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Record W1968464649 · doi:10.5172/hesr.2012.21.1.69

‘Gaining the right amount for my baby’: Young pregnant women’s discursive constructions of health

2012· article· en· W1968464649 on OpenAlexaffabout
Emma Amanda Harper, Geneviève Rail

Bibliographic record

VenueHealth Sociology Review · 2012
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsConcordia UniversityUniversity of Ottawa
Fundersnot available
KeywordsConstruct (python library)Gender studiesHealth promotionSociologyCritical discourse analysisDiscourse analysisObesityProject commissioningPublishingPublic healthMedicinePolitical scienceNursingLaw

Abstract

fetched live from OpenAlex

In Canada, obesity is increasingly emphasised as a ‘risk’ to the health of mother and foetus. At a time when pregnant women are under greater pressure to personally uphold the health of their foetus, understanding the impact of the discourse surrounding obesity and health on young pregnant women is critical. Using a feminist poststructuralist discourse analysis, we explore how pregnant young women construct their subjectivities either within dominant discourse on health and obesity or possibly resistant discourses. Open-ended interviews were conducted with 15 pregnant women between the ages of 18 and 28, coming from various socioeconomic and educational backgrounds in the Ottawa region. The analysis reveals that these women constitute themselves as complex, fragmented subjects who at times construct themselves within alternative and resistant discourses but generally reproduce dominant discourses of obesity, of individual and moral responsibility for health, and of maternal responsibility for foetal health. Implications for health promotion and policy strategies are discussed.

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)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.731
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.119
GPT teacher head0.501
Teacher spread0.382 · 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
GenreReview

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

Citations32
Published2012
Admission routes2
Has abstractyes

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