Studying the Economic, Socio-Cultural and Environmental Outcomes of Ecotourism on Local Communities Using SEM Model
Bibliographic record
Abstract
In this paper the ecotourism development (ED) outcomes on economic (ECE), socio-cultural (SCE) and environmental (ENE) effects on local communities was studied. For this purpose, the structural equation model (SEM) model was used. For empirical data and case study, the Kang and Noghondar villages of Khorasan-e-Razavi province of Iran were selected. Results indicated that ecotourism development (ED) has positive significant effect at 1% on economic effects (ECE) of Kang and Noghondar villages. Also, if ED of Kang and Noghondar villages improve 1 unit, ECE will increase equal to 0.81 and 0.83 units, respectively. In addition, ecotourism development (ED) has negative significant effect at 1% on environmental effects (ENE) of Kang and Noghondar villages. Also, if ED of Kang and Noghondar villages improve 1 unit, ENE will decrease equal to 0.67, and 0.69 units, respectively. Finally, ecotourism development (ED) has positive significant effect at 1% on socio-cultural effects (SCE) of Kang and Noghondar villages. Also, if ED of Kang and Noghondar villages improve 1 unit, SCE will decrease increase to 0.74 and 0.71 units, respectively.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".