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Record W108879966 · doi:10.1017/s0814062600000999

Facilitation in Education <i>for</i> the Environment

2005· article· en· W108879966 on OpenAlexfundno aff
Glyn Thomas

Bibliographic record

VenueAustralian Journal of Environmental Education · 2005
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsnot available
FundersGriffith UniversityLakehead University
KeywordsFacilitationExperiential learningRelevance (law)Environmental educationRhetoricPedagogyAction (physics)Project commissioningPsychologyPoliticsSubject (documents)Experiential educationEngineering ethicsSociologyPublishingPolitical scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract The concept of education for the environment is well documented in the literature but is apparently less common in practice. Some of the reasons provided for this rhetoric-reality gap include: the controversial and political nature of the subject, the difficulty of empowering students into meaningful action, the challenge of using innovative methods, the difficulties associated with values education, and deficiencies in teacher preparation. Advocates of education for the environment encourage teachers to use student centred, experiential approaches yet provide little guidance to teachers on how to effectively utilise these approaches in their programs. There is a growing body of literature in the field of facilitation that is directly applicable to student-centred, experiential, environmental education. This paper will seek to demonstrate the relevance of facilitation skills, knowledge and experience to the effective implementation of education for the environment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.006
Scholarly communication0.0030.002
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.018
GPT teacher head0.327
Teacher spread0.309 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations29
Published2005
Admission routes1
Has abstractyes

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