Tourism and Quebec’s Cree Community of Waskaganish: Navigating the Past, Embracing the Present, and Shaping the Future
Bibliographic record
Abstract
Summary The Cree community of Waskaganish is an Indigenous community on the James Bay in Northern Quebec. Waskaganish is in an early stage of tourism development and currently encounters a relatively limited number of visitors who participate in a variety of informal activities, including traditional cultural Cree activities such as fishing, hunting, and trapping. Current legislation restricts cultural practices such as fishing and hunting to members of the Cree Nation. However, locals informally involve visitors in these activities, which while illegal, is unenforced. A recent Cree Nation Governance Agreement was passed in 2017 enabling the Cree Nation Government to pass laws and regulations that supersede federal or provincial laws in designated category 1A lands. The Cree Nation now has the opportunity to consider modifying these regulations to allow for formal tourism opportunities which could benefit the local economy and protect and showcase the local culture and environment. This study explores the preparedness and potential for legal changes that support formalized tourism in Waskaganish and finds that tourism may be well-positioned to support the preservation of the local environment, culture, and identity while offering economic opportunities in Waskaganish and other neighboring Indigenous communities. Information © The Authors 2025
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.010 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".