Queering reproductive access: reproductive justice in assisted reproductive technologies
Bibliographic record
Abstract
BACKGROUND: Advancements in assisted reproductive technologies (ART) and policy development have enabled more people to have biologically related children in Canada. However, as ART continues to focus on infertility and low fertility of heterosexual couples, ART access and research has been uneven towards meeting the reproductive needs of lesbian, gay, bisexual, transgender, queer, two-spirit, intersex, and asexual (LGBTQ2SIA +) people. Furthermore, experiences of reproduction are impacted by intersectional lived realities of race, gender, sexuality, and class. This commentary utilizes a reproductive justice (RJ) framework to consider reproductive access for LGBTQ2SIA + Black, Indigenous, and people of colour (BIPOC), while simultaneously engaging through a critical lens RJ has on ART. An RJ framework considers the constitutive elements of reproductive capacity and decision making that are not often at the forefront of reproductive health discussions. Additionally, this commentary discusses reproductive rights violations and reproductive violence such as coerced and forced sterilizations that have and are currently occurring in Canada. This article considers systems of access and structures of regulation that seek to control the reproductive capacities of marginalized communities, while empowering accessibility and upholding white supremacy and heteronormativity. In thinking through research and access in ART, who are ART users and whose reproduction is centered in research and access in Canada? CONCLUSION: A reproductive justice framework is urgently needed to address inequities of sexual and reproductive health access in Canada.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.052 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.010 |
| 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".