Sustainable tourism development in Niagara
Bibliographic record
Abstract
Purpose The purpose of this paper is to provide insights to the relevant past discussions, theories and projects; and sustainable tourism development in the Niagara region. Design/methodology/approach Each of the key four sections of this paper zooms in to specific areas. Outcomes from elite discussions involving 47 experts are followed by a concise literature review on sustainable tourism. The paper then analyses the concept of economic sustainability and reviews the outcomes from a blueprint for sustainable tourism development. Findings This paper discusses the economic pillar of sustainable tourism by outlining the negative and positive economic effects of the worldwide travel and tourism industry. In addition to reviewing the relative competitiveness of the world's travel destinations; with a focus on Canada's performance, it outlines strategies for Niagara region to enhance its competitiveness to support sustainable tourism. Originality/value In the recent years not much research has been carried out on the topic of sustainable tourism specific to the Niagara region. Therefore, this paper should be useful to a range of tourism stakeholders in Niagara region as well as readers involved in regional tourism development in other parts of the world. The versatility of the four authors – an administrator who chaired the Niagara Gateway Project, an academic researcher who has focused on sustainable tourism for a long period, a partner of a leading consulting firm and an applied researcher with significant international experience, makes the paper interesting.
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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 | 0.000 | 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 | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".