The White-Shirt Experiment: Influences of Product-Source Knowledge and Attributes on Perceived Values of Secondhand Clothes
Bibliographic record
Abstract
Despite economic benefits, sustainability, and potential hedonic experience; stigma exists regarding the purchase and use of second-hand products. This study explored the influences of that stigma on consumer perceptions by determining differences in perceived monetary values based on product-source knowledge and product attributes. Three gently used white shirts with varying attributes were used in the experiment with a convenience sample of 105 active consumers. While it was inconclusive whether negative perceptions towards second-hand merchandise are predicated on product-source knowledge alone, our findings suggested certain attributes of clothes may neutralize its influence. Second-hand shirts of recognizable high-end brands and ones with unique designs were perceived as having greater value and consumers were willing to spend more on them than on similar but basic or generic items. Consumers from all economic backgrounds can become educated and responsible shoppers by portraying admirable style with secondhand clothes. Resale operators could take away applicable knowledge for value-pricing practice.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".