- Lesya Ilchenko-Syuyva, Kyiv-Mohyla School of Governance, National University of Kyiv-Mohyla Academy, Kyiv, Ukraine, lesya.ilchenko@gmail.com
- Jaroslav Dvorak, Klaipeda University, Klaipeda, Lithuania, Jaroslav.dvorak@ku.lt
- Mihaela Victorita Carausan, National School of Political Sciences and Public Administration, Bucharest, Romania, mihaela.carausan@administratiepublica.eu
Her professional development includes trainings followed at the Centre International de Formation Européenne from Nice, France (1998), Venice Commission – Council of Europe (2001 and 2007), the Romanian Institute of Diplomacy (2010) and Complutense University of Madrid (2013).
Carausan has published widely in the areas of administrative law, street-level bureaucracy, regulatory impact assessment, citizens’ participation and public integrity. Her recent research has focused on monitoring and evaluation of public procurement, and she authored more than 50 articles and books in the areas of interests. She collaborates with different journals as member of the scientific committees or as reviewer. Dr. Carausan received her PhD from the University of Craiova in European Union law and her Master’s from the University "NicolaeTitulescu”. She coordinated different Romanian and European research and educational projects, and she is a member of the American Society of Public Administration, American Evaluation Association and European Law Institute.
WG Background and Rationale:
In recent years, there has been a significant effort to improve algorithm-based decision-making within the public sector by developing machine learning capacity in evidence-based policy making in general and policy analysis in particular in CEE, Central Asian and Caucasus countries.
The Working Group started in 2008 as a Panel Session on Policy Analysis Issues and became an annual Working Group based on the increased demand. The wide variety of papers and the large number of participants confirm the strong interest in evidence-based policy making and policy analysis in the region. Thus, the WG continues to support the scientific development of new ideas in public policies and encourages experience and knowledge exchange on how academics can meet the urgent needs of public servants and civil society. In addition, artificial intelligence agents become autonomous moral agents, causing harmful social and political consequences
The goal of the WG is to focus on discussions and debates around capacity challenges, professional, evidence-based public policy making in the countries embraced by NISPAcee, and not limited to the institutionalisation of public policy analysis procedures and concrete remedies for those challenges. Nowadays, solid and effective public health systems and evidence-based policies are vital for improving health outcomes.
For the 31st Annual NISPAcee Conference 2023, the WG on EVIDENCE-BASED PUBLIC POLICY MAKING welcomes theoretical, empirical or comparative research papers of academics and practitioners on the need for more adaptive, anticipatory, inclusive and sustainable policies. We encourage potential authors to focus on the collaborative decision-making capacity and algorithm-based evidence-based public policy-making and artificial intelligent actors as decision-makers. The WG is interested in papers that focus on those aspects and particularities of policy making, policy analysis or monitoring and evaluation of public policy experiences in a single country and/or region, either generally or in specific sectors.
Requirements for the papers:
The papers can address not only recommendations for further research but also real-world points for practitioners. In this respect, collaborative papers between researchers/academics and practitioners are highly welcomed.
All papers shall include, at least, but are not limited to the following sections: introduction; background of the chosen issue; literature review; the objective of the study; research methodology; analysis; main findings and policy implications; ideas and recommendations for further research.