Non-Surgical Cosmetic Procedures: Older Women's Perceptions and Experiences
Bibliographic record
Abstract
This paper analyzes findings from in-depth interviews with 44 women aged 50-70 regarding their perceptions of and experiences with non-surgical cosmetic procedures such as Botox injections, laser hair removal, chemical peels, microdermabrasion, and injectable fillers. While 21 of the women had used a range of non-surgical cosmetic procedures, 23 women had not. The data are discussed in light of feminist theorizing on cosmetic surgery which has tended to ignore the experiences of older women and has been divided in terms of the portrayal of cosmetic surgery as either oppressive or liberating. We found that some of the women used the procedures to increase their physical attractiveness and self-esteem, others viewed the procedures as excessively risky, and still others argued that the procedures stemmed from the social devaluation of later life. Treatments that involved the alteration of the surface of the body tended to be viewed as less risky than the injection of foreign substances into the body.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".