You’re Getting Two For One With Me: Difficult New Sites Of Community Engagement Leadership Within Higher Education
Bibliographic record
Abstract
The emerging literature on community engagement professionals (Dostilio), who occupy a 'third space' (Whitchurch) between academics and professionals within higher education, has helped construct a potentially unifying identity among staff leading community engagement activity within contemporary post-secondary institutions. This presentation critically engages this literature, and profiles the professional identities of Australian and Canadian postsecondary staff leading the adaptation and adoption of the elective Carnegie Classification for Community Engagement in their institutions. Drawing from interview data of 15 staff responsible for the Carnegie Pilot within their institutions across both Australia and Canada, and employing a narrative inquiry method sensitive to feminist analyses of power and institutional misrecognition (Fraser), we probe the tensions and frustrations of those leading the work of community engagement. We find that although exercising considerable leadership of academic engagement functions, these staff, regardless of their own more hybridized identities as practitioner-scholars or 'prac-academics', are often misrecognized through institutional designations as professional staff. Two staff portraits in particular highlight two sources of misrecognition: gender intersecting with race, and from the relegation of community engagement to an external relations function that runs parallel to the core academic purposes of the institution. The Carnegie Pilots in Canada and Australia represent a valuable attempt to institutionalize community engagement as the critical third mission of higher education. Yet the experiences of these staff also attest to an ambivalence about community engagement within the academy, and the people leading this work, particularly in the most research-intensive and most established universities in each nation.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.039 | 0.031 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".