Trash in the bin, to a cleaner scene we cling: a mixed method approach on tourists’ binning behavior at two spiritual destinations
Bibliographic record
Abstract
This study investigates tourists’ binning behavior and its importance for the environmental sustainability of tourist destinations, a topic currently understudied in academic research. Through the lens of behavioral reasoning theory (BRT), it explores the factors influencing tourists’ decisions to dispose of waste properly, employing a mixed-methods approach. Initial qualitative research at the Indian spiritual sites of Rishikesh and Haridwar identifies key motivators and barriers to binning behavior. These findings are then integrated into the BRT framework and confirmed via quantitative analysis using PLS-SEM. Results show that the perceived sacredness of a site and awareness of environmental risks encourage proper waste disposal, whereas perceptions of inefficacy, lack of facilities, and established habits deter it. The study underscores the role of environmental values in promoting responsible waste disposal, offering practical suggestions for enhancing sustainable tourism through targeted interventions in spiritual tourism settings.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".