Navigating the Paradoxes of Engaged Research to Address Grand Challenges
Bibliographic record
Abstract
Abstract Academic/practitioner partnerships offer powerful opportunities to address grand challenges. Yet, effectively implementing academic/practitioner partnerships triggers ongoing tensions between rigor and relevance. This chapter draws on autoethnographic data exploring our own research partnership between several of the authors and Shorefast, a social enterprise seeking to regenerate rural communities. Three key findings emerged from our analysis. First, we found that, over time, the tension between rigor and relevance continually resurfaced through the process of partnering. Second, the practices that the partners adopted to navigate rigor and relevance paradoxes were themselves paradoxical, which advances process research “with” rather than “on” practitioners. Third, even as these paradoxical practices addressed underlying tensions, new tensions continually emerged. The success of this partnership therefore depended on sustained commitments to the partnership and ongoing trust building to deepen the relationships and generate new insights and approaches. These findings contribute to a growing body of research on engaged scholarship to address grand challenges.
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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 | 0.052 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.060 |
| Scholarly communication | 0.033 | 0.027 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".