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Record W1877157738 · doi:10.29173/cjs882

Men, appearance, and cosmetic surgery: The role of confidence, self-esteem, and comfort with the body

2008· article· en· W1877157738 on OpenAlexaffvenueabout
Rosemary Ricciardelli, Kimberley A. Clow

Bibliographic record

VenueThe Canadian Journal of Sociology · 2008
Typearticle
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsOntario Tech UniversityMcMaster University
Fundersnot available
KeywordsSelf-esteemPerceptionPsychologyIdentity (music)Confidence intervalSocial psychologySituatedLower bodyAestheticsMedicinePhysical therapyArt

Abstract

fetched live from OpenAlex

Recent research has suggested that perceptions of the body are important to men’s sense of confidence and that men see the body as a vehicle for personal improvement. To build on this research, an online survey investigated Canadian men’s perspectives on their appearance and their attitudes toward cosmetic surgery. Low self-esteem, lack of confidence, and comfort with one’s body uniquely predicted different aspects of men’s experiences, including attitudes about body shape, perceptions of others, pressures to lose weight, and perspectives regarding cosmetic surgery. For example, participants who were more comfortable with their bodies and higher in self-esteem were happier with their current body shape and features, whereas participants who were less comfortable with their bodies and lower in confidence put more pressure on themselves to lose weight. In addition, lower confidence significantly predicted willingness to undergo cosmetic surgery. Men’s perspectives on cosmetic surgery were thematically analyzed. These findings are situated within identity theory and sociology of the body.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.234
Teacher spread0.219 · 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 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

Citations19
Published2008
Admission routes3
Has abstractyes

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