Bibliographic record
Abstract
It appears to be a new approach of study that adopting the theory of nonlinear self-organization on the study of enterprises cluster. The emergence, development and growth of enterprises cluster can be satisfactorily analyzed in the theory of self-organization. The theory of self-organization originated from system theory is a result of transition from system theory to nonlinear science of complexity, and a theory of study on self-organization phenomena and laws. Dissipative structure theory deeply unearths the birth environment and conditions of self-organization and lays the foundation for the theory of self-organization; and synergetics theory intends to explain the process in which a system evolves from disorderliness to orderliness, which is essentially a process of self-organization inside the system. Synergy is a form and mean of self-organization. As a social system, enterprises cluster is a complex aggregation of multiple factors, themes and relations, has a series of conditions for self-organization, and its evolution is driven by the synergy among all the subsystems inside the system. On the whole, the process of synergetic evolution is normally the development from the evolution of competitive synergy to the evolution of cooperative synergy.Key words: Self-organization; Enterprises Cluster; Dissipativ Structure; The theory of synergetics; mechanism of evolution
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".