A systematic review of the conceptualization, interpretation, and implementation of shared governance in post-secondary contexts
Bibliographic record
Abstract
Shared governance has emerged as an incrementally inclusive modification to common Western forms of governance, which are often top-down, bureaucratic, and individualistic in nature. Anti-oppressive movements call for structural changes which necessarily involve examining where and how decisions are made in post-secondary institutions. This systematic literature review synthesizes scholarship on shared governance in post-secondary settings. This research is guided by the Joanna Briggs Institute (JBI) guidelines for conducting systematic reviews, a priori protocol to steer the research process, and the PRISMA guidelines for reporting systematic reviews. A review of 48 empirical papers published in peer-reviewed journals resulted in five main themes for shared governance in higher education: potentially interested parties; characteristics of governing leaders; principles and values of shared governance; processes of shared governance; and models of shared governance. We also identified gaps in the shared governance literature: underrepresentation of community (Indigenous and non-Indigenous) as well as Indigenous and diverse ways of knowing, and lack of attention to the diverse identities within the interested parties. We proceed to propose inclusive governance as a more appropriate term than shared governance.
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 | 0.040 | 0.137 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".