Resale of recalled children’s products online: an examination of the world’s largest yard sale: Table 1
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To examine an online auction site for the presence and sale of children's products and toys previously recalled because of safety concerns. METHODS: Targeted items were randomly selected from US Consumer Product Safety Commission (CPSC) press releases of recalled children's products dated 1992-2004. Auction listings from eBay were searched for the 150 targeted recalled items for 30 days. Item, seller, and buyer information were recorded from the auction listings. RESULTS: 190 auctions contained or were suspected to contain a recalled children's item from the target list. Most of the recalled items were listed for sale from addresses within the United States, with sellers from Canada, Australia, Great Britain, and Ireland also represented. On average, six bids were placed on each recalled item, with 70% of auctions eventuating in a sale. CONCLUSIONS: Recalled children's products were found to be available for sale online and were sold most of the time, presenting a risk of injury to children. Although the CPSC is charged with notifying the public of recalled items, these results suggest that potentially hazardous products are recirculating online. A multi-front initiative to decrease the presence of hazards in online auctions is needed. This initiative should include increased manufacturer efforts to improve recall return rates, a requirement by online auction sites that sellers verify non-recall status before item posting, and parental checks of government recall websites before item purchase. Investigation of parental understanding and awareness of recalls and the potential risks associated with recall announcements is needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it