Nature-based awe among water professionals and its influence on workplace decision-making
Bibliographic record
Abstract
Time spent in nature is restorative for both our physical and mental health. Awe is frequently evoked by nature experiences and increasingly linked to pro-environmental behaviours. Yet, research into awe’s influence on environmental managers specifically is sparse. Through a survey-based empirical study, we examined water professionals’ experiences in nature, frequency and characteristics of their nature-based awe experiences (e.g., awe experiences during professional vs. personal hours; ranking of awe-inspiring nature images), and awe’s influence on their workplace decision-making. Participants indicated greatest awe related to water-based scenes and activities. Related to professional decisions, participants reported nature-based awe most influenced their decisions around protecting the natural environment. Results underscored the significance of nature-centric awe in shaping water professionals' decisions. By recognizing the profound influence of nature-based awe on individuals, particularly within professional contexts, this study contributes to a broader understanding of how awe-inspiring experiences can promote environmental stewardship in contemporary society.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".