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Record W3136980156 · doi:10.25071/1916-4467.40613

The Noise of Walking

2021· article· en· W3136980156 on OpenAlexaffvenue
Twyla Salm, Lace Marie Brogden

Bibliographic record

VenueJournal of the Canadian Association for Curriculum Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsLaurentian UniversityUniversity of Regina
Fundersnot available
KeywordsAbleismSociologyCurriculumActive listeningAcknowledgementHonourDiversity (politics)Critical theoryDisability studiesAestheticsPedagogyEpistemologyGender studiesComputer scienceCommunicationHistoryAnthropology

Abstract

fetched live from OpenAlex

Walking pedagogies provide opportunities for embracing diversity, at the same time that they honour a relationship with the Earth. As such, they can be used to encourage learners and curriculum makers to attune to their surroundings. Walking and writing together, though from disparate geographical locations, we provoke critical reflections on ableism through walking pedagogies. Inspired by our surroundings, we explicate and query curriculum experiences and the pedagogical reflections that accompany them/us, holding space for (dis)abilities. Co-constructed poetries frame our autoethnographic engagements with theory and practice. We offer two ways walking pedagogies may be engaged to disrupt ableism: walking to “disorient the norm” (Parrey, 2020) in the first instance, and moving as listening in the second. Through these disruptions to ableist discourses, we attend to ongoing circumstances of curriculum-making, attuning to the noise of walking in nature, where some have unrestricted access, some have partial access and some have no access at all.

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)0.010
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 score0.016
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.031
Scholarly communication0.0080.007
Open science0.0010.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.020
GPT teacher head0.314
Teacher spread0.293 · 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

Explore more

Same venueJournal of the Canadian Association for Curriculum StudiesSame topicIndigenous and Place-Based EducationFrench-language works237,207