Bibliographic record
Abstract
Tourism is considered as one of the largest and fastest developing sectors of the world. Its high growth and development rates bring considerable volumes of foreign currency inflows, infrastructure development, employment generation, regional development, economic multiplier effects and introduction between host and guest peoples experience actively affect various sectors of society, which can positively affected to the social and economic development. However the tourism also generates a number of other negative socio-economic impacts on local communities. This study considers the mainly socio-economic impacts on local community trough tourism development in Kasara. The study is focused to identify the social and economic impacts on local community and their perception towards the tourism. The study is adapted the qualitative methodology and the data is generated through primary and secondary source, personal interviews, discussions and social interaction. The study identified that community has developed positive attitudes about the tourism development and the community is accepted tourism as a major income source through active and passive participations. As usually the tourism has generated both positive and negative impacts in the society. However, the negative impacts are at a minimum level when compare with the positive impacts. The social tradition, culture and human behaviour exchange between host guest interactions. The tourism revitalizes the culture and sometime declines the culture of the host country. The tourism helps to develop the livelihood of the people and can earn money from the different business and cultural activities. Community empowerment and their capacity building are highly important in this context.
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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 | 0.001 | 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 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".