From Suspicion and Accommodation to Structural Transformation: Enhanced Scholarship through Enhanced Community-University Relations
Bibliographic record
Abstract
While substantial efforts are being made in some universities to democratize the production, ownership, and use of knowledge through partnership with the community, significant barriers to community-university partnership persist, maintained through inequitable research relations, reductionist definitions of knowledge, and disincentives for faculty who are interested in community-based scholarship. The perseverance of this disconnect, we argue, is indicative of an existential aversion to community that lies deep within the psyche of the university. We liken the aversion to that of a disgust response, a social response that creates distance from that which is perceived to be dangerous, which in this case serves to preserve the university’s privileged status as knowledge producer. In this paper we bring forward arguments for the importance of community-engaged scholarship to the university’s civic role, to the pursuit of knowledge, and to the principles of democracy. We highlight promising advances in how some universities are accommodating community partnership within their definitions of scholarship and academic production, and, drawing upon Gordon’s theory of structural transformation and Bourdieu’s conceptualization of agency and habitus, we consider how such changes might be brought about at a deeper, structural level within the university.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.021 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.033 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".