Traditions and recent developments in learning in later life in the Russian Federation
Bibliographic record
Abstract
After the economic and ideological changes of the 1990’s older people in Russia have become the most vulnerable, poor and disrespected group in the population. Older people are predicted to constitute almost a quarter of the Russian population in 2016. However, so called ‘people’s universities’ have long been part of the Soviet tradition and were renewed mostly for the education for older people in the post-Soviet era. Primarily they are supported by non-profit organisations and offer informal education on a range of topics and crafts. Their programmes have proved to be enjoyed by older learners and are recognised to be major contributors to active ageing in Russia. Nevertheless, their numbers and capacities are not sufficient to respond to the variety of needs and interests of older people. This article reports on a national survey of University of the Third Age-type provision for older people in eight cities nationwide. In the Republic of Bashkortostan a region-wide programme ‘Third Age Universities for All’ came into operation in 2011. A small survey of U3A students in one city is reported. It suggests that while the programme needs to be amended in many ways, it sets a worthwhile precedent.
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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 | 0.001 | 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 | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".