS) of the Canadian Society for Studies in Education, and organized by Susan Walsh, Barbara Bickel, Carl Leggo, and Diane Conrad. The gathering took place in Toronto, Canada on the traditional territory of the Haudenosaunee, and of the Mississaugas of the New Credit First Nation. The theme of the pre-conference was arts-based contemplative practices in education. The day offered a collaborative space for learning and co-creation as a community of practice supported by a hospitable and responsive design. This enabled movement away from traditional vertical hierarchies of knowledge dissemination towards more lateral exchanges and emergent learning structures.

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)0.009
metaresearch head score (Gemma)0.027
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: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0120.021
Science and technology studies0.0030.003
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.485
GPT teacher head0.556
Teacher spread0.070 · 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
GenreReview

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
Published2017
Admission routes3
Has abstractyes

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