Reconciling the local and the global in the Brisbane independent fashion sector
Bibliographic record
Abstract
The humid, sub-tropical city of Brisbane is Australia’s third-largest and one often regarded as culturally inferior to its southern counterparts Sydney and Melbourne. However, the city has supported a small but active independent fashion scene, and this article examines three of these businesses, exploring how they positioned themselves in relation to the global fashion industry. It contributes to literature on local fashion industries in New Zealand, Scandinavia, Canada and the United Kingdom. Challenges and opportunities presented to local fashion businesses are considered, and ways in which these have changed over time is also discussed. Case studies are drawn from a period between 1950 and 2018 and were purposively chosen so that contemporary case studies could be contextualized with historical examples. Research was conducted through archival research at the Queensland Museum, semi-structured interviews with participants and on-site observations. Findings confirm those of existing studies in the field that suggest local fashion businesses outside of large cities and dominant fashion centres may struggle to remain relevant in a fast-paced global industry, but have an opportunity to develop and foster close bonds to local cultural scenes and to contribute to place-making in the cities in which they are located.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.022 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".