ОЦЕНКА ПОТЕРЬ БЮДЖЕТА КРАСНОЯРСКОГО КРАЯ ИЗ-ЗА НЕДОПОСТУПЛЕНИЯ НАЛОГОВ ОТ ПРЕДПРИЯТИЙ В СВЯЗИ С ВРЕМЕННОЙ НЕТРУДОСПОСОБНОСТЬЮ КУРЯЩИХ СОТРУДНИКОВ И СНИЖЕНИЯ ИНТЕНСИВНОСТИ ТРУДА ИЗ-ЗА ПЕРЕКУРОВ
Bibliographic record
Abstract
The aim of the paper is to estimate Krasnoyarsk region budget losses due to the shortfalls of taxes from businesses related with a temporary disability of smoking employees and the reduction of labor intensity due to the smoking breaks in 2011. In our work we used the method of economic losses estimation, developed by Conference Board of Canada. The following results were obtained. The estimation of tax shortfalls due to a temporary disability of smoking employees and decrease of labor intensity due to smoking breaks was carried out. It was obtained that Krasnoyarsk region budget losses as a result of the tax shortfalls are equal to 532.8 million rubles – due to increased sick absence risks among smokers and 3 414.3 million rubles – due to the lack of workers on the workplace during smoking breaks. Thus, it was found that the total budget losses of Krasnoyarsk region in 2011 reach 0.34% of the gross regional product. The obtained results can be used for the assessments of the economic losses. DOI: http://dx.doi.org/10.12731/2218-7405-2013-7-22
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.011 |
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".