MétaCan
Menu
Back to cohort
Record W4320075787 · doi:10.15173/sciential.vi8.3036

To look like Superman: Male body dysmorphia

2022· article· en· W4320075787 on OpenAlexaffvenue
David Rodrigues, Sabrina Rodrigues

Bibliographic record

VenueSciential - McMaster Undergraduate Science Journal · 2022
Typearticle
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBody dysmorphic disorderPsychologyDistressMental healthHuman physical appearanceSupermanDevelopmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Body dysmorphic disorder (BDD) is a psychiatric illness characterized by obsessive thoughts in relation to one’s appearance. Body dysmorphia continues to gain attention in the general media, academia, and the scientific community. This mental health condition can happen to anyone of any gender and is evaluated to be a chronic and long-term condition. Although research and developed models have attempted to understand the etiology, there is significant limited amount of research regarding BDD in relation to men. This highlights the need to bring awareness surrounding this topic by expressing thought provoking questions, as without treatment, BDD will progressively worsen as one ages. In this piece, we present thoughts on why this area is under-represented, as well as briefly describing what body dysmorphia is and the main area of distress in men. Moreover, we discuss why men are fixated on achieving the “ideal male image” and what it appears to be, what are the possible factors inducing body dysmorphia, and the overarching need to conduct more research on this topic.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.004
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.002

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 head0.022
GPT teacher head0.300
Teacher spread0.277 · 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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueSciential - McMaster Undergraduate Science JournalSame topicBody Image and Dysmorphia StudiesFrench-language works237,207