Strategies for Organization and Development of Tourism Function in Rural Areas Case Study: Villages of Qom Province, Iran
Bibliographic record
Abstract
Regarding its appeals and capacities, tourism function of rural areas in Qom province has not adequately played an effective role in advancing rural sustainable development. Therefore, the current research attempts at identifying and preparing organization and development strategies for tourism function in rural areas of Qom province. Research method is descriptive-analytical and it is applied in terms of its content. The present study aims at searching for organization and development strategies and approaches for tourism function in rural areas of Qom province with special emphasis on existent potentials and restrictions. For so doing, using SWOT technique, strengths, weaknesses, opportunities and threats related to tourism function of rural areas in Qom province have been investigated. Findings indicate that 12 internal strengths and 12 internal weaknesses as well as 10 external opportunities and 9 external threats influence greatly on tourism function of rural areas. In the research presented here, research sample consists of 145 managers and experts of Qom province. Then, their ideas are received and recorded. After that, using one sample t-test, the influence of those two environments on organization and development of rural regions’ tourism function is analyzed. Results obtained from findings analysis reveal that both components of external environment and internal environment do greatly influence on organization and development of tourism function. Compatible with analysis content, efficient strategies are derived and ranked. Ultimately, WO strategies are considered as first priority for planning and SO strategies as second one.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".