Epistemic Rationality in Political Theory

The paper presents a brief analysis of the procedural approach towards constructing liberal political conceptions of justice and democracy. Treatment of J. Rawls’s evolution shows the negative consequences of abandoning external substantive criteria for theory evaluation, including efficiency, justification, truth. It also offers justification for the “epistemic turn” in contemporary political theory. The return of classical epistemological set of tools will help to strengthen the justification and legitimation of philosophical and political conceptions of justice and democracy by overcoming the key limitations of the procedural approach.

Evaluation of Concrete Durability Based on Cloud Model and D-S Evidence Theory

The environment in alpine region is complex and harsh, and the durability of concrete is seriously affected by freeze-thaw and salt invasion. In this paper, the relative dynamic modulus of elasticity, chloride permeability coefficient, mass loss rate and carbonation depth are selected as the evaluation indexes of concrete durability in Northeast China. Based on prior knowledge and expert group decision-making, the durability grade is divided and the evaluation standard is established; The evaluation model of concrete durability based on cloud model and D-S evidence theory is established. According to the engineering experimental data, the membership degree of concrete durability evaluation index in different grades is obtained through the correlation measurement of cloud model. The normalized evidence is formed and fused by D-S evidence theory. The results show that the durability grade of concrete is grade I, which is consistent with the actual project. It shows that using cloud model and evidence theory evaluation model to evaluate the durability of concrete is a new and effective method.

Research on the Evaluation Model of Educational Management Theory Based on Data Mining from the Perspective of Neural Network

The improvement of the theoretical quality of education management is an indispensable part of a country’s education modernization. However, the existing research on the evaluation of educational management theory is still relatively small, and there is a lack of scientific educational management theory evaluation model. Designing a comprehensive and accurate educational management theory evaluation model has important theoretical value and practical significance. It is possible to process a lot of information in parallel using the artificial neural network method. By optimizing the artificial neural network, data mining of characteristic information data can be realized. Therefore, this paper uses neural network to conduct data mining on education management theory and conduct a comprehensive system evaluation of education management theory. At the same time, the traditional BP algorithm is improved. To train a neural network with large amounts of data, the BP algorithm uses a lot of gradient calculation, which takes a long time and often results in training going to extremes in the local area. BP neural networks are trained using the particle swarm optimization algorithm, and the backward propagation process in the BP algorithm is replaced with particle swarm iteration. To improve algorithm execution efficiency and speed up neural network training, a large number of gradient operations can be avoided. This can help overcome the limitations of the BP algorithm when dealing with large amounts of data. The improved BP algorithm is applied to the evaluation system of education management theory, and the quality evaluation prediction of management education theory is realized.

#Ibelong: Towards a sense of belonging in an inclusive learning environment

#Ibelong is an Erasmus+ project delivering a suite of evidence-informed interventions to improve the belonging and success of students who are first-generation entrants, from ethnic minorities or have a ‘migrant background’. The activities operate at course or programme level and involve working with both staff and students. This article provides a rationale for the #Ibelong programme of activities by drawing on relevant research and describing the three interconnected interventions: Dialogue Days, Team Teacher Reflection and Community Mentoring. The interventions were evaluated using Programme Theory evaluation tools: theory of change and logic chains. The descriptions highlight activities that have worked well, how delivery has been adapted from in-person to online delivery, and evidence of short-term benefits and medium-term outcomes. The article concludes by reflecting on how this suite of interventions could be used by other courses, universities and sectors, to improve the belonging and success of diverse students and staff.

Pandemic Communication: Information Seeking, Evaluation, and Self-Protective Behaviors in Vietnam and the Republic of Korea

Saliou (Eur J Epidemiol, 1994, 10 (4), 515–517) argued that pandemics are special kinds of crises and requires the public health sector to focus on: 1) reducing uncertainty, 2) rumor mitigation, and 3) ensuring the public reduces their risk of contracting the disease. With this as a backdrop, the central aim of this research is to better understand the connections between public information seeking, evaluation, and self-protective behaviors in the COVID-19 pandemic and focuses on a comparison between the Republic of Korea and Vietnam to provide insights into the influence of the individual, institutional, and information factors influencing people’s experience with COVID-19. Thus, there are two major contributions of this study. First, it provides a cross-theory evaluation of the factors that contribute to information seeking, evaluation, and self-protective behaviors. Second, the study identifies potentially critical differences in information seeking, evaluation, and self-protective behaviors based on acute disease reproduction in countries with a successful pandemic suppression history. Findings suggest that in countries where there are high levels of trust and satisfaction even small changes in the infection rates lead to different information seeking and self-protective behaviors.

Comparing Theories with the Ising Model of Explanatory Coherence (IMEC)

Theories are among the most important tools of science. Lewin (1943) already noted “[t]here is nothing as practical as a good theory”. Although psychologists discussed problems of theory in their discipline for a long time, weak theories are still widespread in most subfields. One possible reason for this is that psychologists lack the tools to systematically assess the quality of their theories. Thagard (1989) developed a computational model for formal theory evaluation based on the concept of explanatory coherence. However, there are possible improvements to Thagard’s (1989) model and it is not available in software that psychologists typically use. Therefore, we developed a new implementation of explanatory coherence based on the Ising model. We demonstrate the capabilities of this new Ising Model of Explanatory Coherence (IMEC) on several examples from psychology and other sciences. It is also available in the R-package IMEC so that it can help scientists to evaluate the quality of their theories in practice.