Creative cities, creative spaces, and urban policy : the impacts of regulations on artist-run centres and independent arts spaces in Vancouver, British Columbia
Bibliographic record
Abstract
Over the last decade, emergence and popularity of the creative city has generated considerable interest in the significance of arts and culture to economic and community development. In this context, artists and cultural facilities are considered essential assets contributing to creativity and innovation by attracting skilled workers and business investments, revitalizing inner city industrial areas, and discursively reimagining and rebranding the city through cultural events and large-scale cultural infrastructure projects. This research examines the effects of regulations on the creation and operation of artist-run centres and independent arts facilities as essential sources of cultural production and creativity in Vancouver, British Columbia. Drawing on a series of in-depth, semi-structured, face-to-face interviews with the founding members, administrators, directors/curators, and/or primary operators of twelve artist-run facilities in Vancouver, research examines how artists and arts administrators experience the process of achieving bylaw and regulatory compliance to manage and sustain the operations of non-profit and independent arts spaces in a post-industrial context of policy implementation and urban redevelopment. Research addresses the strategies artists’ employ to achieve bylaw and regulatory compliance, as well as the contributions these spaces make to the cultural fabric of the creative city. Finally, research examines artists’ primary motivations for continuing their creative practices in increasingly challenging arts market and policy context. Research findings reveal that while non-profit and independent arts spaces contribute to both community revitalization and artistic development, issues pertaining to the urban planning and policy limit their community and economic development potential. As a result, this paper calls for a constructive and collaborative approach to enabling cultural facilities development within local government, and a re-conceptualization of the creative city planning agenda to include both the cultural products of creative industries and the diverse cultural experiences of non-profit and independent arts organizations beyond their economic and commercial development imperatives.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.012 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".