Six. Re- collecting Black Americana: “Absolutely Derogatory” Objects and Narratives from eBay’s Community
Bibliographic record
Abstract
re-collecting Black americana "a B s o l u t e ly D e r o g at o r y " o B J e c t s a n D n a r r at i v e s f r o M e B ay ' s c o M M u n i t ySellers deploy the terms "gay," "gay interest," "lesbian," and "lesbian interest" to make an array of desires visible on eBay and establish oppositional positions.Many of these sellers resist eBay's structures and regulations.However, sellers support eBay's "Black Americana" category and assist in rendering stereotyped black identities and disempowered African Americans.In this category, sellers have not collaboratively developed forms of critical resistance.Instead, sellers attach such insulting terms as "mammy," "sambo," and "nigger" to reprehensible depictions of African Americans performing dimwitted actions, dancing, and serving.For example, writer_art renders African Americans as cheerful, servile, and unable to separate eating from evacuating by offering an "adorable" bank with a "little fella" that "is happily eating a huge slice of juicy, ripe watermelon as he sits on a pottie" and "happily" holds "coins for you."1smitherama also conflates caricatures and people, connects disability to African American identities, and dismisses black agency and adulthood with the term "little" by offering "a delightful little guy" that "can sit up by himself, but not stand by himself."2Black Americana items are listed under "Collectibles > Cultures & Ethnicities" and "Collectibles > Postcards > Cultures & Ethnicities."3These categories also appear on eBay's Canadian site.eBay's terms and sellers' listings promise to deliver black cultures, collectibles, and history while listing racist representations that empower whites, providing apocryphal narratives
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.041 | 0.016 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".