Understanding the Global Trade of Second-Hand Clothing by Analyzing Used Clothing Donor Perceptions in Ottawa
Bibliographic record
Abstract
The second-hand clothing commodity chain is a global, multi-billion dollar trading network which has been growing steadily since the early 1990s. Used clothing tends to be exported from high-income countries, like Canada, to low-income countries around the world, undermining local apparel industries, livelihoods, and environments. Despite this, North Americans are often ethically motivated to donate; framing their donations within humanitarian and environmental aspirations. In other words, there is a disjuncture between the perceptions of used clothing donors, and the livelihood and environmental impacts on the ground in receiving countries. I take an action-research approach to explore and address this tension, and my work is guided by the question: how do donors of used clothing view their role within the second-hand clothing commodity chain and how does this impact their clothing donation behaviour? I draw from semi-structured interviews (n = 20) with students at Carleton University in Ottawa, Ontario, who have donated used clothing at least four times within the past two years. Young Canadians are an important study group because they are still developing donation habits. In particular, university students can help shape the future of the second-hand clothing industry. I am confident that by improving environmental education and making students aware of the ecological and livelihood impacts of used clothing donation, my action-research approach not only has the potential to impact life-long behavioural change of participants but will uncover creative alternatives for Canada to develop a second-hand clothing industry that is more environmentally viable and socially ethical.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".