Creative Careers and Territorial Development: The Role of Networks and Relational Proximity in Fashion Design
Bibliographic record
Abstract
Geater Montreal is the third largest city in North America for the garment industry in terms of labour force, after Los Angeles and New York. The industry has however changed partly into a service industry, centered on fashion design, with a focus on international competitiveness but also the role of fashion in Montreal's economic and territorial development. Our article analyzes careers in the fashion design sector, sheds light on the evolution of creative sectors, and shows how these sectors could be better supported to favor local development, as neighborhoods and space design appear important in these creative sectors. We situate our analysis in the theoretical context of career theories, and analyze key moments in careers and the role of intermediate organizations and government programs in supporting these careers. Our paper makes a contribution to our knowledge of career paths in the fashion industry, but also to the role of relational proximity in supporting these careers, and thus local development. It highlights the importance of personal connections, the milieu in which the individual works and functions, the creativity of the individual, as well as the role of the local support organizations and professional associations, including agencies of the provincial government.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".