Enabling evidence-led collaborative systems-change efforts: an adaptation of the collective impact approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This article conveys the results of a three-year ethnographic study of a pan-Canadian community–university collaboration to prevent and end youth homelessness. The collaboration adapted aspects of a collective impact (CI) approach to pursue a large-scale shift in how youth homelessness is addressed in Canada. The objective of this article is to codify and share the model developed and implemented by the community–university collaboration as an opportunity for ongoing adaptation and learning among others undertaking similarly complex and collaborative systems-change efforts. Findings suggest a CI approach is unlikely to be suitable for large-scale innovation-oriented initiatives, and that context-specific adaptations of the model should be encouraged. To what is already known about collaborative multisectoral partnerships, this article reveals the importance of strategic information sharing, targeted and flexible research and knowledge mobilization efforts, and ongoing attentiveness to the relational dimensions of collaborative evidence-informed systems-change efforts.
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.
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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.009 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it