The Interpersonal Skills of Community-Engaged Scholarship: Insights From Collaborators Working at the University of Saskatchewan’s Community Engagement Office
Bibliographic record
Abstract
Perhaps more clearly than other research approaches, community-based research or engaged scholarship involves both technical skills of research expertise and scientific rigor as well as interpersonal skills of relationship building, effective communication, and moral ways of being. In an academic age concerned with scientific precision, cognitive skills, quantification, and reliable measurements, the interpersonal skills required for research—and particularly community-based research and engaged scholarship—demand growing importance and resources in contemporary discourse and practice. Focused around the University of Saskatchewan’s Community Engagement Office located in the inner city of Saskatoon, Saskatchewan, the authors draw on over 50 years of collective experience to offer critical reflections on the notion of interpersonal skills in community-engaged scholarship that manifest particularly in place-based contexts of Indigenous community partnerships. Overall, we argue that discourse and practice involving community-engaged scholarship must pay attention to the notion of interpersonal skills in various aspects and across multiple dimensions and disciplines. This approach is crucial to ensure that research is done effectively and ethically, that good quality data are produced from such research, that subtle, systematic forms of micro-aggression and oppression are minimized, and that community voices and knowledge have a meaningful and significant place in scholarship activities.
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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 | 0.092 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.089 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.000 | 0.026 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".