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Record W2281390284 · doi:10.1111/ajr.12214

Birthing in rural <scp>S</scp>outh <scp>A</scp>ustralia: The changing landscape over 20 years

2015· article· en· W2281390284 on OpenAlexaboutno aff
Linda Sweet, V. Boon, Vanessa Brinkworth, Sarah Sutton, Allison F. Werner

Bibliographic record

VenueAustralian Journal of Rural Health · 2015
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsResidenceUnit (ring theory)Rural areaQuarter (Canadian coin)Place of birthPresentation (obstetrics)MedicineChild bearingHealth facilityGeographyBirth orderPregnancyDemographySocioeconomicsFamily medicineHealth servicesPopulationEnvironmental healthPsychologyObstetricsSociology

Abstract

fetched live from OpenAlex

OBJECTIVE: To map trends in the maternity service availability for rural women in South Australia and identify the frequency of women birthing outside of their region of residence. DESIGN: A retrospective review of birth location for rural South Australian women from 1991 to 2010. SETTING: Rural maternity units in South Australia. PARTICIPANTS: Birthing statistics from the Pregnancy Outcomes Statistics Unit in South Australia MAIN OUTCOME MEASURES: Rural birth statistics, including place of birth in relation to place of residence and location of maternity units. RESULTS: Over 60% of maternity units across rural South Australia have closed since 1991. There has been a rise in the percentage of women birthing away from their usual region of residence, rising from 18% in 1991-1995 to 24% in 2006-2010. CONCLUSIONS: This study has revealed that almost one quarter of all women residing in rural South Australia relocate to another area to give birth. This is a significant concern for rural women and their families through the expectation of separation, and for the local health services who might now not have the facilities and skills to manage an unplanned maternity presentation. These concerns need to be considered and addressed in order to provide safe and effective care for child-bearing women regardless of location.

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)0.002
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 score0.136
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.055
GPT teacher head0.354
Teacher spread0.300 · 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

Citations21
Published2015
Admission routes1
Has abstractyes

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