Gyventojų senėjimas - iššūkis socialinei ir darbo rinkos politikai
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Different countries, including Lithuania, meet economic and social challenges and changes in the sector of social security. The anticipation of the problems and taking actions for the prevention of their after-effects, which may occur in future, is especially important, taking in to the account the projection of population ageing. \nThis work analysis the challenges for social and labour market policy, arising from the ageing of the population. \nMain purpose of the work is to unfold the point of view of different age groups, women and men, about the ageing process of the population and the challenges of this process for state social and labour market, as well as discovering the opinion of the questioned groups of the ways for solving the problems, caused by the process. Therefore, a survey for the implementation of this purpose has been performed. 100 respondents in the age of 30-69 age have been questioned during this survey. The data of this survey do not reflect the opinion of all Lithuanian inhabitants about the challenges, changes and problems, arising due to the population ageing. This is just a tendency for seeing some particular consistent patterns. \nEssence and reasons of population ageing, world wide and Lithuanian ageing tendencies, state policy on elderly people are being reviewed in this work.\nCurrently have the rates of population ageing due to the reduced birth rate and high emigration level in Lithuania signally quickened. Responding to the challenges... [to full text]
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.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 it