Exploring the connection between odour and clothing disposal
Bibliographic record
Abstract
Increasing textile waste poses a significant environmental problem. There are many motivating factors that can influence a person's choice about when and how to dispose of unwanted clothing. The development and persistence of odour within clothing may be one such factor. The purpose of this study was to explore the relationship between clothing odour and disposal behaviour. In particular, whether consumers dispose of odorous clothing differently from non-odorous clothing. A questionnaire was developed and distributed to a convenience sample through social networks. Responses from 529 consumers residing in Canada and the United States were analysed. The majority of respondents (98.7%) have perceived odour in a clothing item at some point. Of these, approximately half had gotten rid of an article of clothing at some time because it became too odorous to wear. Odour was not a major reason for consumers to discard their clothing. However, when odour was a reason for disposal, respondents reported they were less likely to donate, give-away or sell odorous clothing and more likely to throw odorous clothing items directly into the trash. Therefore, although persistent odour in clothing plays only a minor role on sustainable disposal behaviour, when odour is a motivating factor for discard it leads to less sustainable disposal practices.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".