Development, improvement and funding of the emergency medicine cases open-access podcast
Bibliographic record
Abstract
Internet-based medical education resources, such as podcasts, have increased in number and popularity in recent years, and are being integrated into all levels of medical training and continuing medical education.1,2 Podcasts may be more effective than traditional methods of instruction such as textbooks for learners who prefer auditory modes of learning.3 Social media, through which podcasts can be distributed, is defined as the social interaction among people through virtual communities. The term ‘Free Open-Access Medical EDucation' (FOAMed), coined in 2012, is a subset of social media relating to the “creation and exchange of user-generated [medical] content via virtual networks and communities”.4 It is growing rapidly, out of a desire by health care professionals for free medical education and as a means to stay current with the wide scope of EM literature.5,6 This article describes the creation of the Emergency Medicine Cases (EMC) podcast, as well as the innovative transformation that occurred as a result of its conversion to a free open-access resource and its partnership with an academic institution. Description of the Podcast EMC, which was created in 2010, is targeted at health care professionals working in the EM environment. In a monthly podcast, the host (ADH) poses clinical questions to guest experts, discussing current controversies and describing evidence-based treatments. Episodes cover broad-based and clinically relevant topics from atrial fibrillation to cognitive decision-making. Eighty-two three-hour podcasts have been produced to date, each accompanied by a written summary, and 46 five-minute ‘Best Case Ever’ capsules. Initially, EMC was offered on a subscription-only basis. As of March 2014, 1,680 health care providers had subscribed to EMC. As demand for free online education increased, however, a free open-access model was adopted in April 2014. To cover the significant ongoing costs of the program, EMC partnered in July 2014 with a non-profit academic institution in Toronto, Canada, dedicated to advancing the care of patients requiring emergency services. The social media presence of EMC was also increased.
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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".