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Record W3158582606 · doi:10.24908/iqurcp.9051

Blue Collar Brawlers and Harley Vagabonds: Masculinity in the Tavern and on the Road

2016· article· en· W3158582606 on OpenAlexvenueno aff
Graeme Melcher

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsnot available
Fundersnot available
KeywordsMasculinityContext (archaeology)SociologyGender studiesPublic spaceAestheticsSubculture (biology)HistoryArt

Abstract

fetched live from OpenAlex

Outlaw motorcycle clubs, such as the Hells Angels, provide a modern interpretation of male working-class culture. Most notably, 19th century working-class taverns and fraternal orders can be seen as forerunners to the culture of outlaw motorcycle clubs, or ‘bikers.’ Within the confines of these spaces, men were able not only to learn male behaviour from others, but to reinforce their own masculinity through ritualized acts, such as drinking, singing, and fighting, resulting in an earned image for the culture and the space as one of violence, filth, and danger to those outside of the culture. This cultural reputation has carried over into the modern context of bikers. Originally formed to provide an adventurous outlet to, predominantly, young white men, biker culture has now become a complex and powerful subculture and image. Where early tavern culture was practiced largely in private, biker culture is defined and practiced in the public space, reinforcing its own reputation and image in the process. Despite, or perhaps because, of this public image, bikers have become deeply rooted in our collective subconscious, and represent, to some, a modern reinterpretation of the lone cowboy, making their own society in the face of all challenges. Bikers provide a modern examination of gendered spaces and masculinity. They have an element of danger and homosocial activities that make them particularly appealing to men looking for a masculine identity within a culture that they otherwise found less than welcoming – and which, in turn, did not welcome them.

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)0.002
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.016
Scholarly communication0.0070.005
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.138
GPT teacher head0.378
Teacher spread0.240 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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