Bibliographic record
Abstract
In this paper, the three-dimension social credit structure made of three vectors including individual credit, organization credit and social credit environment, accordingly, three levels form, they are individual credit and organization credit, social credit environment and organization credit, social credit environment and individual credit. After analyze the interaction between every level vectors. A conclusion is drawn: It is social credit environment that determine the whole social credit condition. This text proceeded with the analysis of the cause of social credit environment of China and put forward the crucial way to improve the credit condition of china. Keyword: Individual credit, organization credit, social credit environment, opportunism Resume: Dans ce texte , la structure tri-dimensionnelle du credit social est compose par trois vecteurs , y compris le credit individuel , le credit d’organisation et l’environnement du credit social , en consequence , trois niveaux de formes y correspondent : credit individuel et credit d’organisation ; l’environnement du credit social et credit d’organisation ; l’environnement du credit social et credit individuel . Apres avoir analyse l’interaction de tous les niveaux du vecteur , il en ressort la conclusion que l’ensemble de la condition du credit social est determine par l’environnement du credit social . Ce texte donne suite a l’analyse de la raison de l’environnement du credit social en Chine et propose des solutions pour ameliorer la condition du credit en Chine . Mots-cles: credit individuel , credit d’organisation , environnement du credit social , opportunisme
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".