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Record W6940594230 · doi:10.11575/prism/49428

Calgary as a Sustainable Tourism Destination

2024· other· en· W6940594230 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2024
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityTourismSustainable tourismSustainable developmentDestinationsDestination management

Abstract

fetched live from OpenAlex

Sustainability drives competitiveness for tourism destinations. When looking to either visit a location or host conventions, meetings, or events, both local and international visitors and clients are increasing their expectations of a destination’s sustainability performance. This, coupled with increase of travellers putting pressure on the planet’s natural resources, demands the sector reevaluates how well its environmental, social, and cultural systems of a destination are managed and protected. This research utilized the Global Destination Movement’s GDS-Index to measure how well Calgary performs as a tourism destination. Sustainability is measured across 77 indicators within four categories (social, environmental, supplier and destination management organization performance), and is aligned with the United Nation’s Sustainable Development Goals. Recommendations were put forth to drive performance year-over-year, focused on program development and meaningful engagement. Overall, this research supports sustainable and regenerative motivations of Calgary’s tourism industry, enabling the destination to remain competitive within a growing sector.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.402

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.017
GPT teacher head0.263
Teacher spread0.246 · 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
Published2024
Admission routes1
Has abstractyes

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