MétaCan
Menu
Back to cohort
Record W3135927894 · doi:10.25071/1916-4467.40642

Walking the Talk: Three Language Educators Engage in a Walking-Based Art Inquiry for Anti-Racist Education

2021· article· en· W3135927894 on OpenAlexaffvenueabout
Adriana Oniță, Lébassé Guéladé-Yaï, Lucie Wallace

Bibliographic record

VenueJournal of the Canadian Association for Curriculum Studies · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCurriculumOppressionSociologyVisual artsThe artsVisual arts educationSituatedLanguage artsPoetryPedagogyAestheticsArtPoliticsLawLiteratureComputer sciencePolitical science

Abstract

fetched live from OpenAlex

As language and art educators committed to anti-oppression, we sought to explore how walking and art-making help us reflect, inquire, create, and act, upon new understandings of anti-racist education. Living in three different cities (Edmonton, Vancouver, and Palermo), we collaborated on a walking-based art inquiry for ten weeks in the summer of 2020, combining walking, art-making (photography, painting, mixed-media collage, screenprinting, and poetry), reflecting, and discussing. We were curious to investigate, both individually and collaboratively, what an anti-racist curriculum looks and feels like to us, and what walking and art-making might do in the process of learning and teaching. We situated our project in an arts-based research paradigm (Conrad & Beck, 2015), and we were inspired by Feinberg’s (2016) walking-based pedagogy and Judson’s (2018) walking curriculum. This article presents artistic experiments we created, as well as curricular insights that emerged from our process, for example, that walking and art may serve as dehabituating forces to help us openly feel, question, protest, and reimagine education, from intersecting perspectives of race and language.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.299
Teacher spread0.267 · 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 teacher head, 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

Citations2
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueJournal of the Canadian Association for Curriculum StudiesSame topicArt Education and DevelopmentFrench-language works237,207