Queer Tax: Examining 2SLGBTQ+ Black, Indigenous, and People of Colour's experiences of accessing assisted reproductive technologies
Bibliographic record
Abstract
The use of assisted reproductive technologies (ART) has risen steadily over the past two decades. In Canada, up to 25 % of assisted reproductive technologies (ART) users identify as Two-Spirit, lesbian, gay, bisexual, trans, and/or queer (2SLGBTQ+). Despite evidence of inequitable ART access for 2SLGBTQ+ communities, scant research has explored the intersectional experiences of 2SLGBTQ+ Black, Indigenous, and People of Colour (BIPOC). Theoretically grounded in reproductive justice and critical political economy, this study examines ART access and clinical experiences for 2SLGBTQ+ BIPOC communities. Interviews were conducted with BIPOC and 2SLGBTQ+ people who had undergone or were seeking ART in Ontario, Canada. Data analysis, guided by constructivist grounded theory and situational analysis, was coded using MAXQDA. The findings reveal structural powers and systemic inequalities shaping the ART process and parenthood. Participants identified four key barriers faced by 2SLGBTQ+ BIPOC families: (1) normative practices (re)produced through ART; (2) mandatory counselling as gatekeeping and disciplining; (3) regulation of known donor sperm augmenting legal, financial, and timeliness barriers; and (4) limited availability of Black, Indigenous, and People of Colour donor sperm. These intersectional barriers highlight the urgent need for ART providers to offer competent and inclusive care. Additionally, the study underscores the necessity for clinical policy reforms to challenge heteronormative and racist practices, ensuring equitable access and improving availability of BIPOC donor sperm for diverse family structures.
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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 | 0.017 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".