Birthing While Black During Emergencies
Bibliographic record
Abstract
My graduate studies have built on my extensive experience as a maternal healthcare practitioner, with a particular focus on the intersections of health and racial inequity, sexual violence, and LGBTQ2S+ issues. My research focuses on reproductive justice during emergencies, including the COVID-19 global pandemic. Specifically, I am examining the experiences of Black Canadians who are pregnant and/or giving birth during the pandemic. It is well-documented in the United States that Black women have disproportionately negative maternal health and childbirth outcomes. These inequitable outcomes have led to a response from a reproductive justice movement that works to redress negative outcomes for Black women as a result of racism. In Canada, there has been a push to collect race-based data to identify health inequities, and advocates have pushed for Public Health agencies to name anti-Black racism as a public health issue. Nevertheless, despite the recognition that Black women have more negative reproductive outcomes due to systemic anti-Black racism, Canada lags behind other Western countries in documenting the impact of anti-Black racism on maternal and infant health. My research responds to this immense gap by doing exploratory, qualitative research with Black mothers/individuals, and birth workers in order to paint a picture of their experiences. My work will contribute to an understanding of the impact of anti-Black racism on maternal health in Canada, especially during a major public health crisis such as the COVID-19 pandemic that is disproportionately impacting the Black community. The final outcome of my plan of study is a portfolio that is housed on a website that I built (www.birthingwhileblack.ca). #BirthingWhileBlack in Canada is a hub for the rough cut of my documentary film ‘Birthing while Black during COVID-19,’ which consists of interviews with Black mothers who were pregnant or gave birth during the pandemic, and Black birth workers; a manuscript submitted for publication ‘Unpacking emergency response: anti-Black racism and other barriers faced by pregnant and lactating asylum claimants in Quebec, Canada’; the development of the conceptual framework of ‘First Food Sovereignty’ as a policy tool that centers the most vulnerable; and the blueprint series, an art installation. What these stories inform us, that is new, is that Black families in Canada are giving birth in a state of survival mode because they are acutely aware of the threat of anti-Black violence existing in the healthcare system. Their trauma responses consist of going into “freeze” mode, making themselves small and invisible, silencing themselves, and not bringing attention to themselves. Even in the face of a pandemic, what they fear most for themselves and their children, is systemic anti-Black racism.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".