Building a framework for evaluation of Fetal Alcohol Spectrum Disorder prevention and support programs: A collaborative Canadian project
Bibliographic record
Abstract
Rutman, D., Poole, N., Hume, S., Hubberstey, C., & Van Bibber, M. (2014). Building a framework for evaluation of Fetal Alcohol Spectrum Disorder prevention and support programs: A collaborative Canadian project. The International Journal Of Alcohol And Drug Research, 3(1), 81-89. doi:10.7895/ijadr.v3i1.122Aims: This article discusses a Canadian project that is designed to identify promising evaluation methods and create common evaluation frameworks for FASD prevention programs serving pregnant women and mothers, and FASD supportive intervention programs serving youth and adults living with FASD. A social determinants of health perspective guided the project.Design: The project has employed a mixed-methods approach including a literature search, documentary review, and an iterative set of consultations with program providers, program managers, government managers and funders, researchers, and evaluators in the context of their work across Canada and internationally.Results: The project’s processes led to the development of three visual “maps” comprised of concentric rings that depict theoretical foundations; activities and approaches; formative outcomes; and participant, community and systemic outcomes. The three visual frameworks depict evaluation of 1) FASD prevention programs; 2) FASD support programs; and 3) FASD programs in Aboriginal communities.Conclusions: The development of visual maps to depict common evaluation frameworks promotes individual and collective action towards applying the frameworks on the part of community-based services and governments across Canada, on the service and systemic levels. Program providers, researchers, and system planners have indicated that the maps have wide-ranging applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.260 | 0.124 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.026 | 0.022 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.008 | 0.018 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".