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Record W7108320694 · doi:10.1080/13549839.2025.2596719

Climate moves: reaching for threshold knowledge one walk at a time

2025· article· en· W7108320694 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLocal Environment · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsClimate changeKnowledge productionProduction (economics)Climate system

Abstract

fetched live from OpenAlex

Walking the Talk: Climate Moves is an interdisciplinary, intergenerational, intercultural collaboration of scholars and community stakeholders in Canada and the US that leverages walking as relational research and pedagogical method for action on climate. Walking the Talk turns to walking as a repeated, durational, embodied mode of learning, to help participants attune to local ecologies and reach for threshold knowledge of the interdependence between human, more-than-human, and ecosystem flourishing. This article, written midway through the pilot year, situates and reflects on learnings so far. Findings from the Kansas mirror lab show that regular walking cultivates relational connections, multispecies awareness, and embodied threshold concepts such as interdependence, with participants reporting increased ecological attunement, wellbeing, and recognition of walking itself as climate action. These insights suggest that walking methodologies are accessible, locally adaptable tools for cultural and organisational shifts towards climate justice.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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