Bibliographic record
Abstract
COVID-19 pandemic crisis enlarged „new “poverty among the working class what is a far-reaching consequences of the processes of globalization and privatization, especially in the USA, Canada and Europe. During COVID-19 pandemic crisis a lot of the workers lost their jobs. Others faced decline of the wages due to downturn in the global economy. „New“ poverty among the working class is particularly widespread in Eastern Europe as a result of privatization of state property and pauperization of the working class. The main issue of our paper is to analyze a link between the policy of flexible labor market and phenomenon of „new “poverty among the working class in Serbia. We explore the living standard of the working families in conditions of increased cost of living and the expansion of number of the workers that earn the minimum wage (400,000 persons, 20% of employees) in Serbia during COVID- 19 pandemic crisis. We examine the value and the content of the minimum consumer goods basket and the amount of the minimum wage. The amount of the minimum price of labor per working hour in Serbia for 2022 has not been determined by the Social and Economic Council of the Republic of Serbia. The decision on the amount of the minimum price of labor has been made by the Government of the Republic of Serbia, as it used to in previous years. The minimum cost of labor for 2022 is only 89% of the value of the minimum consumer basket.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".