Advancing Toward Sustainability: A Systematic Review of Circular Economy Strategies in the Textile Industry
Bibliographic record
Abstract
The textile industry, fueled by the “fast fashion” phenomenon, contributes significantly to environmental, social, and economic degradation through the rapid turnover of styles, leading to substantial waste as consumers frequently discard garments. This cycle of consumption and production is linked to the social demand added to purchase income, demonstrating the urgent need for sustainable interventions. The main objective of this study is to carry out a systematic review of the literature to identify and critically evaluate circular economy strategies implemented in the textile industry. This study conducted a systematic review of circular economy strategies in the textile industry using the PRISMA methodology. Our search spanned a ten-year period, examining 88 articles, from which 55 were selected as pertinent. The primary strategies identified include reuse, recycling, repair, and reduction, each of which is assessed through environmental, social, and economic lenses. Reuse is crucial for reducing impacts and waste, yet it is hampered by insufficient consumer incentives. Recycling shows promise but is hindered by technological and awareness barriers. Repair contributes to extending the lifespan of garments, thereby reducing the need for new production, although it encounters challenges in terms of service accessibility and consumer knowledge. The reduction involves the search for better and more sustainable materials, with the main barrier being the fast fashion. The findings suggest that reuse is not only economically viable but also capable of lessening social inequality. Recycling, however, necessitates substantial investments and the development of supportive policies. Repair, on the other hand, significantly lessens the environmental impact and can spur new economic opportunities and employment. Despite these hurdles, these strategies present viable pathways toward a more sustainable textile industry. However, achieving this requires a paradigm shift in both consumer behavior and corporate practices to embrace and optimize circular economy practices within the sector.
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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 | 0.026 | 0.096 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.024 | 0.022 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".