Overcoming Poverty in the World and in Ukraine: Current State (on the Example of the NFP «Volunteering» and «Voluntourism»)
Bibliographic record
Abstract
In the article, the problem of overcoming poverty acquires further theoretical and methodological substantiation. The current state of overcoming poverty in the world and in Ukraine (on the example of non-standard forms of employment (NFP) "volunteering" and "voluntourism") in the global socio-economic and political aspects in the context of permanent changes and transformations of the world are considered. It is shown: international documents fix the existence of the problem of poverty and determine the main directions of the XXI century for overcoming it (on the example of the UN Millennium Declaration); the coronavirus pandemic has led to an increase in poverty; the main problem of overcoming poverty in Ukraine is the lack of a comprehensive system in the country that can effectively address poverty problems (government bodies are not involved in poverty prevention policies, but only fight with its consequences); in Ukraine, the most pressing problem is poverty among the working-age population and the poverty of families with children; poverty in Ukraine is characterized by a number of national characteristics (the UN notes that absolute poverty in Ukraine has been overcome. But relative poverty is 78%); solving the problem of overcoming poverty in Ukraine requires the development of a system of complex scientifically based and effective measures that should take into account the profile, specifics and features of the formation and spread of poverty, the causes of its occurrence and ways of overcoming it, as well as the most effective state policy for overcoming poverty and economic mechanisms for its implementation; world experience considers the NFP “volunteering” and “voluntourism” as forms of employment that can overcome the effect of abstraction of people from social problems and poverty, form a model of collective participation in the elimination of the latter, and restore human values; volunteering and voluntouring are supported by government agencies of the USA, Canada, Australia, England, Italy, Japan and other developed countries, including through the adoption of legislative acts that stimulate their development, the creation of a system of state volunteer centers and special programs of volunteering and voluntourism; Ukrainians attach great importance to volunteering and voluntourism in the development of social processes.
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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 | 0.002 | 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 | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 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".