‘Made up’ and evolving – or already set in stone? Producing geotourism in the Niagara Region
Bibliographic record
Abstract
What are the origins of niche tourism? The making of a form of niche tourism is explained by more than the economic forces of supply and demand and socio-demographic factors. An integrated web of classificatory practices, people, institutions, knowledge, experts, and place-based factors is involved. This web, derived from the ideas of philosopher Ian Hacking, constitutes a field of niche tourism production. Geotourism and geotourists appear as subjects of interest that become economically useful, thus inviting business-related interventions. Through the field of niche tourism production, geotourism in the Niagara Region becomes an analysable phenomenon; it is created and cultivated as opposed to being purely a consequence of economic forces and socio-demographic factors. The continued emergence of different forms of niche tourism warrants research that explores the origins of specific niches, including those currently taking shape. This paper proposes a conceptual framework that articulates previously unacknowledged dimensions of the creation of niche tourism. A range of practices and phenomena as well as human and institutional actors, as components of an interwoven field of production, play an underappreciated role constituting a form of niche tourism.
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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 | 0.001 |
| 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".