Being a Fashion Designer in Montreal: Flexible Careers across the Life Course!
Bibliographic record
Abstract
Our article addresses the evolution of the fashion designer career over the last century, and situates this in the context of the “creative city” of Montréal: “UNESCO City of design” (2006). In the context of the complex world of local fashion, one form of the World of Art [1], we explore the reality of the flexible career and theprecarious form of work of fashion designers in Montreal. For this, we present a brief historical overview of the development of the profession in order to understand how the profession of fashion design has emerged locally and how careers have developed and transformed over the years and the designers’ life courses. After this overview, we examine the more recent development and the new vision of this profession in the context of the creative economy and particularly the paradox of a career situated between the artistic endeavour and the entrepreneurial and financial challenges. Methodologically, this study is based on a literature review as well as on three series of interviews conducted over the past years (2010-2013) with some (48) designers as well as organizations and associations working in the fashion industry. However, here we use mainly the case of one designer, Jean-Claude Poitras, as a particular illustration.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.009 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.001 |
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".