Waterloo Better Beginnings as a Transformative Prevention Project: Impacts on Children, Parents, and the Community
Bibliographic record
Abstract
Better Beginnings Waterloo (BBW) is an ecological, community-driven, prevention program for children aged 4–8 and their families. BBW was implemented in two low-income communities with high percentages of visible minorities. Data on Grade 1–2 children and their parents (the baseline comparison group) were gathered through parent interviews (n = 34) and teacher reports (n = 68) in 2015, prior to BBW programs, and in the period 2018–2019, the same data were collected through parent interviews (n = 47) and teacher reports (n = 46) for children and parents participating in programs (the BBW group). As well, qualitative, open-ended individual interviews with parents (n = 47) and two focus groups were conducted in the period 2018–2019. Children in the BBW cohort were rated by their teachers as having a significantly lower level of emotional and behavioural problems than those in the baseline sample; parents in the BBW cohort had significantly higher levels of social support than parents in the baseline cohort; BBW parents rated their communities significantly more positively than parents at baseline. The qualitative data confirmed these findings. The quantitative and qualitative short-term findings from the BBW research showed similar positive impacts to previous research on program effectiveness, thus demonstrating that the Better Beginnings model can be successfully transferred to new communities.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".