Public administration megacities in the context mechanisms of public administration
Bibliographic record
Abstract
The article analyzes scientific research of public management of megacities in the context of governance mechanisms. Particular emphasis is placed on the correlation of theoretical and practical approaches to determine the effectiveness of public management of megacities with working component of the mechanisms of governance as well as the determination of basic conceptual approaches to the implementation and use of the political mechanism of public administration in the measurement of the efficiency of public management in megacities. It is proved, that by modern scholars these issues are discussed in the context of the following mechanisms: governance, economic, social, institutional, legal, and from the standpoint of implementation of experience in the USA, Canada, Great Britain, Northern Ireland, Japan and Russia. And less attention is paid to the experience of forming an effective public management of megacities of Ukraine’s neighbors (Belarus, Moldova, Romania, Hungary and Poland), since of all number only capitals can be considered as megacities. It is noted, that the necessity to determine main directions of development of megacities will enable to carry out reforms in public management of megacities.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".