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Public pedagogies of arts-based environmental learning and education for adults

2017· article· en· W2604654563 on OpenAlexaffabout
Pierre Walter, Allison Earl

Bibliographic record

VenueEuropean Journal for Research on the Education and Learning of Adults · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsScholarshipThe artsSociologyUrbanismPedagogyTypologyEnvironmental educationDemocracyArts in educationVisual arts educationScholarship of Teaching and LearningTeaching methodPolitical scienceVisual artsArchitectureAnthropologyArt

Abstract

fetched live from OpenAlex

This paper examines how current theorizing on public pedagogy can be used to understand scholarship on creative, arts-based pedagogies in informal environmental education for adults. In particular, the study applies Biestas (2012, 2014) typology of public pedagogies to three bodies of literature: arts-based adult learning and education in the environmental movement, eco-art, and Tactical Urbanism, respectively. Each of these is about public art, displayed or performed in public spaces, and connected to environmental learning and education. The scholarship reviewed came mostly from Canada and Australia. In the public, democratic spaces of these countries, we found that arts in the environmental movement and eco-art could be characterized by Biestas pedagogy of the public, and partially by a pedagogy in the interest of publicness. The performance of Tactical Urbanism corresponded most closely to pedagogy in the interest of publicness. The paper concludes with a discussion of directions for further theorizing and research on public pedagogy and arts-based environmental learning and education for adults.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.230
GPT teacher head0.421
Teacher spread0.191 · 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.

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

Citations20
Published2017
Admission routes2
Has abstractyes

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