Coworking spaces: New places for business initiatives?
Bibliographic record
Abstract
Increasingly present in many countries, coworking spaces can become spaces for sharing and collaboration to improve the work conditions of self-employed workers, but also of entrepreneurs and salaried workers, although there has been much less study of these. Indeed, there are numerous studies on the self-employed in coworking spaces but few of them are dedicated to entrepreneurs and salaried people, in spite of this population being one of the targeted customers of these spaces. It is thus important to start studying this population of salaried workers and entrepreneurs to identify their interests and strategies in a coworking context. Our article contributes to this, all the more so since these groups are found more in small cities and villages, less in large cities, which mainly host the self-employed. As there is a gap in the literature on these groups, we thus studied the interest of coworking spaces for small firms’ employees and entrepreneurs, a result which contributes to a better understanding of coworking and which can help in establishing coworking spaces in rural and peri-urban contexts, where they are less present to this day. This research thus contributes to knowledge of the benefits of coworking spaces for entrepreneurs and salaried workers. As has been observed elsewhere in Canada, this population of coworkers is especially critical for spaces located in rural or peri-urban areas where the number of self-employed does not allow the development of solid business models and ensure the viability of the coworking spaces. This research shows that there is definitely an interest in this type of business perspective. To answer this question as to the interest of salaried coworkers from small firms and entrepreneurs, we interviewed the founders, entrepreneurs and employees of companies using these spaces in Quebec. The goal is to better understand the strategies that facilitate business initiatives and their success in a coworking context. JEL Codes: M13, O31
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.022 | 0.023 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 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".