Advancing Queer Reproductive Justice: Examining Access to Assisted Reproductive Technologies and Family Expansion for 2SLGBTQ+ Black, Indigenous, and People of Colour
Bibliographic record
Abstract
Scholarship on reproduction among Two-Spirit, lesbian, gay, bisexual, transgender, and queer (2SLGBTQ+) populations has emerged in recent years. Yet, scant research has examined the intersectional experiences of 2SLGBTQ+ Black, Indigenous, and people of colour (BIPOC) communities. To address this gap in literature, this qualitative study applied a reproductive justice and queer theory approach to investigate the experiences of reproductive access and family expansion for 2SLGBTQ+ BIPOC. The study was methodologically informed by a postmodern approach to grounded theory known as situational analysis (SA). Interviews were conducted in family units with 32 2SLGBTQ+ BIPOC and/or partners who accessed or considered accessing assisted reproductive technologies (ART) in Ontario, Canada. The study offers insights into the social and political factors that impact reproductive access, as well as implications for reproductive policy, clinical policy, and clinical practice reforms. Specifically, the study highlights interconnected normative structures of power such as heteronormativity, cisnormativity, racism, and colonialism that impact reproductive decision-making and access. Chapter 1 introduces the overall study by delineating the theoretical frameworks of reproductive just and queer theory, a critical review of the literature, and outline of the research design. Advancing a queer reproductive justice framework, Chapter 2 examines the social and political factors that constitute reproductive decision-making and access for 2SLGBTQ+ BIPOC such as race, gender, sexuality, culture, migration histories, and citizenship status. Chapter 3 investigates experiences of accessing ART at the fertility clinic and sperm banks to highlight the medical and legal processes of ART, as well as practice and policy implications. Chapter 4 focuses on the strategies that 2SLGBTQ+ BIPOC utilize to navigate fertility and reproductive health systems that embody and uphold dominant cultures and discourses around race, gender, and sexuality. Finally, Chapter 5 concludes the study with a discussion on contributions to theoretical, methodological, and substantive bodies of scholarship, as well as implications for policy and practice in the areas of ART access and 2SLGBTQ+ reproduction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".