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Record W2899404720 · doi:10.1017/aee.2018.34

Dancing Teachers Into Being With a Garden, or How to Swing or Parkour the Strict Grid of Schooling

2018· article· en· W2899404720 on OpenAlexaff
Susan Gerofsky, Julia Ostertag

Bibliographic record

VenueAustralian Journal of Environmental Education · 2018
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsParallelsSociologySwingGridEnlightenmentPerformative utteranceSpace (punctuation)AestheticsHegemonyEmbodied cognitionEnthusiasmVisual artsEpistemologyPsychologyComputer scienceArtPoliticsSocial psychologyEngineeringLawPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Abstract The co-authors, collaborators in garden-based teacher education, question the hegemony of grids in Western time, space and relationship structures in education, while also delving into our own complicity and entanglement with these grids. We ask: (1) Can we reject the grid in environmental education and in garden-based learning when it is an intimate part of our way of being in the world? (2) Can we be teachers who are at once within and not-within the regime of the Western Enlightenment/Modernist grid? (3) How can we take a ludic approach to the grid? Can we ‘swing’ and ‘parkour’ the strict grid of schooling? Pleasures and failures of the grid and experiences of alternatives to the grid are documented and exemplified through stories from garden-based teacher education. Considering parallels with principles of the alter-global movement and with the performative, embodied practices of swing dance, parkour and clowning, we meditate on becoming ecological teachers together beside the grid — neither within nor without it, but with a deep awareness of its presence and structure. In uncertain, unchanging times, we want to take a playful, artistic approach to the old certainties and structures, swinging and parkouring from them rather than accepting or rejecting binary formulations.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.329
Teacher spread0.310 · 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 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
Published2018
Admission routes1
Has abstractyes

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