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Record W4399385036 · doi:10.1111/birt.12828

“I have to listen to them or they might harm me” and other narratives of why women endure obstetric violence in Bihar, India

2024· article· en· W4399385036 on OpenAlexaff
Kaveri Mayra, Zoë Matthews, Jane Sandall, Sabu S. Padmadas

Bibliographic record

VenueBirth · 2024
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsUniversity of British Columbia
FundersBurdett Trust for NursingParkes Foundation
KeywordsNarrativeChildbirthGender studiesQualitative researchHealth careHarmNursingHarassmentMedicinePsychologySociologySocial psychologyPolitical sciencePregnancySocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Evidence suggests that obstetric violence has been prevalent globally and is finally getting some attention through research. This human rights violation takes several forms and is best understood through the narratives of embodied experiences of disrespect and abuse from women and other people who give birth, which is of utmost importance to make efforts in implementing respectful maternity care for a positive birthing experience. This study focused on the drivers of obstetric violence during labor and birth in Bihar, India. METHODS: Participatory qualitative visual arts-based method of data collection-body mapping-assisted interviews (adapted as birth mapping)-was conducted to understand women's perception of why they are denied respectful maternity care and what makes them vulnerable to obstetric violence during labor and childbirth. This study is embedded in feminist and critical theories that ensure women's narratives are at the center, which was further ensured by the feminist relational discourse analysis. Eight women participated from urban slums and rural villages in Bihar, for 2-4 interactions each, within a week. The data included transcripts, audio files, body maps, birthing stories, and body key, which were analyzed with the help of NVivo 12. FINDINGS: Women's narratives suggested drivers that determine how they will be treated during labor and birth, or any form of sexual, reproductive, and maternal healthcare seeking presented through the four themes: (1) "I am admitted under your care, so, I will have to do what you say"-Influence of power on care during childbirth; (2) "I was blindfolded … because there were men"-Influence of gender on care during childbirth; (3) "The more money we give the more convenience we get"-Influence of structure on care during childbirth; and (4) "How could I ask him, how it will come out?"-Influence of culture on care during childbirth. How women will be treated in the society and in the obstetric environment is determined by their identity at the intersections of age, class, caste, marital status, religion, education, and many other sociodemographic factors. The issues related to each of these are intertwined and cross-cutting, which made it difficult to draw clear categorizations because the four themes influenced and overlapped with each other. Son preference, for example, is a gender-based issue that is part of certain cultures in a patriarchal structure as a result of power-based imbalance, which makes the women vulnerable to disrespect and abuse when their baby is assigned female at birth. DISCUSSION: Sensitive unique feminist methods are important to explore and understand women's embodied experiences of trauma and are essential to understand their perspectives of what drives obstetric violence during childbirth. Sensitive methods of research are crucial for the health systems to learn from and embed women's wants, to address this structural challenge with urgency, and to ensure a positive experience of care.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.341
Teacher spread0.295 · 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 teacher head, not a consensus.

Study designObservational
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

Citations4
Published2024
Admission routes1
Has abstractyes

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