Rituals expressing gratitude to nature and pro-environmentalism : a multiple case study of long-term participation
Bibliographic record
Abstract
Since time immemorial, many traditional and Indigenous cultures across the globe have ritually expressed gratitude to the natural world. Within Western academic thought, the study of gratitude is an emerging field that has not extensively considered expressing gratitude towards nature. The purpose of this research was to investigate experiences of practitioners of rituals that express gratitude to nature across different cultures to learn how such rituals affect their values and behaviour toward the natural world and each other. An exploratory case study was conducted gathering phenomenological data from nine long-term practitioners of Japanese Shinto, Korean Mugyo, and Six Nations Longhouse rituals. A unique approach to data analysis was undertaken using both hermeneutic-phenomenological analysis and a comparative case study analysis. The findings of this exploratory study indicate that participation in rituals expressing gratitude to nature may influence pro-environmental values but does not appear to have to be associated with pro-environmental behaviours. This study found that rituals in which gratitude is expressed to nature effectively act to preserve and strengthen connection to the ritual community and culture of those who practice them. This research provides insight into how to conduct further research in cross-cultural, multilingual studies of ritual in contemporary contexts. Future research possibilities arising from this study include the study of new practices that may be developed to foster connection between participation in rituals that express gratitude to nature and pro-environmental behaviour. Key words: ritual, gratitude, pro-environmental values, pro-environmental behaviour, Indigenous, participation.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".