State management of import dependency and state’s economic security ensuring: New analysis to evaluating and strategizing
Bibliographic record
Abstract
The need to improve public administration of import dependency was characterized (in the example of Ukraine) and the signs of its influence and interconnection with ensuring the state’s economic security are characterized. The methodological sequence of import dependency evaluation is substantiated. Using Hotelling’s method of transformation (the method of principal components), the multiplicative form is presented and the integral index of import dependency of the country’s economy is calculated. Harrington’s interval scale is used to summarize the results of the integral evaluation of import dependency. The results of the evaluation have confirmed the high level of import dependency of the Ukrainian economy and clear tendencies for its strengthening, which is critically threatening to the country’s economic security. Using the tool of multivariate dynamic regression modeling, a statistically significant correlation between the level of import dependency and the country’s economic security is established. The economic and mathematical descriptive model of state management of the state’s economic security is formed, which is embedded in a methodical approach to strategizing the state policy of import substitution. The purpose of the state management of import substitution, the parameters of ensuring the country’s economic security agreed with it, the strategic priorities of the state policy of import substitution and the indicators of their implementation are determined.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".