Bibliographic record
Abstract
Innovations are also an integral part of local self-government. If the self-government wants to keep up with growing claims of the citizens, or with very quick modernization of competition, it has to outlay the necessary effort to modernize itself and its offered services. The aim of the paper is to identify and analyse the innovative activities of the city of Košice and its quarter Košice - Staré Mesto with a focus on evaluating the innovation environment, identifying implemented innovations, evaluating the financing of innovations as well as the institutional context of their creation. Both primary and secondary data were used to identify and evaluate innovation activities. In order to obtain empirical data was used the interviewing method supported by the structured interview. The municipality perceives the need for innovations in order to increase the efficiency of ongoing processes within its organizational structures, which will enable citizens to provide better services. It also considers it necessary to increase the share of funding to support introducing innovations. So far, most resources have been focused on process and organizational innovations, many of which have been created by the Office's employees, which can be considered as original.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".