Street art and creative place-making: urban tourism regeneration in Toronto, Canada
Bibliographic record
Abstract
Purpose This paper aims to discuss the place-making processes of street art within the context of Toronto, Canada, and potential for street art as alternative tourism to contribute to new urban tourism and encourage urban regeneration in the city. Design/methodology/approach The study applies reflexive thematic analysis to analyse secondary data sources such as reports, maps, videos, websites, news articles and official documents alongside photographic documentation and field research. Findings Street art in Toronto has been found to coincide closely with processes of creative place-making. While there is some indication that municipal street art organizations and destination marketing organizations are aware of the possibilities for street art to contribute to tourism in the city, it remains an untapped resource for new urban tourism. As a component of creative place-making, it has great potential as a form of alternative tourism to regenerate a still struggling tourism economy. Originality/value This paper explores the nascent research area and practical application of street art as an alternative form of urban tourism in Toronto, Canada. It also fills a gap by connecting the concept of creative place-making with street art, urban regeneration and tourism specifically; a focus that needs wider attention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".