MétaCan
Menu
Back to cohort
Record W4407649137 · doi:10.1079/tourism.2025.0009

Tourism and Quebec’s Cree Community of Waskaganish: Navigating the Past, Embracing the Present, and Shaping the Future

2025· article· en· W4407649137 on OpenAlexaffabout
Jonathan Blueboy, Zainub Ibrahim

Bibliographic record

VenueTourism Cases · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsAlgonquin College
Fundersnot available
KeywordsTourismPolitical scienceGeographyRegional scienceEconomic geographyArchaeology

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0230.010
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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.

Opus teacher head0.042
GPT teacher head0.366
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueTourism CasesSame topicIndigenous Studies and EcologyFrench-language works237,207