The Consequences of the Military Conflict in Eastern Ukraine, Its Impact on International Investment Attractiveness, Economic and Demographic Development in Ukraine
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 conflict in the Eastern part of Ukraine and the growing geopolitical tensions have had a significant impact on the economy and society of the country. As a result, it deepened the recession and diverged from the planned development indicators. In particular, this concerns international reserves of the National Bank of Ukraine and the country's budget deficit. Multilateral economic changes, exacerbated by the impact of hostilities in the Eastern part of the country have transformed the structure of socio-demographic processes in Ukraine. Armed confrontation causes a continuous deterioration of demographic and economic indicators of development not only of Donetsk and Luhansk regions, but also has an impact on the whole country. This confrontation is also accompanied by the loss (destruction, theft, etc.) of public assets. The estimated cost of destroyed components of industrial, communal, social, transport, energy and other infrastructure are indicative due to the inability to inspect objects located within the territory controlled by terrorist groups. The conflict has also affected the investment attractiveness of the country, which accelerates the creation of a depressed nature of country’s development. Therefore, in the context of hostility in the Eastern Ukraine, it is important to understand and study its destabilizing impact, not only on domestic economic and demographic indicators, but also on the volume of foreign investment, which will allow us to understand the level of country’s involvement in the global investment space and the real impact of military action on the population and on international economic affairs of Ukraine. As a result of this scientific research, the population and GDP forecast have been conducted. It is worth noting that the forecast itself based on regression mathematical modelling which includes past data and can be accurate if current conditions are stable in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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