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
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".