Creating innovative design labs for the public sector: A case for institutional capacity building in the regions of Ukraine
Bibliographic record
Abstract
Innovative design labs were created by public authorities of the USA, Australia, Singapore, Finland, Canada, the UK, Switzerland, Denmark, China, and other countries to accelerate changes and develop modern public service. This paper provides further insight to establishing external innovation accelerators for strengthening capacity of public institutions. The study aims to define the development opportunities for innovative design labs for the public sector in Ukraine’s regions by the case of the Laboratory of Intellectual Development for Empowering Regions (LIDER). The study was conducted at two stages: (1) exploring the features of innovation implementation in the public sector and outlining the main problems of innovation capacity of public institutions; (2) defining the development opportunities for the LIDER via SWOT-analysis. To substantiate the study results, the correlation analysis between autocratic, bureaucratic, competitive, self-protective, and participative leadership behaviors of CEOs and innovation index based on data from 18 countries was performed, as well as a survey of 195 public servants of the Ministry of Justice of Ukraine and an interview of 9 experts were conducted. The following key development opportunities for the LIDER were detected: promoting the introduction of incremental innovations in public institutions by using design thinking methodology; assisting the development of pro-innovative culture and participative leadership via individual-centric and system-oriented approaches; developing effective tools for performance management and supporting public institutions in project activity; organizing the competitions for regional innovative projects; assisting in creation of radically human systems in public institutions. AcknowledgmentThe paper was prepared within the framework of the joint Ukrainian-Lithuanian R&D project “Competence Development of Lithuanian and Ukrainian Public Sector Employees Using Design-Thinking Methodology”.The project has received funding from the Research Council of Lithuania (LMTLT, agreement № S-LU-20-5) and the Ministry of Education and Science of Ukraine (agreement № М/31-2020).
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| 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".