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Record W7039032576

Keeping the Canary singing: Maternity care plans and respectful home birth transfer

2021· other· en· W7039032576 on OpenAlexaboutno aff

Bibliographic record

VenueUTS ePRESS (University of Technology Sydney) · 2021
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicOrthoptera Research and Taxonomy
Canadian institutionsnot available
Fundersnot available
KeywordsMainstreamMaternity careHome birthOppressionHuman rightsHome ChildbirthNatural childbirthPlace of birth
DOInot available

Abstract

fetched live from OpenAlex

This book investigates why women choose ‘birth outside the system’ and makes connections between women’s right to choose where they birth and violations of human rights within maternity care systems.
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\nChoosing to birth at home can force women out of mainstream maternity care, despite research supporting the safety of this option for low risk women attended by midwives. When homebirth is not supported as a birthplace option, women will defy mainstream medical advice, and if a midwife is not available choose either an unregulated careprovider or birth without assistance. This book examines the circumstances and drivers behind why women nevertheless choose homebirth by bringing legal and ethical perspectives together with the latest research on high risk homebirth (breech and twin births), freebirth, birth with unregulated careproviders and the oppression of midwives who support unorthodox choices. Stories from women who have pursued alternatives in Australia, Europe, Russia, the UK, the US, Canada, the Middle East and India are woven through the research.
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\nInsight and practical strategies are shared by doctors, midwives, lawyers, anthropologists, sociologists and psychologists on how to manage the tension between professional obligations and women’s right to bodily autonomy. This book, the first of its kind, is an important contribution to considerations of place of birth and human rights in childbirth.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.012
GPT teacher head0.181
Teacher spread0.169 · 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 designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueUTS ePRESS (University of Technology Sydney)Same topicOrthoptera Research and TaxonomyFrench-language works237,207