Bibliographic record
Abstract
The National Basketball Association (NBA), now flush with lucrative television contracts from its broadcast partners and an owner-friendly collective bargaining agreement, is as popular as ever. Besides athleticism only reserved for a small portion of humans and basketball plays that can only be made by not even most elite college players, what also keeps fans on the edge of their seats are the outfits worn by Russell Westbrook, James Harden, Lebron James and the many other fashionable players. Using what Bourdieu’s (1984) termed cultural intermediary in Distinction as a conceptual framework, this study will examine how 12 fashion journalists write about Black NBA dandies. According to Bourdieu (1984), cultural intermediaries are involved in the presentation and representation of cultural and symbolic goods and services, some of whom are salespeople, advertising executives, and interior designers. Cultural intermediaries serve as the link between production and consumption, giving the end consumer access to legitimate culture. As fashion journalists, these participants educate their readers on the latest in bespoke wear, haute couture clothing and Black style. The Black NBA body provides a medium for fashion journalists to highlight the exclusivity and democratic ideals of fashion because of the ways in which they peel off the layers of celebrity, position Black NBA dandies within a network of images, and create a dialectic tension between Black culture and a generic White culture.
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.
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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.020 | 0.013 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".