Sustainability in Fashion and Textiles
Bibliographic record
Abstract
The fashion clothing industry is particularly subject to strong external pressure for sustainable behaviour and the increased outsourcing of manufacturing has created long, globally fragmented supply chains.Supply chain management (SCM) has come to the fore in this industry, as the way a firm designs and manages its supply chain can provide competitive advantage in a market focused on cost, speed and availability.It also provides a relational view of the supply chain that can be used to evaluate and address the environmental, social and economic impacts of products, processes and practices.Building on sustainability theory and supply chain strategy, this chapter attempts to provide an integrated understanding of how supply chains can be managed in practice to effectively address the dimensions of sustainability.It analyses all stages within the clothing supply chain and assesses the different environmental and social impacts that can occur throughout the product life-cycle.It considers the value of long-term, collaborative relationships in providing a coordinated supply chain strategy which addresses these serious, increasingly high profile issues, and in turn generates competitive advantage.The chapter will address the following research questions:1. How is sustainability interpreted academically and how does this translate into practice?Chapter 03.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.069 | 0.019 |
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".