Bibliographic record
Abstract
Alumni engagement is widely defined as the level of relationship graduates have with their alma maters. Universities have an opportunity to leverage benefits from having strong connections with their alumni. Furthermore, graduates generally have a stronger affinity to the academic departments they graduated from than to the universities where these departments are based. Additionally, the fiscal and regulatory pressures facing Canadian universities within the province of Ontario highlight the advantages that come with having an engaged alumni community. The Problem of Practice (PoP) investigated in this Organizational Improvement Plan (OIP) is the lack of alumni engagement within a faculty of business at an Ontario-based university and the negative impact it has on students, faculty members, staff, alumni, and external partners. The change process undertaken to close the gap in alumni engagement within the organization is described, as well as several possible solutions for improving alumni engagement. As the Director of Student Engagement and Alumni Development for this business faculty, my thinking is influenced by having a social constructivist view. A good example is my focus on stakeholder engagement and leveraging the knowledge that it provides. I also have the agency to enact the change process and apply authentic, shared, and transformational leadership approaches to close the gap that results from the PoP. The aim of the OIP is to mobilize stakeholders across academic departments within the university and achieve the envisioned future state of enjoying a stronger relationship between alumni and their alma mater.\nKeywords: alumni engagement, leadership, faculty, social constructivism, universities, organizational change
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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.018 | 0.014 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".