Collective actions and crisis adaptation of a rural tourism community
Bibliographic record
Abstract
Community resilience is crucial for tourism communities to adapt successfully to crises. Communities can address challenges through collective actions that individual households cannot tackle effectively. Current literature emphasizes the importance of building household resilience and destination resilience, yet there is limited empirical discussion on resilience at the community level. Through a qualitative case study, we explore the relationship between collective agency and community resilience practices in a rural tourism community in southwest China. We propose a conceptual framework of tourism community resilience, which includes three key components: community resources, community competence, and social structure. This framework illustrates how community resource mobilization and allocation, community collective action and decision making, and social relationships within and beyond the community interact, thereby influencing the outcomes of tourism communities’ adaptation to external shocks. Our work enriches the understanding of tourism resilience at the community level and adds detailed empirical examples to a literature that has so far been predominantly conceptual.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".