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Record W4294739146 · doi:10.1386/csmf_00058_1

Undressing masculinity: An exploratory study on men’s embodied engagement with underwear

2022· article· en· W4294739146 on OpenAlexaff
Johnathan D. Clancy, Ben Barry

Bibliographic record

VenueCritical Studies in Men’s Fashion · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsYork University
Fundersnot available
KeywordsMasculinityEmbodied cognitionContext (archaeology)Exploratory researchPsychologyHegemonic masculinityGender studiesScholarshipSocial psychologyDemographicsSociologyCasualSocial sciencePolitical science

Abstract

fetched live from OpenAlex

This article shares findings from an exploratory study on the relationship between men’s embodied engagement with underwear and their practices of masculinity. Drawing on wardrobe interviews with nine men and object analyses of their underwear, we investigate how men understand the role of underwear in their lives, how they shift their underwear choices in different social contexts and how they experience their bodies through underwear. Our participants developed emotional bonds with their underwear, but their engagements with these items were restricted by gendered social pressures and boundaries. We argue that men use underwear as ‘manhood acts’ to provide themselves with comfort and confidence to navigate everyday life and, ultimately, shore up and affirm hegemonic masculinity. This article contributes to men’s fashion scholarship on underwear by introducing the context of everyday dress practices to the existing focus on branding and advertising images. We encourage researchers to build upon our study on men’s underwear by engaging participants whose demographics expand beyond our sample of primarily heterosexual, cisgender men who were under 35 years of age.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.010
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.203
GPT teacher head0.362
Teacher spread0.159 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2022
Admission routes1
Has abstractyes

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