The View on the Three Major Problems and Solutions to the Deepening of State-Owned Enterprises Reform
Bibliographic record
Abstract
Since the 1990s, state-owned enterprises in competitive profession generally take a separation way that " hang difficult problems up " making the key business and the relevant good assets peel off, reorganize and get listed on the stock market. The listing part among them is known as continuing enterprises. The problem of continuing enterprises, to a great extent, it is a not thorough result of SOE reform. Because market system is unripe and the supervisory system is imperfect, in a situation that their reorganized and reformed system has been fulfilled, a considerable amount of state-owned enterprises adopt discrete scheme of reforming system, isolating a large amount of non-core business, low commercial ability assets and redundant staff from the continuing enterprises to construct "good assets " which can reach the requirements of listing on the stock market. This kind of method has met demand at one o'clock of smooth listing and financing of state-owned enterprise, but has failed to solve the problem fundamentally, so as to make the contradiction must be faced straightly during the deepening of the state-owned enterprise reform concentrated in the continuing enterprises. Concretely speaking, the current primal problems which the continuing enterprises face are: first the resource key element is bad. Continuing enterprises have common existence condition of bad assets, many redundant staff and the heavy managing bears. Not only assets scale and quality are inferior to the host job obviously, but also the personnel exists of the retiring personnel, laid-off workers and redundant staff in the reformed enterprises are more than needed. Therefore, it
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".