The issue of performance in Higher education institution - Community partnerships: A Canadian perspective
Bibliographic record
Abstract
Higher education institutions are expected to account for their performance and this increasingly includes strengthening community relationships. However, assessment of Higher education institution (HEI)-Community partnerships is nascent. In this study we seek to discern the situation of these partnerships and examine accountability for performance in Canada, thereby advancing understanding about this international phenomenon. A search of Canadian HEIs was carried out to identify those with an explicit mandate relating to community relationships and an initial questionnaire was distributed to their offices. Results afford insights into the present state of HEI-Community partnerships in Canada. A second questionnaire, distributed to individuals within the HEIs as well as community partners, examined how best to assess the performance of HEI-Community partnerships. Indicators and measures associated with a three-fold framework (inputs, processes, outcomes) were validated, offering important and timely advancements to HEIs in the era of accountability and performance-based funding.
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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 | 0.022 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.028 | 0.025 |
| Scholarly communication | 0.026 | 0.008 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".