Innovation in the field of medical-conference-based education: a new marketplace
Bibliographic record
Abstract
Anyone who tries to make a distinction between education and entertainment doesn't know the first thing about either—Herbert Marshall McLuhan, 1911–1980, Canadian philosopher of communication theory and a public intellectual. International and national conferences remain a dominant means of delivering emergency medicine (EM) education and continual professional development (CPD). We are bombarded with adverts to attend and support such events, but how effective are conferences in delivering high-quality education? Emergency physicians are increasingly using multimodal, multiplatform technology-enhanced education alongside traditional methods for their CPD. Do conferences still have a role in this modern age, other than a very good way of meeting new and old colleagues? In this paper, the authors reflect on their experience in attending and organising conferences, and believe that large conferences have a better future, but will look different from the past. Your choice of conference may reflect your personal, clinical, financial and social needs, as well as other influences such as the location or the ‘status’ of the conference. When perusing the programme, you will ask yourself how well the conference matches your own personal CPD needs in terms of topics and speakers, but increasingly, the programme might describe both the mode of delivery of the education as well as giving you multiple options for topics. EM, because of its fast pace, varied nature, need for rapid decisions and array of life-saving practical procedures, lends itself well to dynamic, interactive and stimulating teaching formats that are the antithesis of the format of conferences in the past, which we will describe as Conference V.1.0. Many EM conferences have successfully embraced change. The authors describe and discuss the current models as Conference V.2.0, and speculate about how Conference V.3.0 might look. EM audiences are not alone in wanting more diversity and interactivity. We do not know how …
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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 | 0.012 | 0.101 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.065 | 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".