Econometric Analysis of the Labor Market in the North Caucasus Region
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this study is an econometric analysis of the labor market in the North Caucasus region in the Russian Federation. The article examines the main indicators characterizing the labor market, such as the average monthly nominal accrued wages of workers across the entire spectrum of economic organizations as a whole by business entities, the real average monthly accrued wages of workers, the share of the number of workers employed in work with harmful and/or dangerous conditions labor in organizations, Labor productivity index, Level of innovative activity of organizations, Degree of depreciation of fixed assets in the constituent entities of the Russian Federation of the Russian Federation across the entire spectrum of organizations, Consumer price indices for all goods and services by subject at the end of the period, Number of graduates of higher educational institutions that have a direct impact on the level of unemployment and labor force in the region. The relevance of the chosen topic is due to the study of the role of these indicators in the analysis of the region’s activities in an economic and social key. The structure of the article provides for a consistent presentation of the results of the analysis of each of the models, an assessment of their adequacy and explanatory power, as well as an interpretation of the obtained modeling results. Particular attention is paid to how changes in economic indicators and policies can affect the labor market and unemployment rates in the region. In conclusion, conclusions based on the results of the study are formulated and recommendations are proposed to stimulate economic growth and reduce unemployment in the North Caucasus Federal District.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it