Pregnancy loss in lesbian and bisexual women: an online survey of experiences
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
BACKGROUND: Although pregnancy loss is a distressing health event for many women, research typically equates women's experiences of pregnancy loss to 'married heterosexual women's experiences of pregnancy loss'. The objective of this study was to explore lesbian and bisexual women's experiences of miscarriage, stillbirth and neonatal death. METHODS: This study analysed predominantly qualitative online survey data from 60 non-heterosexual, mostly lesbian, women from the UK, USA, Canada and Australia. All but one of the pregnancies was planned. Most respondents had physically experienced one early miscarriage during their first pregnancy, although a third had experienced multiple losses. RESULTS: The analysis highlights three themes: processes and practices for conception; amplification of loss; and health care and heterosexism. Of the respondents, 84% conceived using donor sperm; most used various resources to plan conception and engaged in preconception health care. The experience of loss was amplified due to contextual factors and the investment respondents reported making in impending motherhood. Most felt that their loss(es) had made a 'significant'/'very significant' impact on their lives. Many respondents experienced health care during their loss. Although the majority rated the overall standard of care as 'good'/'very good'/'outstanding', a minority reported experiencing heterosexism from health professionals. CONCLUSIONS: The implications for policy and practice are outlined. The main limitation was that the inflexibility of the methodology did not allow the specificities of women's experiences to be probed further. It is suggested that both coupled and single non-heterosexual women should be made more visible in reproductive health and pregnancy loss research.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| 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