Bibliographic record
Abstract
This chapter is composed of excerpts from Indigenous Tourism Association of Canada (ITAC) publications with permission from ITAC. ITAC is not alone in representing Indigenous tourism operators, but it provides a good example of what can be achieved by cooperation and integration amongst Indigenous peoples at a national level. It provides advice, organization, and assistance to Indigenous groups involved in tourism to enable them to survive in tourism in Canada and appropriately represent Indigenous culture. ITAC works with national and provincial governments in the formulation of policies related to Indigenous tourism development and in the development of programmes to assist the growth of Indigenous tourism and its recovery after the COVID-19 pandemic. It provides definitions of the terms involved, guarantees authenticity and quality to tourists and runs programmes to improve business efficiency and increase benefits to Indigenous communities. Except where shown in Italics, the following text has been drawn from ITAC’s publications and websites in 2023. Some changes in the order of material only have been made.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.113 | 0.025 |
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".