Autoethnography of a Pregnant Doula: An Anthropological Investigation of Birth Experiences During the COVID-19 Pandemic in Ontario and Quebec
Bibliographic record
Abstract
The COVID-19 pandemic has exposed weaknesses in the existing systems and institutions people depend on in all areas of life. Birth is no exception. This research shows that COVID-19 replicated dominant North American cultural scripts treating birth as a risky and stressful medical event. It goes further to explore how birthers themselves described their experiences. Drawing on autoethnographic reflections, ethnographic interviews and a WhatsApp group chat, this thesis documents the nuance in predominantly middle class, cis-gendered women’s experiences giving birth in Ontario and Quebec during the pandemic. It uncovers the overarching non-birther centric nature of local birth culture and argues for a more balanced view of the advantages and disadvantages of giving birth during a pandemic. The research highlights the increased labor women were burdened with but also points to the ‘things that worked’ for people giving birth during a pandemic. This study contributes to the broader literature on anthropology of birth by offering in depth autoethnographic reflections to understand the complex phenomenon of pandemic births.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".