Ecological footprint analysis of tourism management in rural areas
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
Ecological footprint analysis is one of the most useful models for the environmental impact assessment of human activities. This research aimed to estimate the environmental impacts of the tourism industry on Hosainabad village, Kurdistan Province, Iran by using the ecological footprint model. A descriptive-analytical method is used based on documentary library studies as well as field surveys. The statistical population for this study is the number of tourists who visited Hosainabad village in 2018. The findings show that the tourism ecological footprint in Hosainabad village in food, transportation, heating, water, electricity, and waste generation groups was 0.994 hectares) per capita). Comparing this amount with its surrounding spaces indicates that the tourism industry in Hosainabad relies on an area beyond this village to meet its biological needs and environmental sustainability. Findings suggest that decision-makers must pay enough attention to tourists’ activities in small areas in order to prevent further environmental disruption.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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