It’s hard to be loved by idiots.Fred Perry’s troubled relationship with the Proud Boys
Bibliographic record
Abstract
Research methodology For the design of this case study, the authors used primary sources of information from the shops visited by them in preparation of the case and website of Fred Perry and secondary sources of information from both academic and journalistic publications. Case overview/synopsis Fred Perry is a premium clothing brand, well-known for its polo shirts. It was created by Mr Fred Perry, a British tennis player. The brand’s stated values are integrity, personality and individuality. Throughout its history, the brand has been adopted by different British subcultures but recently it has faced a challenge because of the brand appropriation by the Proud Boys, a US far-right white supremacy group and other extremist groups as Antifa and hooligans. The nature and actions of the group mean that Fred Perry runs the risk of losing control over its brand equity. This brand hijack means that Fred Perry risks alienating some of its customers by openly opposing the group but also by embracing this subculture’s appropriation. Practically, the brand opposed the appropriation in a press release and by putting an end to the sale of the black and yellow polo shirts in the USA and Canada. Fred Perry has also made a lot of efforts to reposition the brand away from extremist groups while maintaining its strong historical and cultural roots. Through this case study, students will have the opportunity to discuss this topic and explore solutions for brands that face this type of dilemma. Complexity academic level This case is designed to be used in a marketing management, brand strategy or consumer behavior/culture course, especially in the subfield of market segmentation in the telecommunications sector. Specifically, this case is designed for college seniors or master students with basic strategic marketing training. This case will help students understand the difference between the brand identity that the brand owners intend and the brand image that consumers actually perceive. It provides the basis of discussions on the topics of brand management, consumer culture, consumers-brands relationships, brand architecture, brand equity, brand appropriation and repositioning strategy.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.027 | 0.011 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 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".