External Risk Factors Influence on the Financial Stability of Construction Companies
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 modern conditions of construction companies’ activities in Russia are influenced by various processes: developing globalization, limitation of free trade due to economic sanctions, man-made disasters growth, worldwide digitalization, constantly evolving technologies. The purpose of this study is to develop a model for assessing risk factors’ impact on the financial stability of construction companies using regression analysis based on dependencies between risk factors and financial stability of construction companies on the basis of statistical data over the past 10 years. The following methods were used: questioning of owners and key employees in construction companies on the indicators choice that characterize external risk factors, correlation analysis, regression analysis, expert evaluation method, trend line method. As a result it was revealed that in order to create favorable conditions for the construction companies’ growth, a stable legislative base, a stable ruble rate and an activation of investments in fixed assets are needed. The proposed tool for assessing external risk factors and their impact on the construction companies’ financial sustainability can be used both to assess the organization's environment and to assess various risk situations in order to further use the results in decision-making.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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