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Record W2136700127 · doi:10.1177/1049732314551058

Reenvisioning Success for Programs Supporting Pregnant Women With Problematic Substance Use

2014· article· en· W2136700127 on OpenAlexaff
Lenora Marcellus, Karen MacKinnon, Cecilia Benoit, Rachel Phillips, Camille Stengel

Bibliographic record

VenueQualitative Health Research · 2014
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsFormative assessmentProgram evaluationAddictionAbstinenceSubstance usePsychologyAlcoholics AnonymousProgram Design LanguageNursingMedical educationMedicinePsychiatryPedagogyPolitical science

Abstract

fetched live from OpenAlex

Community-based, integrated, primary care maternity programs for pregnant women affected by problematic substance use are emerging as effective models for engaging women affected by multiple health and social issues. Although addictions services have historically been evaluated by individual achievement of abstinence, new definitions of program success are required as addiction comes to be viewed as a chronic illness. We conducted a mixed-methods study to follow the formative development stages of a community-based program, identifying key evaluation indicators and processes related to this program, program team members, and women and families served. As this program model develops, it is critical that providers, community partners, and health system leaders collaborate to frame definitions of success in ways helpful for guiding program development.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0040.003
Open science0.0020.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.276
GPT teacher head0.523
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations44
Published2014
Admission routes1
Has abstractyes

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