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Record W2800853504 · doi:10.3138/cjhs.2017-0020

Acceptance of female public toplessness: Structural, contextual, and individual predictors of support

2018· article· en· W2800853504 on OpenAlexvenueno aff
Colin R. Harbke, Dana F. Lindemann

Bibliographic record

VenueThe Canadian Journal of Human Sexuality · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsnot available
Fundersnot available
KeywordsReligiosityPublic opinionSocial psychologyPsychologyTraitDisgustOpposition (politics)PoliticsPolitical science

Abstract

fetched live from OpenAlex

Despite frequent attention in contemporary culture, little empirical research has been done on acceptance of female public toplessness during the past 20 years. As a replication and extension of prior work (Fischtein et al., 2005), an international survey of 314 women and 86 men reported their opinions toward the legality of female toplessness in three public settings. Overall, support ranged from 58% to 76% and was higher than observed in prior surveys from the 1990s. Context, or the specific location where toplessness occurs, remained an important consideration for support. In addition, demographic and attitudinal factors served to predict support and opposition to public toplessness. Specifically, higher religiosity and lower attitudes toward sexual permissiveness were associated with opposition to public toplessness, whereas, lower child protectiveness beliefs and lower trait disgust sensitivity were associated with support of public toplessness. Although men were generally more supportive of public toplessness, gender did not emerge as a significant predictor. Sampling differences and concerted efforts through social media and political campaigns that occurred between prior surveys and the current study may explain, at least in part, the increased overall support and lack of gender differences. As such, these findings may have important societal and legal implications for the acceptance of female public toplessness.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.090
GPT teacher head0.354
Teacher spread0.264 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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