Exploring the Role and Impact of Cultural Appropriation in the Fashion Industry
Bibliographic record
Abstract
Cultural appropriation is a general phenomenon in the fashion industry today, in which international brands appropriate cultural elements from marginalized groups without permission or compensation. This causes continuous public discussion and criticism of the fashion industry. This article uses typical examples such as Gucci's "blackface" sweater, Dior's "Sauvage" perfume advertisement, and Isabel Marant's use of Mexican Huipil embroidery as a starting point to analyze the phenomenon of cultural appropriation in brand fashion design. The article uses qualitative analysis and theoretical integration to examine the impact of cultural appropriation in the fashion industry on marginalized groups (ethnic minorities, indigenous communities, and religious groups). The results indicate that cultural appropriation often derives from unequal power structures between social groups and the lack of legal protection for traditional cultural expressions. This is leading to cultural devaluation, economic exploitation, and emotional harm toward marginalized groups. The article claims that brand companies should not use "borrowing inspiration" as an excuse for cultural appropriation. Instead, companies should shift toward collaborative and co-creation models with marginalized groups, and international organizations should enhance consumer awareness of cultural appropriation issues while addressing legal loopholes related to cultural copyright ownership, thereby protecting marginalized groups' cultural autonomy.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| 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".