Dynamic Comprehensive Evaluation of the Performance of Introducing Foreign Investment in Jiangsu
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Bibliographic record
Abstract
This research focuses on using a dynamic comprehensive evaluation model to assess the performance of introducing foreign investment in 13 cities in Jiangsu province of China. The model breaks the traditional evaluation model of a weighted average, using a second weighted average method. On the basis of the status in Jiangsu, five assessment indicators are chosen. Then the paper summarizes and classifies the changes of all cities according to the dynamic comprehensive value. Combined with the status and trends of introducing foreign investment in Jiangsu, the paper gives a detailed analysis to the evaluation results with a view to grasp the dynamic changes of introducing foreign investment in Jiangsu and to make an objective assessment. Key words: dynamic comprehensive evaluation, introducing of foreign investment, performance evaluation Resume: Cette recherche se concentre sur l'utilisation d'une dynamique integrale modele d'evaluation pour evaluer la performance de l'introduction des investissements etrangers dans 13 villes de la province de Jiangsu en Chine. Le modele rompt le modele d'evaluation traditionnel d'une moyenne ponderee, en utilisant une seconde methode de la moyenne ponderee. Sur la base des statuts a Jiangsu, cinq indicateurs d'evaluation sont choisis. Puis, le document resume et classifie les changements de toutes les villes conformement a la valeur dynamique integrale. Combine avec le statut et la tendance de l'introduction des investissements etrangers a Jiangsu, le document donne une analyse detaillee pour les resultats de l'evaluation en vue de saisir les changements dynamiques de l'introduction des investissements etrangers a Jiangsu et de faire une evaluation objective. Mots-Cles: evaluation dynamique integrale, introduction des investissements etrangers, performance evaluation
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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