Ethical trade-offs in fast fashion: Exploring social, environmental, and health dimensions in clothing consumption
Bibliographic record
Abstract
We conduct a choice experiment survey to determine Swedish consumers' preferences for T-shirts with different levels of health risks to the consumer, environmental impact of production, and working conditions during production. We estimate the marginal willingness to pay (MWTP) for improvements in each attribute and explore ethical trade-offs between them. We conduct the same analysis for consumers buying a t-shirt for themselves and parents purchasing a t-shirt for their children. Our findings show that the health attribute was ranked highest, followed by working conditions and the environmental attribute. While the ranking of the attributes is consistent between the two samples, parents exhibited a lower overall MWTP. We also observe a general pattern of higher willingness to pay to avoid the lowest level (‘Very Poor’) of each attribute and achieve the intermediate level (‘Fairly Good’) than for further improvements to the highest level (‘Good’). This pattern, consistent with how the levels were designed, holds across all subsamples and attributes. Thus, we find substantial demand for more sustainable clothing, particularly for avoiding the worst practices. Our results also suggest that producers could pass on a portion of their increases in costs if sustainability improvements are effectively communicated. While most consumers are not willing to pay more to reach the highest level of an attribute, there are groups of consumers who are willing to pay a premium for high sustainability standards.
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How this classification was reachedexpand
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) | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".