Europe‐Wide Survey of Teaching in Geriatric Medicine
Bibliographic record
Abstract
By 2050, the European population of 720 million will include 187 million (one quarter) octogenarians. Although living longer is a true privilege, care for the graying population suffering from chronic and disabling diseases will raise enormous challenges to healthcare systems and geriatric education. Are European countries ready to cope with these challenges? An extensive 2006 survey of geriatric education in thirty-one of 33 European countries testifies that geriatrics is a recognized medical specialty in 16 countries and a subspecialty in nine of them. Six European countries have an established chair of geriatric medicine in each of their medical schools. Undergraduate teaching activities are organized in 25 of the surveyed countries and postgraduate teaching in 22 countries under the leadership of geriatricians (n=16) or general internists (n=6). A comparison with data collected in the 1990s shows important progresses: the number of established chairs increased by 45%, the undergraduate and postgraduate teaching activities increased respectively by 23% and 19%. However, these changes are very heterogeneously organized from country to country and within each country. In most European countries, there remains a huge need for reinforcing and harmonizing geriatric teaching activities to prepare the next generation of medical doctors to address the projected increase in chronic and disabled older patients. Several different innovative strategies are proposed.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; 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".