Partnerships for Knowledge Building: An Emerging Model
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
Knowledge Building is approached in this study from an organizational perspective, with a focus on the nature of school-university-government partnerships to support research-based educational innovation. The paper starts with an overview of what is known about effective partnerships and elaborates a conceptual framework for Knowledge Building partnerships based on a review of literature and two case studies of school-university-government partnerships. In one case, a Ministry of Education wanted to bring more vitality into schools of small remote villages, and in the other case another Ministry of Education wanted to renew its school-based international cooperation profile. Emerging from this work is a three-component model for going to scale with Knowledge Building partnerships: Knowledge Building as a shared vision; symmetric knowledge advancement; and multi-level, research-based innovation. Characteristics of, and conditions for, effective partnerships for Knowledge Building are elaborated, and an emerging model is developed to help communities establish effective partnerships and contribute to this evolving model.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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