Залежність рівня життя населення в Україні від політичних циклів(Dependence of standards of living in Ukraine from political cycles)
Bibliographic record
Abstract
У статті досліджено залежність рівня життя населення України від політичних циклів. Виявлено вплив на зростання доходів населення, інфляції, тінізації та доларизації економіки. Визначено, що основним інструментом впливу є зростання соціальних стандартів. Це призводить до підвищення дефіцитності Державного бюджету України і стимулювання інфляції. Зміни соціальної політики пов’язані з виборами Президента України. In the article, the authors examine the dependence of the living standards in Ukraine from political cycles. The authors found that the political cycles represented by presidential elections have the strongest influence in Ukraine. Thus, the growth of minimum wages and pensions in 2000s (except 2016) in Ukraine depended on the presidential election. The increase in social standards and social benefits in the pre-election period increases the deficit of the State Budget of Ukraine, stimulating the growth of inflation after the election period. The authors found that the government predominantly increases the minimum social standards the quarter right before the election or in the quarter of elections, which confirms the stake of politicians on the short-sightedness of voters. The greatest growth of social standards occurred in 2005 and 2010, despite the state of the economy, when the opposition was coming to power. Such measures led to the growth of inflation in Ukraine in all the years following the elections, except in 2010 and 2012. In 2010, inflation was observed in the first half of the year. The growth of inflationary processes always led to a slowdown in economic development after the election period. Independence of the employment rates from the actions of political cycles is an important peculiarity in the economy of Ukraine. The most of candidate programs include the points about the increase in household incomes rather than reducing unemployment. During all election years there was an increase in incomes and real cash incomes of the population of Ukraine. However, the modeling of minimum wages and pensions dependence on elections in Ukraine showed a lack of citizens’ income. Governments do not use the state’s ability to develop and increase social guarantees. The timely growth of these indicators could have an impact on GDP growth and commodity turnover. This leads to an increase in the level of the shadow economy of Ukraine, the growth of the dollarization level in the election years and the devaluation of the monetary unit after the election. After significant depreciation fluctuations in the 1990s and early 2000s, Ukraine’s population took into account the effects of political cycles on foreign currency before the elections.)
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".