Fostering Family–School–Community Partnership With Parents of Students With Developmental Disabilities: Participatory Action Research With the 3D Sunshine Model
Bibliographic record
Abstract
Education studies have repeatedly emphasized the crucial contribution of family–school–community partnership to children’s academic and educational success, as well as to improving organizations and systems. Such partnership becomes even more complex when the child presents needs in several areas of development. In this context, it is essential that researchers work collaboratively with actors in the field, first to identify barriers to family–school–communi- ty partnership, and then to support the implementation of levers to overcome those barriers. In this research, we built upon an existing model, the Sunshine Model, and tested our enhanced model in vivo in three specialized schools in greater Montreal serving adolescents with developmental disabilities. Opera- tionalization of the adapted model through participatory action research shows great promise for supporting professionals, not only in specialized but also in inclusive school settings, in grasping the multilevel dimensions—types and diversity of activities, partnership principles, interactional contextual factors— that facilitate or impede family–school–community partnership.
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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 | 0.017 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".