Understanding stakeholder perceptions of environmental justice: a study of tourism in the Erhai Lake basin, Yunnan province, China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Environmental justice is an important component of sustainable tourism, but stakeholder perspectives related to environmental justice may vary. Using Q-methodology, we investigated different stakeholder perceptions related to environmental justice within the context of tourism and ecological restoration. Specifically, in the Erhai Lake basin, China, we explore perspectives around an ecological restoration effort that included the government mandated closure of 1900 establishments (inns and restaurants) in response to environmental degradation. We identify and explore four environmental justice perspectives: the togetherness, protection, operator loss, and local loss perspectives. These four perspectives are contextualized within three dimensions of environmental justice (i.e., distribution, recognition, and participation). Our findings highlight differing views related to who is affected most by the inn closures (e.g., future generations, local residents, inn owners), and general consensus related to the outcomes of the process being more important than the process itself. Finally, we discuss potential reasons for these differing perspectives and recommend ways to improve environmental justice among different stakeholders. This research can facilitate sustainable development of tourism by highlighting the facets of ecological restoration policy implementation most important to stakeholders, including recognition of diverse stakeholder concerns and identities, clear and well supported rationale for policy design, and increased equity in the distribution of costs and benefits of policies.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it