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Record W3002594143 · doi:10.1080/13504622.2020.1717448

Encounters with suchness: contemplative wonder in environmental education

2020· article· en· W3002594143 on OpenAlexaff
David Chang

Bibliographic record

VenueEnvironmental Education Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsWonderCuriosityAestheticsReverenceAnthropocentrismCLARITYEnvironmental educationNatural (archaeology)ContemplationEnvironmental ethicsPsychologySociologyEpistemologyPedagogySocial psychologyPhilosophyHistory

Abstract

fetched live from OpenAlex

Much of the current literature on environmental education links the outdoors with experiences of wonder, which connotes a range of experiences from fascination to curiosity, excitement to delight. Most of these associations fall within a nexus of positive valences that render the discourse of wonder in glowing light. However, pedagogical recommendations that unfurl from ‘wonder’ can often reproduce anthropocentric attitudes toward the natural world. In addition to the positive vision of environmental education under the guise of wonder, other modes of attention and interaction can help educators broaden students’ engagement with wild places. This paper explores the Buddhist concept of suchness, a raw encounter with phenomena in the stark clarity of awareness. The development of such awareness can potentially generate a deep respect for place, a reverence for life, and a recognition of subtleties in nature that often escape notice. The author posits suchness as a concept that complements existing practices that cultivate wonder, and points to pedagogical practices that refine students’ awareness.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.998

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.044
GPT teacher head0.369
Teacher spread0.325 · 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 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

Citations17
Published2020
Admission routes1
Has abstractyes

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