Technique of Tax Rates and Customs Duties Updating as the Tool of Enterprises Innovative Activity Stimulation
Bibliographic record
Abstract
Purpose: one of the actual economic science problems is the study of the tax loading influence to the economic activity of the managing subjects which are carrying out an innovative activity. Thus an innovative activity of a business is one of the basic factors capable to provide the innovative development of the country as a whole. The article purpose is the study of the approaches directed to the decrease of the managing subjects’ tax loading. Methods: in the course of the research the comparative analysis methods and the statistical methods of research were used. Results: Firstly, on the results of the research conducted the algorithm of the taxes and duties sums calculation was developed on the basis of the tax and customs rates updating taking into account a the admissible limits establishment of their change depending on the activity efficiency of the innovatively active managing subjects promoting their activity activization at the expense of the effective utilization of labor, financial, industrial resources at all stages of the innovations life cycle. Secondly, the universal complex technique of the tax rates and the customs duties updating was offered allowing operating the rates of federal, regional, local taxes and also the export and import customs duties depending on the efficiency activity results of the innovatively active managing subjects at scientific, technical, technological and operational stages of the innovations life cycle.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".