Bibliographic record
Abstract
This paper is an explorative study into coworking.Coworking is a relatively new business service model, which has been rapidly expanding in recent years.Little academic research has been completed on the definition and composition of coworking spaces around the world, and the businesses that use them.This work examined existing academic literature, traditional media, and social media sources to assess the roots of coworking in the larger socio-economic sphere, and the current incarnations and general conceptualization of coworking spaces.An exploratory study of a coworking site in Halifax, Nova Scotia, Canada was conducted through one-on-one interviews with two owners and five members.The results of the interviews were examined for themes and their consistency with the literature to date.It was found that there are different models for coworking across North America.The Hub-Halifax is focused on networking and the connections and partnerships that can form in its openconcept office environment.In general, the owners and the users of the Hub-Halifax agreed with the literature that coworking decreases isolation, offers networking opportunities, intrinsically supports bootstrapping functions, and assists with ideation and productivity.They also agreed that the coworking space could be improved: it can be noisy, there is demand for more amenities, and privacy and security can be an issue.These interviews also uncovered some other themes not covered in the current literature.One was age: whether this method of working was more intuitive for younger people.Another was the possibility that coworking could function as a platform for social engineering and activism through leveraging its networking capabilities to fully engage with the community, positively affecting the economic viability of the local area.
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 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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".