Bibliographic record
Abstract
It is said that imitation is the greatest form of flattery. Is it narcissism then to copy oneself? Whatever the label and whatever the accusations that come with it, some things are worth repeating. To wit … In 2016, the celebration of Medical Education's 50th volume culminated in publication of a somewhat satirical, somewhat spoofy, issue entitled 'Medical Education Unleashed'.1 To create it, the journal solicited 'quirky papers on topics of relevance to the lives and practices of health professional educators and trainees'; to curate it, we gave priority to those 'that amused and entertained'. The effort to free authors from the stilted norms of academic writing, however, was not an exercise in frivolity. Rather, it was a chance to put the insight that can be gained from thinking differently on full display through the creativity inherent in our community. Health professional education thrives, after all, to the extent that our educators remain passionately engaged, to the extent that personal connections are made between those with ideas and experiences worth sharing and to the extent that new ideas and new ways of thinking are encouraged and tested.2 With those goals in mind, and with our 60th volume looming, it is time again to demonstrate the liveliness of our field in an effort to see what new light whimsy can cast on important topics. As stated in the earlier call, consider this initiative to be an attempt to provide voice to the playful imps inside each of us that have valuable things to say, but often get bottled up. Show us, in other words, how well you can type with your funny bone, taking on serious issues without taking the issue too seriously. Novel empirical work is welcomed (hence the long lead time for this announcement), but so are well-crafted essays that offer a new and generative spin on well-known topics or findings. Previously published examples can be found in the December 2016 issue and details will be posted at mededuc.com. The key bits of information, however, are that papers should be no more than 1500 words and must be submitted through mededuc.com by September 30, 2024. Queries can be sent to [email protected]. As we begin to look forward to the humorous and thought-provoking papers that will be submitted, it is also time to look back in celebration of particularly strong contributions made to Medical Education in the past year as I once again have the pleasure of announcing our award winners. The Silver Quill, acknowledging the most downloaded article from the preceding year: Georgina Stephens, Mahbub Sarkar and Michelle Lazarus (Monash University, Australia) for their article entitled 'A whole lot of uncertainty: A qualitative study exploring clinical medical students' experiences of uncertainty stimuli'.3 The Henry Walton Prize, awarded to the most downloaded Really Good Stuff article from the preceding year: Bridget Addis, Kimberley Dean, Madeline Setterfield (University of Sydney, Australia), Amanda Hunter, Shannon Nott (Western New South Wales Local Health District, Australia) and Emma Webster (University of Sydney School of Rural Health, Australia) for their article entitled 'Virtual elective placements for medical students during COVID-19'.4 As some will have noticed, we have added a 'Peer Reviewer Hall of Fame' to mededuc.com. Well on their way to joining that illustrious group are this year's Choice Critics Award winners: Sola Barhous (Lebanese American University, Lebanon), Mohammed Khalil (King Fahad Medical City, Saudi Arabia), Cathy Lazarus (Tulane University, USA), Morris Gordon (University of Central Lancashire, UK) and Katharine Reid (University of Melbourne, Australia). The Medical Education Developing Scholarship Award, granted by ASME and Wiley on behalf of the journal, was won by Roma Forbes (University of Queensland, Australia) and Alison Pearson (University of Exeter) for their proposal 'Internationalising health professions education researcher development: A collective approach in two continents'. Finally, July 2023 marked the start of a new decade for our editorial internship program. While we celebrate the achievements of those who participated during the first 10 years on mededuc.com, the editors and staff look forward to welcoming the 11th cohort: Farhan Vakani (Dow University of Health Sciences, Pakistan), Georgina Stephens (Monash University, Australia) and Molly Fyfe (University of California at San Francisco, USA). Thanks to all who laid the groundwork for this trio through their active engagement as interns past.
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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.019 |
| Insufficient payload (model declined to judge) | 0.023 | 0.018 |
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".