Bibliographic record
Abstract
Title in English: The future of metropolitan cooperation in the czech republic: development, governance, management Metropolitan regions are engines of economic growth, where research, innovation, technology and creative human potential are concentrated. The cooperation of municipalities in metropolitan regions in economically developed Europe dates back to the mid-1990s, while in the Czech Republic this new form of cooperation has been discussed more intensively since 2014, when three metropolitan areas and ten urban agglomerations were defined. However, there is still no systemic coordination of the problems and needs of metropolitan areas. The first activities aimed at real strengthening of metropolitan cooperation and development took place in the Brno Metropolitan Area within the framework of the TAČR ÉTA project “Institutionalization of metropolitan cooperation as a factor to increase the motivation of municipalities to cooperate in metropolitan areas”. The aim of the publication is to present the results of the project, experiences from abroad and their possible application in the Czech environment, as well as real steps to set up metropolitan inter-municipal cooperation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.007 | 0.008 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.065 | 0.034 |
| Open science | 0.054 | 0.042 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.356 | 0.392 |
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; both teacher heads agree on what is shown here.
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".