Bibliographic record
Abstract
China attracts people with its geographic and economic diversity, an impressive heritage of over three thousand years old civilisation and the size of population which creates different opportunities for business. Understanding past and current reality of this country seems to be difficult as its economic and political system is somewhere in between bureaucratic and authoritarian one-party state and market orientated modern economy. The State centre within last three decades became one of the most important players in the world on political, economic and military scenes. It has the largest population, the most numerous army, nuclear weapons, large surplus in foreign trade balance, central bank reserves amounting 3,5 trillion USD and its national currency named yuan, which already has become a part of SDR. Nowadays China is on the way to become the world largest economy with independent impact on global political and economic affairs.This country is also facing a list of problems, which seem to be very serious and which will be challenging authorities and society in coming years and decades. One of the most important is necessity to strength environmental regulations to improve quality of life and to decrease the level of destruction of nature, secondly to support human capital to facilitate transition to higher value-added economy, it means to increase internal consumption and the third to boost rural development, which is slow, ineffective and it creates significant differences in individual incomes between urban and country regions. The speed of economic growth seems to be essential for business, stock exchanges and foreign investors and therefore questions concerning the barriers on the road to grow seem to be essential for coming years. This article is a trial to indicate these key challenges and threats for China on the way to grow.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".