Advocacy in Outreach: A BHSc Outreach Case Competition 2023
Bibliographic record
Abstract
The “Advocacy in Outreach” case competition hosted by BHSc Outreach at McMaster University encouraged students identify a salient healthcare issue in the Hamilton community and then develop an evidence-backed initiative to address it. McMaster students were challenged to assume the role of health advocates by practicing their community-oriented thinking and ability to creatively problem-solve for the benefit of others. Fostering this thinking among our future health leaders is important since Canadians face a diverse range of healthcare issues from gaps in accessibility to staffing shortages to growing health inequity. To embark on the path toward solutions, participants created abstracts that outlined their plans for raising awareness of a pertinent health issue or a community-level program that supports vulnerable populations. The following abstracts are well-considered proposals that aim to proactively address challenges and improve health outcomes in Hamilton. Through this competition, BHSc Outreach hopes to inspire students to take further steps to contribute to their community in the future.
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 | 0.029 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.042 | 0.007 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.017 | 0.011 |
| Insufficient payload (model declined to judge) | 0.018 | 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".