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Record W2097112942

EarthShapes: Potential for Place-based Teacher Learning between the Virtual and the Actual

2009· article· en· W2097112942 on OpenAlexvenueno aff
Valerie Triggs

Bibliographic record

VenueCanadian journal of environmental education · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Environments and Student Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsAnticipation (artificial intelligence)Futures contractAction (physics)Experiential learningStudioAction researchService (business)Computer scienceSociologyPedagogyMathematics educationPsychologyArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

This contribution investigates a recent research project involving in-service teacher learning as experienced through an online/offline art studio in which common experiences of relationships to particular local landforms generate imaginative and collaborative processes and practices of teaching and learning. EarthShapes Studio is both a pedagogical strategy and a methodological tool for teacher learning that acknowledges an emerging view that the tangible, material effects of relating to places and others are central to learning and can generate anticipation of alternative futures. This paper analyzes EarthShapes through Mellet-d’Huart’s (2006) model of (en)action which is based on the work of Francisco Varela and includes three co-existing and overlapping spheres of potentialization, virtualization, and actualization.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.267
Teacher spread0.258 · 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 designObservational
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

Citations1
Published2009
Admission routes1
Has abstractyes

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