As an interdisciplinary field of scholarship, transitional justice is still in its pre-theoretical stage, focusing mainly on the case and comparative studies, supported by general considerations concerning justice in the times of transition. To entrench the field as a distinct area of studies, a theory of transitional justice needs to be formulated. The article explores the possibility of making a step towards such a theoretical basis with the use of the tools of analytical philosophy, methodology and legal theory. First, drawing on Leszek Nowak’s procedure of idealisation, three basic models of responses to a painful past are formulated. Then, distinct transitional justice values are attributed to each of the models. Finally, with the use of Jerzy Kmita’s concept of humanistic interpretation, the article seeks to conceptualize the way in which these values – among other factors, such as the need to uphold the rule of law or to preserve the stability of a democratic system – influence the choice of a model of transitional justice response. Thus, the aim of the presented models – which I described in more detail elsewhere (Krotoszyński 2017) – is to provide a sound theoretical basis for some of the fundamental claims formulated in the field of transitional justice.

The Polish Political Science Yearbook, WSB University in Bydgoszcz and Center for Local Government Studies in Bydgoszcz invite all scholars, researchers and professionals to participate in the PPSY Bydgoszcz International Seminar "Local Government: Experiences, Challenges & Models" which takes place in Bydgoszcz (Poland) on May 8, 2018. The conference supports a special section of the current Volume 47 of 2018 of the journal and its objective is to discuss challenges of security and stability in Central Europe and to present current advancements in regional security studies.

Deadline for application: April 25, 2018, with the Online Form.

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Analysis of the possibility of building a credit risk model

FinAi has undertaken a project focused on the development of an innovative credit risk model utilizing alternative data sources, such as data from social media platforms (Facebook, LinkedIn) and mobile phone records. This project was co-financed through the European Regional Development Fund under a funding agreement between FinAi S.A. and the National Centre for Research and Development (NCBiR), headquartered in Warsaw. The initial phase of the project involved the collection of data and their utilization in constructing a network graph of customer relationships. Furthermore, leveraging external data as well as data managed by FinAi, specific indicators were formulated. These indicators were employed under the supervision of experts to train a predictive model that incorporated graph structures. The model thus constructed was to exhibit a higher predictive capability compared to conventional models commonly employed within the industry. The study explored the feasibility of creating a credit risk model based on the acquired data and assessed the quality of data originating from alternative sources. It was demonstrated that alternative data sources were populated for a small fraction of the population, and their quality has proven unsatisfactory. The scale of the dataset proved inadequate for establishing a robust credit risk model or attaining a competitive advantage over the models in use within banking institutions.