Bibliographic record
Abstract
This study investigated how women interpret and experience menstrual suppression, the long-term limiting of women's menstrual cycles using hormonal interventions such as oral contraceptives (birth control pills) or Depo-Provera injections. Asserting that monthly menstruation is detrimental to both women's health and their lifestyles, some physicians and health care professionals are recommending menstrual suppression to women. Critics argue that menstrual suppression is unhealthy and has the potential to harm women physically, emotionally, and psychologically, as menstruation is commonly regarded as a key aspect of being female (Chrisler, 2000). To date, the research on menstrual suppression includes clinical studies and psychological investigations of women's knowledge and openness to menstrual suppression. However, the existing research has not investigated the relationships between women's feelings about their bodies, their senses of femininity and sexuality, their lived menstrual cycle experiences, and their perceptions of menstrual suppression. Building on the extant research, this study used in-depth interviews with 12 women aged 18 to 36 to examine the meanings that women give to menstruation and menstrual suppression. My findings suggest that women's experiences and perceptions of menstrual suppression are complex and bound up with issues of sexuality, femininity, body image, and socialization. The majority of the women described menstruation as a nuisance, embarrassing, "gross", and also as a marker of womanhood. The women also argued that Western culture promoted negative views of menstruation, and they described how they made sense of these menstrual taboos. The women maintained that they would consider menstrual suppression for reasons of convenience, to please their sexual partners, and to feel more positively about their bodies. Reasons to avoid suppressing menstruation included fears about compromising one's health, worries about altering the "natural" menstrual cycle, and uneasiness with pharmaceutical products in general. The findings are discussed in relation to feminist theorizing about menstrual culture and body work. The findings from my research underscore the need for more thorough clinical research on menstrual suppression. As menstrual suppression continues to be recommended to women as a healthier option than monthly menstruation, it is imperative that we understand the effects of menstrual suppression on women's health and lives.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".