Navigating eco-anxiety and eco-detachment: educators’ strategies for raising environmental awareness given students’ disconnection from nature
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".