MétaCan
Menu
Back to cohort
Record W7143259969

Ideales de belleza femenina y su impacto en la satisfacción corporal de la mujer en Latinoamérica

2023· article· es· W7143259969 on OpenAlexaboutno aff
Pierre Wilhelm, Jhoeen Sneyder Rojas Día

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2023
Typearticle
Languagees
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsnot available
Fundersnot available
KeywordsBeautyLatin AmericansContext (archaeology)Ideal (ethics)Construct (python library)
DOInot available

Abstract

fetched live from OpenAlex

The ideals of beauty are a construct in which the family, culture, society and the media intervene, in an interweaving that ultimately determines the woman’s bodily satisfaction. This reflection article derives from the theoretical and contextual review of the research “Female viewers’ processing of contravening beauty ideals in movie melodrama in Mexico and Colombia and their body esteem responses: an exploratory study” project carried out between the University of Athabasca (Canada), the University of the Gulf of California (Mexico) and the Catholic University Luis Amigó (Colombia) and presents, based on the studies found in the context of Latin America, how the beauty ideals of women in the continent are influenced by the media and their impact on the body satisfaction of Latin American women. In conclusion, it is evident that there is a relationship between the media uses of women and the construction of their ideals of beauty, which affects a greater dissatisfaction with their bodies. It highlights the impact of the thin ideal on women’s body satisfaction and how it influences eating disorders, sports behavior, surgery, and mental health conditions. Although there are important research contributions in Latin America on the subject, further study is required on the social determinants in the construction of beauty ideals and the contribution of the media to 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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.018
GPT teacher head0.316
Teacher spread0.297 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueDialnet (Universidad de la Rioja)Same topicMedia, Gender, and AdvertisingFrench-language works237,207