Coworking spaces in mid-sized cities: A partner in downtown economic development
Bibliographic record
Abstract
The 21st century economy is knowledge-intensive, creative and flourishing in larger urban centres. Less is known about how smaller urban centres are faring in this new economy. This research aims to fill that gap by exploring whether mid-sized cities, in a designated growth area in Ontario, Canada, can leverage the knowledge economy and foster local economic development to help revitalize their ailing downtowns. Through a case study approach, this research looks at the role that coworking, or shared workspaces, can play in the local economy of mid-sized cities in Ontario. Recognizing the role that community-based actors play in urban affairs, this paper uses a local economic development framework to explore the role of coworking spaces in the urban economic fabric of mid-sized city downtowns. Survey responses and interviews, coupled with insights from global surveys on coworking and a literature review, begin to tell the story of how economic change is playing out in mid-sized cities, illustrating the importance of an innovative, collaborative and inclusive approaches to city building and local economic development.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| 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".