Eco-Anxiety: A Cascade of Fundamental Existential Anxieties
Bibliographic record
Abstract
Eco-anxiety is the experience of persistent feelings of anxiety regarding degradation of our natural environment. Building upon the work of existential psychologists and our own Eco-Existential Positive Psychology framework, we consider how eco-anxiety engenders the existential anxieties of identity, happiness, meaning, death, freedom, and isolation. Regarding identity, ever-shrinking biodiversity and the threat this poses to the existence of our species has made us contemplate our nonbeing, and with that our identity as beings. Our happiness, too, is ill-affected by reduced opportunities to engage with thriving ecosystems as a result of climate crises. Our sense of coherence, connectedness, and continuity—and therefore, meaning in life—is diminished as landscapes and ecosystems that we have become attached to over time become degraded and disrupted. Mounting environmental crises conjure fears of death, including the possible mortality of our human species as a collective. While nature has long been associated with freedom of human behavior and spirit, a broken human–nature relationship leads to an infringement on our autonomy. Finally, the experience of eco-anxiety appears to be a solitary one, heightening our sense of isolation. We discuss implications of these existential threats, emphasizing that ecoanxiety is something with which we need to cope and live.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".