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Record W2169397613

Cultivating and Reflecting on Intergenerational Environmental Education on the Farm

2009· article· en· W2169397613 on OpenAlexvenueno aff
Jolie Mayer‐Smith, Oksana Bartosh, Linda Peterat

Bibliographic record

VenueCanadian journal of environmental education · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental educationEnvironmental stewardshipEnvironmental adult educationStewardship (theology)Environmental consciousnessWork (physics)Consciousness raisingSociologyConsciousnessAgriculturePedagogyEnvironmental resource managementPsychologyPolitical scienceEcologyEngineeringEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

Based on the idea that eating is an environmental act, we designed an environmental education project where elementary school children and community elders work as partners to raise food crops on an urban organic farm. Our goal was to illustrate how eco-philosophies could be translated into educational programs that foster environmental consciousness and care, and to further the critical and systematic examination of environmental education initiatives. In this article we draw on six years of empirical data and self-examination to present our learning about environmental education in practice. We discuss three iterations of our project to illustrate the ways in which our thinking about the practice of environmental education has evolved along with our efforts to advance environmental understanding and stewardship through intergenerational farming.

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)0.009
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.019
Scholarly communication0.0050.004
Open science0.0010.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.274
Teacher spread0.261 · 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 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

Citations29
Published2009
Admission routes1
Has abstractyes

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