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Record W2347211091 · doi:10.18192/riss-ijhs.v1i1.1532

Portrayals of Childbirth: An Examination of Internet Based Media

2010· article· en· W2347211091 on OpenAlexaffvenue
Tiffany L Holdsworth-Taylor

Bibliographic record

VenueRevue interdisciplinaire des sciences de la santé - Interdisciplinary Journal of Health Sciences · 2010
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMisinformationMainstreamChildbirthThe InternetPsychologyEntertainmentSocial mediaObstetricsPregnancyMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

More pregnant women turn to reality-based television programs and the Internet than to prenatal classes. Scant research examines the portrayal of childbirth in these new media. Although its impact is unknown, we do know that up to 20% of pregnant women fear giving birth; consequences include avoiding pregnancy, termination, depression, and increased maternal morbidity. Overall internet content tended to be contradictory but largely reflected two categories: natural and mainstream, with two different portrayals of childbirth. Natural sources focused on eliminating fear, discrediting hospital births, and promoting ‘alternative’ options such as homebirth and midwifery. Mainstream sources reinforced fears, discredited home births, reported statistics from studies, and employed misinformation. Popular Internet sources tended to have the goal of educating whereas media uncovered in the purposive searches tended towards entertainment goals. Conflicting and misinformation from the Internet may entrench rather than assuage fears. Women may become confused and develop a heavily biased representation of birth. This could strongly impact a woman’s approach to and experience of birth.

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)0.020
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.008
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.052
GPT teacher head0.439
Teacher spread0.386 · 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

Citations1
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueRevue interdisciplinaire des sciences de la santé - Interdisciplinary Journal of Health SciencesSame topicGrief, Bereavement, and Mental HealthFrench-language works237,207