Ecotourism’s Impact on Ethnic Groups and Households near Chitwan National Park, Nepal
Bibliographic record
Abstract
The Chitwan National Park (CNP) is renowned as a premier attraction in Nepal. This study surveyed the ethnic communities and households living in the buffer zone (BZ) proximate to the CNP, where ecotourism has been strategically introduced to provide an alternative means of livelihood to the locals and to enhance biodiversity conservation. This study examined to what extent these households have economically benefited from local ecotourism activities as well as their perceptions of ecotourism. A structured questionnaire was used to collect data, surveying 145 Kumroj and Amaltari village households using a stratified random sampling technique. The findings indicated that similar ecotourism activities were taking place in both sites. We found that only certain households benefited directly, and that it was mostly the socioeconomically disadvantaged households that missed out on the livelihood opportunities provided by ecotourism. Further, it was revealed that the socio-economically disadvantaged locals still illegally extracted/sold forest products. However, such individuals also acknowledged that ecotourism has increased employment, social development, and forest conservation, and they desired to participate in ecotourism activities. This research can help policymakers better understand the gaps in their policies and restructure them to level the ecotourism playing field for all ethnic groups and economic levels (e.g., landowners versus non-landowners). This study recommends that policymakers rethink and reframe policies to protect the interests of communities living in the BZs of national parks, especially low-income households and/or locals who are disadvantaged because they do not have land or facilities to conduct ecotourism activities.
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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 | 0.000 | 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 | 0.000 |
| 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 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".