Does ecotourism contribute to sustainable destination development, or is it just a marketing hoax? Analyzing twenty-five years contested journey of ecotourism through a meta-analysis of tourism journal publications
Bibliographic record
Abstract
Conducting a periodical systematic review on a given field of study enables to comprehend the conceptual development of a discipline. A decade has passed since the last in-depth systematic review on contemporary ecotourism research has been published. This study is, therefore, executed to systematically analyze ecotourism research articles published in the previous twenty-five years and thereby to reassess the past, understand the present and envisage the future of ecotourism development. 470 articles published in nine top-tier tourism journals are screened and analyzed. Thematic and summative content analyses are employed to examine the contents of each publication. The findings highlight that over the years, researchers have examined myriads of ecotourism research themes. Despite fluctuations over the years, the overall publication trend shows growth. Most ecotourism studies are conducted in developing countries, with Asia taking the lead followed by Africa and Latin America. However, in terms of researchers’ domicile, the USA becomes the first followed by Australia, the UK, and Canada. Despite modest successes, overall, the contribution of ecotourism towards sustainable destination development remains indiscernible. The current study provides up-to-date insight into the ecotourism literature by highlighting the main themes and trends of ecotourism research over the last twenty-five years. Research findings also enhance our understanding of the evolution of ecotourism research and ignite further study in ecotourism by suggesting issues that merit rigorous investigation.
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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 | 0.044 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.013 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".