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Record W4367030204 · doi:10.3138/cjpe.0015.011

Prenatal Education Class Attendance with Additional Insights Provided by a Geographic Information System

2001· article· en· W4367030204 on OpenAlexvenueno aff
Brenda Suggett, Pamala D. Larsen

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2001
Typearticle
Languageen
FieldDecision Sciences
Topicdemographic modeling and climate adaptation
Canadian institutionsnot available
Fundersnot available
KeywordsAttendancePopulationClass (philosophy)DemographySet (abstract data type)GeographyMedicineFamily medicinePsychologyEnvironmental healthComputer scienceEconomic growthSociology

Abstract

fetched live from OpenAlex

Abstract: In reaction to an unexplained 25% drop in prenatal class attendance, the Regina Health District (RHD) set out to determine the proportion of women not attending, where these women live, and the reasons for not participating. The study included a cross-sectional survey of 1157 new mothers and the use of MapInfo software. The results showed that many of those who attend RHD programs live in low-income areas, a targeted population. Yet there was evidence of a significant group of mothers in these same areas who were still not attending. Strategies for better serving first-time mothers were created by examining characteristics of the clusters of non-attenders and potential barriers, such as time of day and ease of geographic access. Methods for promoting the prenatal classes were also updated based on survey feedback.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.076
GPT teacher head0.346
Teacher spread0.270 · 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 designOther design
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
Published2001
Admission routes1
Has abstractyes

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