Stories of Grief and Hope: Queer Experiences of Reproductive Loss.
Bibliographic record
Abstract
When parents and researchers talk of queer perspectives on pregnancy, birth and parenting, an issue that we often avoid is queer experiences of loss during pregnancy, birth or adoption. Drawing on data from an online survey of 60 non-heterosexual women from the UK, USA, Canada and Australia and 40 interviews with LGBTQ people who had experienced loss in the USA and Canada, we argue that for LGBTQ people, challenges in achieving conception and adoption amplify stories of loss, and that both grief and hope suffuse stories of reproductive loss. We identify several factors, such as the severely under-researched experiences of non-gestational or “social” parents, financial concerns about loss following assisted reproduction or adoption expenses, and fears of further marginalization as non-normative parents. These issues are particular, if not unique to queer experiences of reproductive loss. As most research and existing resources for support have focused heavily on the experiences of married, heterosexual (primarily white, middle-class) women, we conclude by suggesting ways for medical professionals and support groups to better serve LGBTQ people following reproductive loss.
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.
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".