Internet-based Ecotourism Marketing: Evaluating Canadian Sensitivity to Ecotourism Tenets
Bibliographic record
Abstract
The internet is providing a new and important electronic commerce medium for tourism. In the ecotourism case, it provides the primary mechanism for promoting ecotourism opportunities (providers) and for researching and planning ecotourism experiences (consumers). As a matter of concern, the literature establishes that the congruency of traditional ecotourism marketing with established ecotourism tenets is limited. Ecotourism may be on a ‘precarious course’ whereby the natural environment, long-term sustainability and legitimacy of the industry are at risk. The scale of the internet and its use to promote ‘disingenuous’ ecotourism products may accelerate negative outcomes. However, our understanding of internet-based ecotourism marketing – both delivery and outcomes – is limited. Through the application of a content analysis framework, this paper assesses the congruency of internet-based ecotourism marketing with ecotourism tenets. The study finds the use of the term ‘ecotourism’ and its tenets to market tourism experiences is a well-established internet-based marketing activity, and congruency between ecotourism tenets and ecotourism marketing messages is contentious amongst the Canadian sample providers. It supports antecedent claims that disingenuous ecotourism marketing is the norm, not the exception. Recommendations for improving marketing success, long-term sustainability of the industry and delivery of ‘genuine’ ecotourism products are presented.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".