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Record W1557237650 · doi:10.3138/cjpe.30.1.79

Toward an Evaluation Framework for Community-Based FASD Prevention Programs

2015· article· en· W1557237650 on OpenAlexaffvenueabout
Carol Hubberstey, Deborah Rutman, Sharon Hume, Marilyn Van Bibber, Nancy Poole

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2015
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsBritish Columbia Centre of Excellence for Women's HealthUniversity of Victoria
Fundersnot available
KeywordsFormative assessmentPerspective (graphical)Product (mathematics)PsychologyProgram evaluationKnowledge managementComputer scienceMedical educationMedicineMathematics educationArtificial intelligencePolitical science

Abstract

fetched live from OpenAlex

Abstract: This article discusses creation of common evaluation frameworks for FASD-related programs. The project was guided by a social determinants of health perspective and included a literature search and consultations across Canada to help refine and confirm the final product. The end result was development of three visual maps: FASD prevention programs, FASD support programs, and FASD programs in Aboriginal communities. Each map comprises concentric rings showing theoretical foundations; activities and approaches; and formative (program), participant, and community/systemic outcomes. The project website provides tools and indicators. The visual maps have wide-ranging applications that go beyond evaluation of FASD programs.

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)0.310
metaresearch head score (Gemma)0.167
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.310
Threshold uncertainty score0.851

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3100.167
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0270.013
Science and technology studies0.0110.018
Scholarly communication0.0270.016
Open science0.0070.015
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.350
GPT teacher head0.446
Teacher spread0.096 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations4
Published2015
Admission routes3
Has abstractyes

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