Ambiguous Endings: A Feminist Sociological Approach to Women’s Stories of Discontinuing Medical Fertility Treatment in Canada
Bibliographic record
Abstract
This dissertation problematizes the dominant cultural view that assisted reproductive technologies (ART), such as in vitro fertilization and intrauterine insemination, are highly successful medical treatments that produce ‘miracle babies’. I preface this study by outlining the landscape of fertility clinics and ART legislation in Canada, emphasizing the murkiness of Canada’s data on ART use and efficacy. I then use a post-structural feminist theoretical lens to focus on women’s experiences of discontinuing medical fertility treatment in Canada. I interviewed 22 women who received various forms of fertility treatment in Canada and who were at various stages in relation to treatment (e.g. on a temporary break from treatment, left treatment indefinitely, had yet to decide whether to initiate treatment after a diagnosis). Using a sociological form of narrative analysis, I analyzed these stories and co-constructed eight narrative themes. Through these eight narrative themes, I demonstrate two things: first, that there are multifaceted ways in which women engage these technologies and ultimately leave, and secondly, that there are implicit gendered power relations at work within the fertility clinic that may make it more difficult for women to leave treatment when it is financially, emotionally, and physically beneficial for them to do so. I highlight the stories of these women and their differing life circumstances, including women across a broad age range (approximately 25 to 50 years of age), two women in self-identified queer relationships, and women with varying degrees of financial security, to elucidate the ambiguous character of ending treatment-- an experience that is often marginalized in the public-facing view of fertility treatment as a highly positive scientific innovation. Out of my interpretations I make eight recommendations for health providers, stakeholders and policymakers to improve fertility care in Canada and to make the experience of medical fertility treatment less physically, emotionally and financially distressing for users.
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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.078 | 0.054 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".