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Record W2620844321 · doi:10.1177/0731121415601269

Editor’s Pick

2015· article· en· W2620844321 on OpenAlexafffund
Tina Fetner, Melanie Heath

Bibliographic record

VenueSociological Perspectives · 2015
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsHeteronormativityHeterosexualityGender studiesSociologyWhite (mutation)Resistance (ecology)Human sexuality

Abstract

fetched live from OpenAlex

Critical heterosexuality studies demonstrate the role of the traditional, white wedding in the reproduction of heteronormativity and gender and contribute to a social order that privileges white, middle-class, heterosexual married couples over other relationships. However, social science research points to the ways that same-sex weddings offer a site of resistance to heteronormativity and traditional gender roles. We analyze in-depth interviews with women in straight and same-sex marriages. We find that women in straight marriages are more likely to embrace the traditional, white wedding than those in same-sex marriages. Women planning same-sex weddings think deeply about their wedding ceremonies as they relate to heteronormativity. Some participants reject traditional weddings as excessively costly and wasteful. We argue that although weddings are often sites for the celebration of consumerism, traditional gender, and heterosexuality, they can also be sites of resistance that challenge these same social norms.

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)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.597
Threshold uncertainty score0.852

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0030.002
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.4030.214

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 head0.100
GPT teacher head0.429
Teacher spread0.329 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations15
Published2015
Admission routes2
Has abstractyes

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