‘We are not the shoes of white supremacists’: a critical race perspective of consumer responses to brand attempts at countering racist associations
Bibliographic record
Abstract
Recently, brands have come under fire for being associated with groups like neo-Nazis and white nationalists. In reaction, brands have tried to distance themselves through appeals to diversity. This research contributes to the literature on multiculturalism in marketing through a critical race perspective of how and why consumers participate in social networks in efforts to counter racism. Our findings identify three ways in which consumers respond, by punishing, advising, and defending, and highlight the relevance of circulating affect and exalted national subjects for understanding the practice and impact of multiculturalism in marketing on social media. This research contributes to our understanding of multiculturalism in marketing by extending ideas of impact beyond questions of personal cognitive change. By connecting issues of race to the larger project of nation-building, this research also complements psychological accounts of how consumers engage with brands in social networks as they work to take up diversity.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".