Promoting sustainable festival events tourism: a case study of Lamu Kenya
Bibliographic record
Abstract
Purpose Tourism has been a key force in promoting festival growth and expansion. Towns, villages and cities are increasingly keen to share their culture, environment and spending opportunities with visitors by the promotion of festivals. One such festival is held annually in Lamu Old Town, a world heritage site in Kenya. The purpose of the paper is to highlight the importance of hosting sustainable events in Kenya. Design/methodology/approach The subject scope is on maintaining sustainable events within local communities with an aim of improving the local economy. Findings Results suggest that although festivals may have the potential to provide opportunities for sustainable local economic development, such opportunities frequently remain unexploited. For these reasons, festivals' engagement with tourism forces in Lamu need to be carefully managed, both in the interests of sustaining festivals and of promoting sustainable approaches to tourism development. Practical implications In addition to their cultural and social values, cultural festivals have emerged as an instrument for tourism development, tourism seasonality expansion, city image improvement and boosting regional economies. Therefore, the implications will be to invest in festivals development and community engagement and present the tourist with authentic experiences. Originality/value This article is valuable to policy makers as not enough research has been done on the importance of this festival and the need to provide a significant role to the local people in Lamu in communicating their identity, history and cultural practices.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".