An asset analysis of the Yukon Territory for sustainable tourism development
Notice bibliographique
Résumé
Purpose: This research represents the first comprehensive post-pandemic analysis of tourism assets across Yukon Territory, undertaken in partnership with the Tourism Industry Association of the Yukon (TIAY) to address critical knowledge gaps regarding the current state, availability, and diversity of tourism-related infrastructure. These gaps include: (1) the actual number and distribution of tourism businesses across communities, (2) the operational status and recovery patterns of businesses post-pandemic, (3) the degree of tourism service diversification in rural communities, and (4) the systemic barriers preventing tourism development despite natural and cultural assets. These knowledge gaps are critical because they impact evidence-based policy development, efficient resource allocation, and strategic investment decisions in a territory where tourism represents a primary economic driver. The study also examines how northern destinations like Yukon can develop sustainable tourism systems while preserving their unique cultural and ecological integrity, responding to the intersection of environmental vulnerability, infrastructure limitations, and pandemic-related disruptions that have created challenges for territorial tourism development. Methodology: The research employed a mixed-methods approach using the asset database, quantitative survey analysis, and qualitative interviews of tourism business owners/managers. The asset inventory identified 590 tourism businesses across 21 communities and 11 sectors—significantly exceeding the 400 businesses previously estimated for planning purposes. Data collection included an online survey distributed to all identified businesses (90 completed responses), semi-structured phone interviews with tourism operators, and field observations conducted during a familiarization tour. Analysis was conducted using SPSS, Microsoft Excel, and NVivo to integrate quantitative patterns with qualitative insights from industry stakeholders. Results: Key findings address critical knowledge gaps: (1) Tourism asset distribution follows extreme concentration patterns, with 51.9% of businesses in Whitehorse and 81.4% along highway corridors, revealing that infrastructure determines rather than supports tourism development; (2) Two communities (Whitehorse and Dawson City) achieved complete tourism service diversification (3) Seasonal operations create a 59% average staffing reduction, representing not just demand variation but systemic operational discontinuity that existing tourism theory does not address; (4) Housing emerged as a cascade constraint, simultaneously limiting workforce availability, business expansion capacity, and visitor accommodation; (5) Post-pandemic assessment shows 62% of businesses pursuing growth strategies despite these constraints, suggesting resilience mechanisms not predicted by conventional crisis recovery models. These findings reveal that the critical knowledge gaps were not simply about counting businesses, but understanding how infrastructure dependencies create tourism development paradigms.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».