Paint it White: Segregationist Logics in Advertising and the Electric Guitar
Bibliographic record
Abstract
Sociologists recognize that symbolic boundaries may be activated and reinforced through the production and consumption of cultural objects. Less attention, however, has been paid to the role of advertising as an ascriptive boundary‐making mechanism in the life cycles of objects. Using the case of the electric guitar, this study examines how a cultural object‐pioneered and popularized by Black celebrity guitarists became homologous with White masculinity through the production and circulation of visual images featured in advertising materials. Data come from product catalogs circulated by the two preeminent electric guitar brands during the instrument’s large‐scale production and consumption in the United States (1955–1982). I conduct a content analysis of annual product catalogs focusing on the proportional representation of visual images of Black and White celebrity guitarists. Findings indicate that Black celebrity guitarists were rarely featured in advertising materials despite their exclusive use of both brands’ instruments. Consistent with segregationist logics embedded in modern advertising, Black celebrity guitarists were rendered non‐existent and replaced with images of White celebrity guitarists and depictions of middle‐class White masculinity. I interpret my findings as evidence of the prevalence of segregationist era logics in the advertising and construction of the electric guitar as a racialized and gendered cultural object. I conclude by discussing how this study advances recent scholarship concerning racial inequities in the consumer marketplace and the significance of ascriptive boundaries in the production and consumption of cultural objects.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".