How can research partnerships better support local development? Stakeholder perceptions on an approach to understanding research partnership outcomes in the Canadian Arctic
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 Understanding the benefits and outcomes of Canada's public investment in Arctic science and associated community–researcher partnerships represents a significant challenge for government. This paper presents a capital assets-based approach to conceptualising northern research partnership development processes and assessing the potential outcomes. By more explicitly considering the pre- and post-partnership asset levels (that is, social, human, physical, financial and natural assets) for different collaborators, the potential benefits and challenges associated with community–researcher partnerships can be collaboratively assessed. In order to help refine this approach, we conducted a survey of those involved in developing and maintaining community–researcher partnerships across Arctic Canada. Results indicate that the proposed approach could be useful for research funding agencies seeking to better understand partnership outcomes and promote more effective community–researcher interactions. Challenges include adequately capturing the qualitative nature of different capital assets, pointing to future research and policy needs. Better understanding the role of research in northern development has the potential to improve northern research, policy and practice.
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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 | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.031 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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