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Record W7104176885 · doi:10.1080/14616688.2025.2580390

Regenerative tourism through multicultural placemaking

2025· article· en· W7104176885 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTourism Geographies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative and Sustainable Housing Initiatives
Canadian institutionsToronto Metropolitan UniversityWilfrid Laurier University
Fundersnot available
KeywordsPlacemakingTourismMulticulturalismTourism geographyCultural tourism

Abstract

fetched live from OpenAlex

Regenerative tourism closely aligns with the principles of place-making, contributing to the revitalization of ethnic heritage landscapes and the communities that inhabit them. This study commentary explores the intersections of immigration and tourism development in Toronto, highlighting the significant role that multicultural diversity plays in rebuilding communities disproportionately affected by the COVID-19 pandemic. The discussion offers a critical analysis of Toronto’s current tourism policy, evaluating the extent to which regenerative principles are integrated into its strategic framework. It emphasizes the transformative potential of multicultural place-making in reshaping tourism through community-driven resources and regenerative urban development. By adopting a place-based lens, the study addresses existing gaps in understanding the importance of immigration histories to multi-ethnic urban environments and their capacity to foster urban regeneration.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.325
Teacher spread0.308 · 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