CONTRADICTIONS AND THE POTENTIAL FOR THE DEVELOPMENT OF THE NATIONAL ECONOMY IN 2024
Bibliographic record
Abstract
В статье анализируются макроэкономическая ситуация в национальной экономике через призму сравнения результатов 2023 года и разворачивающихся тенденций 2024 года. Обоснован оптимистический итог завершения прошлого года. Обозначены основные перспективы российской экономики в условиях геополитической напряжённости 2024 года. Обоснованы скромные результаты первого квартала текущего года. Сформулировано предложение о задействовании новых стимулов, без чего невозможно выйти на траекторию устойчивого развития. The article analyzes the macroeconomic situation in the national economy through the prism of comparing the results of 2023 and the unfolding trends of 2024. The optimistic outcome of the end of last year is justified. The main prospects of the Russian economy in the context of geopolitical tensions in 2024 are outlined. The modest results of the first quarter of this year are justified. A proposal has been formulated to use new incentives, without which it is impossible to enter the trajectory of sustainable development.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".