8 Investigating Social and Environmental Impacts of the Indian Clothing Sector
Bibliographic record
Abstract
The clothing sector is one of the oldest trades, having import and export practices from all corners of the world. Clothing is one of the most prominent economic activities in the globally competitive world. It has been innovating to satisfy the growing demands of customers. The buying preference in the clothing industry has been ever-changing, uneven and hyper-individual. Increasing demand in its consumption has exponentially increased production. Consumers demand affordable clothes and find quick disposal convenient, leading to increased harmful waste generation. The inferior composition of material processing leads to enhanced soil contaminations and excessive wastage of water, resulting in massive environmental and social degradation, which is often beyond repair. Natural fabrics are now increasing in demand to address the health and environmental concerns of many of the current consumers. Thus, sustainability is becoming the primary concern for some fashion brands, both in terms of projecting the right image and modifying the manufacturing processes to address these rising awareness and concerns. The present chapter explores the environmental and social impacts of the Indian clothing sector through a theoretical investigation from past research insights.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".