Exploring a Momentary Eco-Anxiety Induction Technique Using a Mixed-Methods Approach
Bibliographic record
Abstract
Concern surrounding climate change and other global environmental issues is very high.For many people, this means a subsequent rise in feelings of eco-anxiety.Presently, little research methodology surrounding eco-anxiety is aimed at investigating momentary feelings of ecoanxiety.This study at hand empirically tested a state eco-anxiety induction technique and quantitatively and qualitatively explored self-reported coping techniques associated with ecoanxiety.Three hundred ninety-three MTurk participants watched one of seven randomly assigned videos intended to evoke feelings of eco-anxiety.A mixed ANOVA revealed successful induction of increased state eco-anxiety at post-test compared to pre-test.Thematic analyses revealed coping themes, with top suggestions being pro-environmental behaviour, use of informational support, emotional or social support, and self-distraction.The findings of this study will aid in future research concerned with momentary feelings of eco-anxiety, and how it relates to coping behaviours.iii Dedication To my late Uncle Derek, who has inspired me to approach the field of Psychology with compassion and curiosity.
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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 | 0.022 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".