Agritourism-A Sustainable Approach to the Development of Rural Settlements in Jordan: Al-Baqura Village as a Case Study
Bibliographic record
Abstract
Agritourism is gaining growing recognition in both developed and developing countries. In developing countries, it is considered as an instrument, not only for sustainable rural development but also for local community poverty alleviation. Al-Baqura is an important agricultural village in the north of Jordan. In 2019, Jordan retrieved control over it after 25 years of leasing to external investors. Thereupon, the Jordanian government should encourage investments in this area and improve its agricultural production in terms of quality and quantity. The objectives of this study were to explore the perspectives of local farmers on the launch of agritourism in this village and to identify the variables that affect farmers' motives for engagement in agritourism activities in their locality. In addition, the study aimed at determining the agritourism-associated difficulties faced by the residents who seek to boost their livelihoods through tourism. The study followed the quantitative research approach and used a questionnaire as the data collection tool in a survey of 163 residents of Al-Baqura village. The results of the analysis uncovered a high potential for economic, environmental, and socio-cultural benefits of agritourism in this village. In particular, it will empower the women to improve their social status in society, provide the rural population with increased revenue and new job opportunities, and improve the quality of the environment. However, for agritourism development in this area, the government should support the local families and help them in establishing and operating tourism enterprises.
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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 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".