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Record W7076053154 · doi:10.18063/lne.v3i4.937

Aitchelitz Band Tourism Development Proposal For Aitchelitz Band Council

2025· article· en· W7076053154 on OpenAlexaffabout

Bibliographic record

VenueLecture Notes in Education Arts Management and Social Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Resources Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTourismSustainabilityRevenueWorkforceResource (disambiguation)AutonomyCompetition (biology)

Abstract

fetched live from OpenAlex

This proposal, developed in collaboration with the Aitchelitz Band council, explores tourism development initiatives aimed at enhancing revenue generation, promoting local culture, and improving workforce sustainability within the Aitchelitz First Nation. The primary target market for these initiatives will be BC residents due to the Band's remote location near Chilliwack. The project is anticipated to take between six to nine months to complete, focusing on expanding existing infrastructure and potentially involving 10-15 First Nations residents. Three alternatives were evaluated: Airbnb, featured handicrafts, and local cuisine. Each option was assessed based on cost, competitiveness, and resource availability. While Airbnb offers a unique living experience, its cost is moderate, and it faces competition from existing options in Chilliwack. Local cuisine, despite its potential to attract international visitors, presents higher costs and lacks uniqueness compared to Chilliwack's culinary scene. Featured handicrafts, drawing inspiration from the Aitchelitz Band's rich history, emerged as the most viable option due to its lowest estimated cost, strong uniqueness, and manageable resource requirements. The recommendation emphasizes the Band's full autonomy in the design, material sourcing, instruction, and marketing of these handicrafts. This approach ensures the preservation of cultural integrity while fostering economic growth through tourism.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.726
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.268
Teacher spread0.239 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

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