“So, should we stay in touch?” A Plan to Build Community Using Social Media Among Alumni of the Michael G. DeGroote School of Medicine at McMaster University
Bibliographic record
Abstract
Can a community be maintained or put back together when there is distance? Students of McMaster University’s Michael G. DeGroote School of Medicine spend an intense three years together in its undergraduate program, and then they move on. However, universities, including McMaster, look to maintain rapport with alumni who often support their alma mater: Alumni often appreciate ties to the prestige of a high profile academic institution and to the memories of their time there. The new social media technologies appear to give the chance to maintain or even rebuild that engagement, but universities are stepping into the opportunities slowly. They are cautious because there is no wave of social media acceptance except, perhaps, for Facebook, and the costs of providing true two-way communications on a one-to-one basis is not in the budget. However, building on a survey of its market, this case study looks at using social media to start to build community among alumni of the Michael G. DeGroote School of Medicine.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".