KOMPARASI PERTUMBUHAN PDB NEGARA LIBERAL KAPITALIS, KOMUNIS, DAN EKS-KOMUNIS
Bibliographic record
Abstract
The reseach was done to compare Gdb growth between liberal capitalist states (England, United States, Australia and Canada), comunists states (RRC, Cuba, Vietnam) and ex-comunists states (Russia, Poland, Hungary, Ukraine, Lithuania, Kazakthan, Armenia, Georgia). Results of one-way ANOVA showed an average growth of GDP in 1991-2011 to three groups of countries differ significantly. The biggest economic growth in 1991-2011 was China (10,41%), while Ukraine (-1,24%) and Georgia (-0,16%) have average experienced negative economy growth. The average of GDP growth on liberal capitalist countries was 2,61%, comunists countries was 6,53%, while ex-comunists countries was 1,44%. ABSTRAKSI Penelitian ini dilakukan untuk membandingkan pertumbuhan PDB negara-negara yang menganut sistem ekonomi liberal-kapitalis (Inggris, Amerika Serikat, Australia, Kanada), komunis (RRT, Kuba, Vietnam), dan eks-komunis (Federasi Rusia, Polandia, Hongaria, Ukraina, Lithuania, Kazakhstan, Armenia, Georgia).Hasil one-way ANOVA menunjukkan rata-rata pertumbuhan PDB tahun 1991-2011 pada ketiga kelompok negara tersebut berbeda signifikan. Rata-rata pertumbuhan ekonomi terbesar pada periode 1991-2011 adalah Tiongkok (10,41%) sedangkan Ukraina (-1,24%) dan Georgia (-0,16%) mengalami rata-rata pertumbuhan ekonomi negatif. Rata-rata pertumbuhan PDB kelompok negara liberal-kapitalis sebesar 2,61%, kelompok negara komunis sebesar 6,53%, sedangkan kelompok negara eks komunis sebesar 1,44%.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".