Standards of Femininity in Traditional and Contemporary China: Stereotypes and Beliefs on Women’s Appearance, Roles and their Cultural Influences
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Technological advancements have advanced patriarchal society. Modern society is bombarded with media, which introduces new styles and trends daily. These new fashion standards often have negative effects and reinforce social norms and stereotypes. Female roles and fashion trends are stereotyped worldwide, but they are rarely rigid. However, many in Eastern Asia, especially China, are concerned about this issue because cultural and media influences shape many stereotypes and perceptions about women’s physical appearances and social roles. People used to embrace their own beauty standards. However, modern society has adopted a standardised ideal, leading many to undergo extensive plastic surgery procedures like nose bridge enhancement, V-shaped face, skin lightening, and double eyelids. It seems like everyone is identical and can be easily replicated. Without inner beauty and values, outer beauty is just a decorative vase. Beauty, like anything else, is harmful in excess. Self-improvement and personal values should be prioritised before cosmetic enhancement. Through impact of social media, Chinese people set beauty standards and keep them for female generations .
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it