Ideales de belleza femenina y su impacto en la satisfacción corporal de la mujer en Latinoamérica
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".