The diversity of coworking spaces: case studies from Canada
Bibliographic record
Abstract
With an inductive approach, based on a dual qualitative and quantitative approach, we analyze the situation of coworking spaces and coworkers in Canada. The purpose of this chapter is to analyze the Canadian coworkers’ characteristics and motivations and to compare the characteristics of coworking spaces in large urban centers and those in regional or rural areas. These spaces seem conducive to the development of individual entrepreneurship and self-employment initiatives since the sharing of values and collaborative exchanges between coworkers are facilitated. However, other categories of users are present in these places, such as company employees or students. These coworking spaces stimulate people’s professional activities and can facilitate business and professional opportunities. However, there seem to be differences between metropolitan and non-metropolitan, or peri-urban, spaces. In any case, coworking is growing all over Canada and bringing together more and more different professionals in closed or open spaces.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".