Festivals and Events as Everyday Life in Montreal’s Entertainment District
Bibliographic record
Abstract
Cities struggle to balance vitality and livability, and noise is at the center of many of these debates. Preconceived ideas on the sonic expectations and needs of groups of city users can be misleading, particularly in entertainment districts such as the Quartier des Spectacles in Montreal (CA). We investigated what life was like in QDS for its year-round users during the 2019 festival season (the last before the COVID-19 pandemic), building on insights from residents, workers and visitors collected through online surveys. Respondents described an overall positive view of their district marked by a diversity of experiences and frustrations, with subtle intragroup differences between residents and workers. Age was an important variable framing these experiences, but unexpectedly, older respondents enjoyed their life in QDS just as much as younger users. Dissatisfaction with residing or working in QDS was rarely geared toward the frequency or loudness of festivals, but rather to other everyday life situations. Emergent from the data, we argued for the development of soundscape personas to refer to typologies of users whose experiences differ in terms of sonic priorities and evaluations. Our findings could inform strategies for organizing large events in urban areas, maintaining an awareness of diversity of users.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".