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Record W4405767918 · doi:10.1080/14729679.2024.2444913

Belonging to the living world: The benefits of nature and place-based education for collective wellbeing and eco-social-cultural change

2024· article· en· W4405767918 on OpenAlexaffabout
Daniella Roze des Ordons, Cher Hill

Bibliographic record

VenueJournal of Adventure Education & Outdoor Learning · 2024
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsScholarshipSociologyMainstreamIndigenousOppressionEnvironmental ethicsContext (archaeology)Social sciencePolitical scienceEcologyPolitics

Abstract

fetched live from OpenAlex

In the context of the escalating ecological crisis, which is deeply intertwined with colonial and capitalist structures of oppression, mainstream public schooling in Canada is not supporting the health and wellness of many students or creating the eco-social-cultural changes needed to live within the Earth’s carrying capacity. In this paper, we draw insights from liberation psychology and decolonial scholarship to offer a critical analysis of Western human development theories and suggest alternative wholistic and relational possibilities for education that can help institutions work toward collective wellbeing and community transformation. Guided by Indigenous and place attachment scholarship and through an examination of our own experiences as land-centred educators, we exemplify how attachment theory can be expanded to include the natural world. We propose that relational belonging to the living world and a nature-connected learning community is a crucial developmental need for learners that is foundational for collective wellbeing and eco-social-cultural change.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.010
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0100.023
Scholarly communication0.0060.005
Open science0.0010.011
Research integrity0.0010.004
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 head0.341
Teacher spread0.327 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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