Nyugdíjas orvosok helyzete Magyarországon – országos, reprezentatív felmérés eredményei alapján
Bibliographic record
Abstract
INTRODUCTION: The aging population and the aging physician society is an important challenge of the New Millenium. Despite this, very few publications are dealing with the older generations' physical and mental well-being, quality of life and working conditions. AIM: The aim of this study was to describe the retired physicians populations' (n = 2112) demographic data, work status, income and health status. METHOD: Data of this representative, cross-sectional epidemiological study was obtained from online and paper-based questionnaires completed by 2112 retired physicians. RESULTS: The retired physicians' average age is 72 years, nearly two-thirds of the respondents retired after 35-45 years of service. Currently, nearly 60% are working, almost a quarter of them more than 40 hours per week. 35% of the respondents' income is below HUF 150,000. On this issue, significant differences emerge between female doctors and their male colleagues. CONCLUSIONS: The employment data of the results is consistent with the international trend, but the gender perspectives has unique significance in the international literature. Orv. Hetil., 2016, 157(43), 1729-1736.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".