Persistence and Proliferation: Integrating Community-Engaged Scholarship into 59 Departments, 7 Units, and 1 University Academic Promotion and Tenure Policies
Bibliographic record
Abstract
Choosing how to recognize community-engaged scholarship in promotion and tenure policies so that it is assessed accurately and fairly remains a relatively new and ongoing challenge for institutions of higher education. This case study examines how one U.S. research university integrated recognition of community-engaged scholarship across all levels of policy, including university, unit, and department. The terms used within and across policies reveal that while some terms were perpetuated across policies, many more terms proliferated across policies. Using organizational change and signaling theories, as well as the Democratic Civic Engagement Framework, analysis raises questions and insights regarding the use of both specificity and ambiguity when choosing and defining terms, and the use of terms across faculty roles of teaching, research/creative activity, and service to signal and address legitimacy of community-engaged scholarship within a larger context of institutional values.
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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 | 0.017 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".