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Record W4406307874 · doi:10.1177/00222437251314372

From Streetwear to High Fashion: How Nonelite Producers Use Hybridization to Enter an Elite Category

2025· article· en· W4406307874 on OpenAlexafffund
Pierre-Yann Dolbec

Bibliographic record

VenueJournal of Marketing Research · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsConcordia University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEliteBusinessComputer scienceAdvertisingPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Gaining access to elite categories is challenging for nonelite producers. This longitudinal analysis of the evolution of the fashion market explains how some nonelite streetwear producers gained access to the elite high fashion category by creating an interstitial hybrid category-luxury streetwear-that bridged the two. Nonelite producers create a hybrid category by establishing commensurability with the elite category and generating appeal through cultural consonance. The hybrid category challenges the elite boundary while potentializing value creation for elites. In response, elite producers subsume the hybrid category, which resolves the challenge posed by nonelite producers and allows elites to capture the value introduced by nonelites by absorbing and exerting control over them. By doing so, elite producers rejuvenate their category's cultural relevance and strengthen its elite status, while some nonelite producers gain access to the elite category. This research contributes to the literature by theorizing nonelites' status gains through categorical hybridization, an empirically prevalent but undertheorized phenomenon. These theoretical insights are leveraged to explain why subsumption solves cooptation issues, distinguish between collective and collaborative market driving, suggest that market actors can concomitantly participate in market maintenance and change, and offer managerial recommendations for nonelites to solidify status gains.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.086
GPT teacher head0.337
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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