Establishing Community, Academic, and Industry Partnerships to Support Experiential Learning Within a Community-Based Research Collaborative
Bibliographic record
Abstract
Sudden cardiac arrest (SCA) is a common but potentially reversible cause of death. Unfortunately, few communities have attempted to improve survival using a holistic approach to resuscitation science including preventative, clinical, and rehabilitative care. The Durham Region Resuscitation Research Collaborative (DRRRC) has been established to identify research priorities, leverage regional community and health care services, and provide experiential learning and training opportunities within the resuscitation science continuum of care. Our objective is to provide an overview of the DRRRC and to present the collaborative learning experiences that link learners, stakeholders, research, and knowledge users in a community- based resuscitation laboratory. We used a case study approach that illustrated the opportunities for learning within the context of DRRRC’s first initiative focused on improving community- based cardiopulmonary resuscitation (CPR). To date, this community-based resuscitation laboratory has included: one-second year and four fourth year undergraduates, and one medical resident. Learners engaging with the co-investigators and stakeholders have experienced learning opportunities that support the development of critical thinking skills and problem solving in the real world to support strategies to increase bystander CPR.
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 | 0.016 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.013 |
| 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; both teacher heads agree on what is shown here.
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".