Theorizing Beauty Regimes: Indonesian Women Performing their Gender Ideology and Resistance through Makeup
Bibliographic record
Abstract
This article is about how Indonesian women talk about their beauty practices. They are aware how their beauty routines are often seen as banal and shallow but simultaneously essential to their gendered beings. However, this article argues that women are able to subvert the deprecating narratives of their beauty regimes into empowering ones while maintaining the same practices. Through their practices, they seem to conform to the beauty requirement in society. However, through their discourse, they present their beauty regimes with perspectives that put their free will and agency at the centre of their beauty regimes. The research used a sample of twenty-two Indonesian women aged from the mid-twenties to mid-sixties, to ask about beauty routines. Their answers are analyzed by using feminist discourse analysis to seek possibilities of subversion and empowerment. Another theoretical approach used in this research is the politics of everyday lives. The problematization of everyday practices allows for the deconstruction of ideology that perpetuates gendered norms of beauty. This research is significant because it provides a blueprint for further research on gender politics in the 21st century that focuses on everyday practices.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".