Community Engagement and Participation in Collective Impact Initiatives
Bibliographic record
Abstract
There is no question that large social problems like poverty and educational inequality are difficult to solve. Many groups throughout the nation and world are adopting the framework of collective impact in efforts to solve these problems together, as opposed to working in individual silos yielding only isolated impact. However, the framework that is used to align high-level leaders and resources has been criticized for being too “top down” and perhaps leaving out the actual people who are directly affected by the interventions. This report examines whether and how collective impact initiatives foster the participation and engagement of the very people that the initiatives purport to affect. It presents three case studies of initiatives that have had great success solving a social problem in their communities: Shape Up Somerville (childhood obesity and community health in Massachusetts); the Communities That Care Coalition of Franklin County and the North Quabbin (teen substance abuse in rural Massachusetts); and Vibrant Communities and the Hamilton Roundtable for Poverty Reduction (poverty reduction in Ontario, Canada). Analysis of these collective impact initiatives through the lens of community engagement and participation finds that not all groups have been intentional about creating structures that, from the beginning, meaningfully involve affected populations at the leadership level. However, some groups are moving toward greater inclusion, and do rely on community members for consultation and implementation of strategies. To do so, initiatives must consider that the deepest forms of engagement require considerable capacity building and support of new leaders, and that groups must take time to develop trusting relationships at all levels of engagement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".