What Do We Need to Protect, at All Costs, During the 21st Century? Reflections From a Curated, Interactive Co-Created Intellectual Jazz Performance
Bibliographic record
Abstract
The question that forms the title of this article, "What do we need to protect, at all costs, during the 21st century?," speaks to the sizable changes in health care systems and settings that surround the continuing professional development (CPD) provider, and the need to establish a core set of principles and practices as the field moves forward from both theoretical and practical aspects. It also provided the focus for one of the five keynote lectures presented during the 2016 World Congress on Continuing Professional Development. As the planners of this keynote session, we sought to evoke answers to the question, not from the speaker, but from the audience itself, a process enabled by a highly engaging presentation style and powered by interactive digital technologies. Further, we believed that the session would not directly lead to suggestions to improve the theory and practice of CPD, but rather to create the biopsychosocial context-a sort of platform-on which such discussions can occur.
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 | 0.034 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.047 | 0.080 |
| Scholarly communication | 0.037 | 0.020 |
| Open science | 0.005 | 0.033 |
| Research integrity | 0.012 | 0.038 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".