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Record W2128232058 · doi:10.1177/0011392115590075

Always, already-medicalized: Women’s prenatal knowledge and choice in two Canadian contexts

2015· article· en· W2128232058 on OpenAlex
Claudia Malacrida

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCurrent Sociology · 2015
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsUniversity of Lethbridge
FundersAlberta Innovates - Health Solutions
KeywordsMedicalizationChildbirthSociologySubject (documents)Gender studiesPsychologyPregnancyPsychiatry

Abstract

fetched live from OpenAlex

Women’s childbirth choices occur within contested discourses about medical, natural, and woman-centered births. All three perspectives, to slightly differing degrees, presume an autonomous female subject who makes childbirth choices. Thus informed choice is posed as a crucial corrective to the increasing medicalization of childbirth. This article employs a critical feminist analysis to examine how women learn about childbirth and make choices long before the moment of informed choice. Interviews with 40 pregnant and recently birthing women in two cities in Alberta, Canada illustrate how media, family and friends, and prenatal courses comprised core pre-birth knowledge systems informing women’s decision-making. The interviews exposed how medicalization is naturalized in these knowledge systems, so that women approached their actual births with an already-medicalized set of perceptions. This already-medicalized knowledge foreclosed women’s choices, a finding that complicates arguments over improving informed choice during childbirth as a means of reducing childbirth medicalization.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.970

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)0.0010.000

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 head0.077
GPT teacher head0.434
Teacher spread0.358 · 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