Bibliographic record
Abstract
This chapter examines Canadian creative hubs and networks that support arts, culture and media organizations and creative workers, based on five years of research. These networked sites can contribute to local cultural districts, provide co-working spaces to share skills among professionals, spark innovation, or involve clients, users, and social groups in more collaborative ways. The chapter assesses opportunities and limitations implicated in current federal policy (specifically the Canada Cultural Spaces Fund or CCSF). The concept of creative citizenship is used to examine the CCSF as a financial instrument but also how it incorporates an ethics of care to think about how creative workers operate in tandem with the systems they occupy and maintain. To illustrate this, I turn to some of the hubs and networks I have investigated, as well as funders I have spoken with about these sites. I also briefly explore how four organizing pivots shape an emergent taxonomy of creative hubs and networks that is being prepared for public distribution based on my research over the last five years. Finally, this chapter uses exemplars of the four pivots to suggest how varied creative networks and hubs can reshape policy itself as well as production and distribution environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
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".