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Record W4389203053 · doi:10.1080/13504622.2023.2286929

Navigating eco-anxiety and eco-detachment: educators’ strategies for raising environmental awareness given students’ disconnection from nature

2023· article· en· W4389203053 on OpenAlexafffundabout
Rachael C. Edwards, Brendon M. H. Larson, Susan Clayton

Bibliographic record

VenueEnvironmental Education Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Waterloo
FundersUniversity of WaterlooFaculty of Environment, University of Waterloo
KeywordsDisconnectionEnvironmental educationPsychologyAnxietyNature versus nurtureExperiential learningConsciousness raisingSocial psychologyPedagogySociologyPolitical science

Abstract

fetched live from OpenAlex

Awareness of environmental problems such as climate change can motivate action, but educators debate whether to raise students’ awareness
\ngiven that it may provoke eco-anxiety. We have even less understanding
\nof how these relationships are affected by young people’s growing disconnection from nature. Through 28 semi-structured interviews in Canada and
\nthe United Kingdom, we explore how educators perceive students’ nature
\nconnection and eco-anxiety and how they introduce discussion of environmental problems. Educators frequently observed experiential, cognitive,
\nand emotional indicators of nature disconnection and eco-anxiety, although
\nmany (39%) reported rarely, if ever, witnessing such environmentally related
\ndistress. Educators prioritised improving nature connection over raising
\nawareness of environmental problems. When they discuss these issues
\nwith students, they emphasise hope and encourage pro-environmental
\nbehaviours to avoid eliciting eco-anxiety for those not currently experiencing it, a strategy that is partially inconsistent with literature suggesting
\nsome eco-anxiety can nurture pro-environmental behaviour. Our findings
\nprovide new insights into the challenges that educators face in helping
\ntheir students navigate current environmental trends.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score1.000

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 studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.023
GPT teacher head0.397
Teacher spread0.375 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations30
Published2023
Admission routes3
Has abstractyes

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