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Record W3081937261 · doi:10.1111/1467-9752.12465

‘Mother‐trees’ and Teachers: Connecting My Daughter's Environmental Education with Diana Beresford‐Kroeger's Enduring Wisdom

2020· article· en· W3081937261 on OpenAlexaff
S. B. Heath, Diana Beresford‐Kroeger, Jeff Stickney

Bibliographic record

VenueJournal of Philosophy of Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAttendanceNarrativeDaughterSociologyEnvironmental educationPsychologyPedagogyLiteratureArtLaw

Abstract

fetched live from OpenAlex

How does environmental knowledge move from an expert's books into the life and learning of a small community? Diana Beresford-Kroeger, a renowned author of The Global Forest and Arboretum America, A Philosophy of the Forest, kindly agreed to an interview with Simon Heath, organiser of a rural literary festival. In working with the transcripts, it dawned on Simon Heath (author) and Jeff Stickney (editor) that the educational story here is about community members gathering under a big tent to watch Diana's documentary, ‘The Call of the Forest’, hearing her eye-opening explanation of how trees can positively affect our health and climate. Inspired by seeing a small group of preteen girls fundraising and distributing maple saplings to the 150 people in attendance, the narrative follows the educational path of one of these children, attending an alternative Forest School that allows for discovery approaches to individualised environmental learning and activism. Phenomenologically, the vignette opens to view how words of wisdom, both scientific and spiritual, percolate into the lives of readers and listeners, inspiring both children and adults to begin changing how they live.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.460

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 communication0.0000.001
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 head0.017
GPT teacher head0.264
Teacher spread0.246 · 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 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

Citations2
Published2020
Admission routes1
Has abstractyes

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