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Record W4405485446 · doi:10.24124/2024/59590

Bringing dinosaurs into the 2020s: Considering current visitation and future virtual tourism possibilities for the Tumbler Ridge Museum and the Tumbler Ridge UNESCO Global Geopark (BC)

2024· dissertation· en· W4405485446 on OpenAlexaboutno aff
Yihang Zhang

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicGeotourism and Geoheritage Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsGeoparkRidgeTourismCurrent (fluid)GeographyGeologyArchaeologyHistoryPaleontologyOceanography

Abstract

fetched live from OpenAlex

Designed in collaboration with the Tumbler Ridge Museum and the UNESCO Tumbler Ridge Geopark, I adopted a mixed-methods approach in designing this project. My research examines potential virtual tourism inclusions for the Geopark and the Museum, and considers how these technologies can be used to enhance visitor experiences and accessibility. Core project components are a literature review of virtual tourism technologies and possibilities represented in the academic literature, and empirical data that I gathered via a visitor survey and on-site observations in Tumbler Ridge, British Columbia, Canada (summer 2022). My literature review found inconsistencies in virtual tourism terminology. As a result, I am proposing a new umbrella term, “virtual tourism experiences (VTEs),” to encourage clarity and ease of access to this topic. VTEs include technologies such as Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), 360° photo view, live streaming, and webcam-travel. All of these can be used to invite people to connect with remote places and/or on-site experiences. VTEs can be employed engage people during different stages of a user/visitor journey: pre-trip, during-trip, and post-trip. To clarify potential types and uses with respect to trip stages, I am also forwarding a modified conceptual model. It illustrates how various types of VTEs can be employed throughout the user/visitor journey. The Tumbler Ridge visitor survey data that I collected and analyzed generally fits with prior visitor data, but also provides new insights into stays and activities. It also raises some key concerns and contrasting opinions about VTEs—some participants perceived VTEs as potential helpful supplements to physical trips. Others raised concerns about VTEs as threats to nature-based authenticity. My thesis closes with resulting tailored VTE recommendations for the Tumbler Ridge Museum and Tumbler Ridge UNESCO Global Geopark.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.710
Threshold uncertainty score0.991

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 studies0.0010.000
Scholarly communication0.0010.000
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 head0.010
GPT teacher head0.240
Teacher spread0.230 · 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 designObservational
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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