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Record W976182556 · doi:10.1163/9789460911613_013

Environmental Learning and Agency in Diverse Educational and Cultural Contexts

2010· book-chapter· en· W976182556 on OpenAlexaboutno aff
Robert B. Stevenson, Carolyn Stirling

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)SociologySocial science

Abstract

fetched live from OpenAlex

[Extract] Environmental education is concerned with engaging learners in examining the relationship between humans and nature, or stated another way, between society and its social systems, on the one hand, and the biophysical or non-human natural environment and its ecological systems, on the other. And as Scott and Gough (2003) argue: learning is central to the relationship between society and nature. People learn, organizations learn and, in a sense, the environment learns as nature responds to the results of human and activity. (p. 8) These authors further characterize environmental as learning that accrues from an engagement with the environment or environmental ideas (p. 14). Furthermore, with the emergence over the last 20 years of the language of sustainable development and sustainability in international policy, they argue that sustainable development itself is a process through which we need to learn to build our capacity to live more sustainably (Scott & Gough, 2003). Thus, is viewed as central to creating a more environmentally sustainable, and, I would add, more socially just, future. In other words, is involved in improving both the condition of the planet and the human condition. The previous chapters in this book examine environmental in a full range of educational settings in diverse international contexts, including Canada, Denmark, the Netherlands, South Africa, Sweden, the United Kingdom and the United States. The case studies from these different educational and cultural contexts illuminate the challenges of engaging children and adults in meaningful regarding the complexity of environmental issues, as well as document and offer insights into the promising possibilities of such engagement.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.951

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0500.000

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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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 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

Citations18
Published2010
Admission routes1
Has abstractyes

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