Assessment and Management of Factors of the Regional Investment Potential
Bibliographic record
Abstract
The article is devoted to the questions of the territory investment potential valuation. It is the valuation system ofdistinctions in territories characteristics and their comparisons that are especially actual and necessary forinvestors as territories differ in labour, financial, natural and other resources, and various conditions created forinvestors by governing bodies. The article suggests the solution of this problem by calculating a total evaluativeindicator, that is, territory investment potential. The authors of article present the analysis results of a number ofvarious valuation techniques of investment potential, and mark the main advantages and disadvantages ofexisting approaches and valuation techniques. In the article the author's technique of valuation of territoryinvestment potential is suggested. It is based on the analysis of factors influencing investment potential. Thetechnique takes into account inflationary, political and social risks because stable political, economic and socialsituation is important for an investor. On the basis of the technique developed by the authors investmentpotential of a separate territory was calculated and forecasted.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".