Exploring the dimensions of place branding: an application of the ICON model to the branding of Toronto
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the place branding dimensions of a city undergoing a concerted effort to build a distinctive brand for itself. Design/methodology/approach A qualitative, exploratory approach is adopted, applying the ICON model of place branding to the multistakeholder city branding strategy of Toronto. A combination of interviews, participant observation, content analysis and professional reflection inform the study. Findings Toronto’s emergence as a creative city with global standing has been achieved, in part, through a holistic and collaborative approach that is integrated, contextualized, organic and new. Practical implications Place and destination promoters are offered a practical application of the ICON model of place branding, informing future initiatives and offering insight into good practice. Originality/value Viewed through the lens of the ICON model, the paper provides insights into the collaborative and innovate practices that characterize effective city branding.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".