Comparing pre-war and forced Ukrainian migrants in Poland: Challenges for the labour market and prospects for integration

Before full-scale war broke out in 2022, over 1 million Ukrainians resided legally in Poland. Within weeks of Russia's aggression, around 1.5 million new Ukrainian forced migrants had arrived, many of whom remain in Poland. As of September 2023, 970,000 Ukrainian refugees were still in Poland, where they enjoyed temporary protection status. This paper analyses data from a 2022 survey of both forcibly displaced and pre-war Ukrainian migrants with the aim of establishing what measures are needed to facilitate the economic integration of the former group. The two cohorts differ in terms of gender, age, family status, ways of seeking employment, employment situation and aspirations. Although 66 per cent of respondents had completed tertiary education, only 30 per cent of the forcibly displaced group had Polish-language skills. The paper recommends strategies for the provision of language education along with solutions to enable the labour market participation of this group and otherwise support their integration.     

Multi-couple reflecting team: preliminary report

The aim of therapeutic help in marital crisis is to break the vicious circle of mutual hurtful accusations. The method that the authors present below involves a group of couples working within a closed cycle of meetings. In the course of successive group meetings, the various couples act as reflecting teams (RTs) for each other. This achieves two objectives: the couple recounting their crisis receives nonthreatening feedback, which helps them to implement positive changes and break out of the self-perpetuating destructive interaction. In addition, the couples acting as the RT learn nonjudgmental, nontheorizing and affirmative communication.     

Extreme ranking analysis in robust ordinal regression

We extend the principle of robust ordinal regression with an analysis of extreme ranking results. In our proposal, we consider the whole set of instances of a preference model that is compatible with preference information provided by the DM. We refer to both, the well-known UTA^GMS method, which builds the set of general additive value functions compatible with DM's preferences, and newly introduced in this paper PROMETHEE^GKS, which constructs the set of compatible outranking models via robust ordinal regression. Then, we consider all complete rankings that follow the use of the compatible preference models, and we determine the best and the worst attained ranks for each alternative. In this way, we are able to assess its position in an overall ranking, and not only in terms of pairwise comparisons, as it is the case in original robust ordinal regression methods. Additionally, we analyze the ranges of possible comprehensive scores (values or net outranking flows). We also discuss extensions of the presented approach on other multiple criteria problems than ranking. Finally, we show how the presented methodology can be applied in practical decision support, reporting results of three illustrative studies.     

Beyond Markowitz with multiple criteria decision aiding

The paper is about portfolio selection in a non-Markowitz way, involving uncertainty modeling in terms of a series of meaningful quantiles of probabilistic distributions. Considering the quantiles as evaluation criteria of the portfolios leads to a multiobjective optimization problem which needs to be solved using a Multiple Criteria Decision Aiding (MCDA) method. The primary method we propose for solving this problem is an Interactive Multiobjective Optimization (IMO) method based on so-called Dominance-based Rough Set Approach (DRSA). IMO-DRSA is composed of two phases: computation phase, and dialogue phase. In the computation phase, a sample of feasible portfolio solutions is calculated and presented to the Decision Maker (DM). In the dialogue phase, the DM indicates portfolio solutions which are relatively attractive in a given sample; this binary classification of sample portfolios into ‘good’ and ‘others’ is an input preference information to be analyzed using DRSA; DRSA is producing decision rules relating conditions on particular quantiles with the qualification of supporting portfolios as ‘good’; a rule that best fits the current DM’s preferences is chosen to constrain the previous multiobjective optimization in order to compute a new sample in the next computation phase; in this way, the computation phase yields a new sample including better portfolios, and the procedure loops a necessary number of times to end with the most preferred portfolio. We compare IMO-DRSA with two representative MCDA methods based on traditional preference models: value function (UTA method) and outranking relation (ELECTRE IS method). The comparison, which is of methodological nature, is illustrated by a didactic example.     

Comparison of Kernel Discriminant Coordinates Algorithms

The construction of kernel discriminant coordinates reduces to the solution of a generalized eigenvalue problem in which both matrices are nonnegative definite. Six different algorithms for solving that problem are described, and the performance of these algorithms is tested on 26 different datasets. The percentage of misclassifications using a linear discriminant function is noted, and the algorithms’ running times are ascertained. Classification is also performed in the space of classical discriminant coordinates.     

Three categories of urban green areas and the effect of their different management on the communities of ants,spiders and harvestmen

Urban green areas have become an important tool for biodiversity conservation in cities. However, land use and the different management practices applied to these areas determine their effectiveness as biodiversity refuges within cities. In our study, we compare the biodiversity of three bioindicator groups of arthropods (ants, spiders and harvestmen) found in eleven urban green sites in Warsaw (Poland). The studied sites represent three categories of management: botanical gardens, public parks and urban woodlands. Our aim was to determine the effect of the type of management (as urban green categories) on arthropod communities in urban areas.

     

Knowing that you mimic me: the link between mimicry,awareness and liking

Mimicry pays off for a mimicker, and that mimickees are not aware of being influenced by mimicry. In this study, we investigated the link between mimicry, awareness and liking using a 2 (mimicry: yes/no) × 4 (awareness manipulation) experimental design. We found a main effect of mimicry (the confederate was liked more in the mimicry condition) and an interaction between mimicry and awareness. Awareness manipulation had a limited effect on the association between mimicry and liking. Providing participants with little or no information about mimicry (information not including any remarks about its consequences) had an effect on the association between mimicry and liking. However, when participants were informed about the interpersonal consequences of mimicry, mimicry did not influence liking.