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Record W4308772656 · doi:10.1111/maq.12739

Re‐centering Relationships: Obstetric Violence, Health Care Rationalities, and Pandemic Childbirth in Canada

2022· article· en· W4308772656 on OpenAlexaboutno aff
Kathleen Rice

Bibliographic record

VenueMedical Anthropology Quarterly · 2022
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsChildbirthSafeguardingPersonhoodContext (archaeology)Health careNursingNarrativePandemicMaternity careCriminologySociologyMedicinePsychologyPolitical sciencePregnancyLawCoronavirus disease 2019 (COVID-19)Geography

Abstract

fetched live from OpenAlex

Emerging evidence suggests that the COVD-19 pandemic is eroding childbirth rights. Drawing on narratives of women who gave birth in Canada during the pandemic, this article exposes a paradox in that policies aimed at limiting interpersonal contact implicitly acknowledge the connection between health, well-being, and the social context of people's lives, yet they frame this relationality as a liability to be eliminated. They do this despite the many benefits that social support is known to confer for pregnancy and childbirth. I suggest that obstetric violence theory could be expanded to include the perinatal health care system's failure to consider the well-being of pregnant and birthing persons as necessarily interdependent with that of close others. Conscientiously and routinely making the safeguarding of these relationships a priority in perinatal health care planning may strengthen existing health care systems against certain forms of obstetric violence. [childbirth, COVID-19, obstetric violence, relational personhood, Canada].

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.949

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0330.014
Scholarly communication0.0060.002
Open science0.0020.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.027
GPT teacher head0.327
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMedical Anthropology QuarterlySame topicMaternal and Perinatal Health InterventionsFrench-language works237,207