Engaged Scholarship in Tenure and Promotion: Autoethnographic Insights from the Fault Lines of a Shifting Landscape
Bibliographic record
Abstract
Pre-and post-tenure faculty face immense pressure to meet professional expectations and requirements from their colleagues and disciplines.Faculty involved in community-campus engagement (CCE) for social change face additional demands to maintain relationships and continue their interventions.We present a collective autoethnography from a Canadian context reflecting on experiences as CCE faculty at various stages of tenure and promotion (T&P).We draw from our efforts working together on a pan-Canadian CCE research project, Community First: Impacts of Community Engagement (CFICE).From these experiences, we identify tensions within T&P processes and argue the need for highly contextualized narratives when faculty present their collaborative efforts, research processes with community partners, and community impact in their multiple faculty roles.From these kinds of narratives, the intra-and inter-institutional gaps, connections and spaces become clearer, especially for tenured and increasingly senior faculty, to support culture change at the institutional level, thereby increasing the value and recognition of CCE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.026 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".