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Record W4400615205 · doi:10.22374/cjmrp.v13i2.89

Perinatal Outcomes for Four Toronto Midwifery Practices: Exploring Best Practices for Normal Birth

2024· article· en· W4400615205 on OpenAlexaboutno aff
Vicki Van Wagner, Mary Sharpe, Judy L. Rogers, Elizabeth Brandeis, Andrea Levy, Tia Sarkar, Bridget Lynch, Kristen Dennis, Leah Klein, Jenna Robertson

Bibliographic record

VenueCanadian Journal of Midwifery Research and Practice · 2024
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsObstetricsPerinatal mortalityBest practiceHome birthMedicineNursingPregnancyChildbirthPolitical scienceFetus

Abstract

fetched live from OpenAlex

This study explores outcomes from four Toronto midwifery practices from 2003 to 2007, using data from the Midwifery Outcomes Database to look at similarities and differences between the practices and with provincial averages. The goals of our project included establishing a university/community partnership with the participating practices, which included Ryerson and McMaster University faculty members; improving capacity among midwives with using a provincial database; and producing a comprehensive perinatal outcomes report for midwifery practices that could be used for internal review and for presentation at interprofessional forums such as hospital rounds and interprofessional conferences. A comparative analysis between the practices and with the provincial midwifery data showed several trends, including an increased incidence of late maternal age, low rates of intervention, and high rates of home birth. Our research raises questions about scope of practice and best practices for supporting normal birth. This article has been peer reviewed.

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)0.006
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.004
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 head0.544
GPT teacher head0.531
Teacher spread0.013 · 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
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
Published2024
Admission routes1
Has abstractyes

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