The Competitive Foundations of Localized Learning and Innovation: The Case of Women's Garment Production in New York City*
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract: This article considers the relevance of the “local” for firm learning in New York City's Garment District. By documenting the design innovation process in the district's women's wear industry and the ways in which designers draw on the district's specialized services and institutions to assist in the process, the article examines how a localized agglomeration or “cluster” facilitates the development of shared conventions and practices. It also shows how the district confers benefits on firms in indirect ways. Since apparel manufacturers operate in a U.S. regulatory framework that inhibits cooperation, the Garment District's support institutions serve as production intermediaries, providing firms with a means to monitor and observe rival firms' performances and solutions. As such, the case of the Garment District poses interesting challenges to the prevailing conceptions of the “local” as a site for cooperation and suggests the need to rethink the relevance of competition for learning and innovation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it