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Record W2542736829 · doi:10.1111/1467-9566.12518

A narrative analysis of the birth stories of early‐age mothers

2016· article· en· W2542736829 on OpenAlexafffundabout
Anna Carson, Cathy Chabot, Devon Greyson, Kate Shannon, Putu Duff, Jean Shoveller

Bibliographic record

VenueSociology of Health & Illness · 2016
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
FundersCanadian Institutes of Health ResearchUniversity of British Columbia
KeywordsNarrativeGender studiesNarrative inquiryIdentity (music)Social identity theoryNegotiationPsychologyDevelopmental psychologySocial classSociologySocial psychologySocial groupLiteratureSocial sciencePolitical scienceArtAesthetics

Abstract

fetched live from OpenAlex

The telling of birth stories (i.e. stories that describe women's experiences of giving birth) is a common and important social practice. Whereas most research on birth narratives reflects the stories of middle-class, 'adult' women, we examine how the birth stories told by early-age mothers interconnect with broader narratives regarding social stigma and childbearing at 'too early' an age. Drawing on narrative theory, we analyse in-depth interviews with 81 mothers (ages 15-24 years) conducted in Greater Vancouver and Prince George, Canada, in 2014-15. Their accounts of giving birth reveal the central importance of birth narratives in their identity formation as young mothers. Participants' narratives illuminated the complex interactions among identity formation, social expectations, and negotiations of social and physical spaces as they narrated their experiences of labour and birth. Through the use of narrative inquiry, we examine the ways in which re-telling the experience of giving birth serves to situate young mothers in relation to their past and future selves. These personal stories are also told in relation to a meta-narrative regarding social stigma faced by 'teenage' mothers, as well as the public's 'gaze' on motherhood in general - even within the labour and delivery room.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.377
Teacher spread0.339 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations55
Published2016
Admission routes3
Has abstractyes

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