Belief Structures Research Articles

Smart Cities and Resident Well-Being: Using the BTOPSIS Method to Assess Citizen Life Satisfaction in European Cities

With rapid urbanization, maintaining a high quality of life (QoL) for city residents has become a critical challenge for policy-makers and urban planners. Smart cities, leveraging advanced technologies and data analytics, present a promising pathway to enhance urban services and promote sustainability. This paper introduces an innovative adaptation of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, integrating a Belief Structure (BTOPSIS) to improve the evaluation and interpretation of survey data. Our approach effectively addresses the distribution of responses across categories and the uncertainty often present in such data, including missing or ambiguous answers. Additionally, we perform a sensitivity analysis to assess the stability of the BTOPSIS rankings under varying utility function parameters, further validating the robustness of our method. We apply this framework to the 2023 ‘Quality of Life in European Cities’ survey, analyzing diverse urban factors such as public transport, healthcare, cultural facilities, green spaces, education, air quality, noise levels, and cleanliness. Additionally, our study offers a comparative analysis of BTOPSIS against other multi-criteria methods used for evaluation data from this report, showcasing its strengths and limitations in addressing the dataset’s complexity. Our findings reveal significant variations in residents’ perceived QoL across European cities, both between cities and within countries. Zurich and Groningen rank highest in satisfaction, while Tirana, Skopje, and Palermo are ranked lowest. Notably, residents of cities with populations under 500,000 report higher satisfaction levels than those in larger cities, and satisfaction levels are generally higher in EU and EFTA cities compared to those in the Western Balkans, with the highest satisfaction observed in northern and western Member States. To aid urban planners and policy-makers, we propose a ranking tool using the BTOPSIS method, capturing nuanced resident perceptions of living conditions across cities. These insights provide valuable guidance for strategic urban development and advancing the smart city agenda across Europe.

A systematic review of TERF behaviour online in relation to sociopsychological group dynamics

ABSTRACT The increasing presence of Trans-Exclusionary Radical Feminists (TERFs) in the media raises questions about their rhetoric and convictions, particularly on platforms like X (formerly Twitter), where contentious debates unfold. Given the limited existing research on TERFs, this study aims to deepen our understanding of the TERF movement’s dynamics. Two document analyses were conducted to uncover insights into their online behaviour and its interplay with sociopsychological group dynamics. The first analysis scrutinized feminist journals and diverse X platform posts to delineate TERFs’ categories and belief systems. The objective of this analysis was to provide a comprehensive overview of recent online discourse concerning gender criticism directed at trans individuals from a feminist perspective. In a second analysis, a literature review compared the identified categories, belief systems, and group dynamics with empirical findings, revealing alignment with recent literature. It was shown that TERFs exhibit typical group dynamics that can also be found in other conservative and authoritative ideologies. Nonetheless, further analyses are needed to fully grasp TERFs’ group dynamics and elucidate their online behaviours and belief structures.

Uncertainty management with quantitative propensity matrix in random permutation set theory

The refined belief structure provides a more comprehensive capability for handling uncertain information. As an emerging belief model, the random permutation set (RPS) can be viewed as a layer-2 belief structure. Unlike fuzzy belief structures, RPS achieves precision without complex computations, as sequential calculations are more manageable. Previous studies typically assume a fixed and equidistant model for weak propensities in RPS. However, in practice, RPSs from different sources often fail to satisfy this assumption. This paper proposes the Quantitative Propensity Matrix (QPM) to distinguish the relative importance of elements within an ordered focal set and introduces a fusion method to integrate weak propensities across various RPSs. The QPM also enables the transformation of permutation mass functions (Perms) into probability mass functions (ProbMFs) through weight allocations. Given the varying reliability of information sources, the proposed method is applied to multi-source information fusion and decision-making processes. Some numerical experiments demonstrate the effectiveness of the proposed approach.

Divergence and Similarity Characteristics for Two Fuzzy Measures Based on Associated Probabilities

Abstract: The article deals with the definitions of the distance, divergence, and similarity characteristics between two finite fuzzy measures, which are generalizations of the same definitions between two finite probability distributions. As is known, a fuzzy measure can be uniquely represented by the so-called its associated probability class (APC). The idea of generalization is that new definitions of distance, divergence, and similarity between fuzzy measures are reduced to the definitions of distance, divergence, and similarity between the APCs of fuzzy measures. These definitions are based on the concept of distance generator. The proof of the correctness of generalizations is provided. Constructed distance, similarity, and divergence relations can be used in such applied problems as: determining the difference between Dempster-Shafer belief structures; Constructions of collaborative filtering similarity relations; non-additive and interactive parameters of machine learning in phase space metrics definition, object clustering, classification and other tasks. In this work, a new concept is used in the fuzzy measure identification problem for a certain multi-attribute decision-making (MADM) environment. For this, a conditional optimization problem with one objective function representing the distance, divergence or similarity index is formulated. Numerical examples are discussed and a comparative analysis of the obtained results is presented.

Non-Linear Saturated Multi-Objective Pseudo-Screening Using Support Vector Machine Learning, Pareto Front, and Belief Functions: Improving Wastewater Recycling Quality

Increasing wastewater treatment efficiency is a primary aim in the circular economy. Wastewater physicochemical and biochemical processes are quite complex, often requiring a combination of statistical and machine learning tools to empirically model them. Since wastewater treatment plants are large-scale operations, the limited opportunities for extensive experimentation may be offset by miniaturizing experimental schemes through the use of fractional factorial designs (FFDs). A recycling quality improvement study that relies on non-linear multi-objective multi-parameter FFD (NMMFFD) datasets was reanalyzed. A published NMMFFD ultrafiltration screening/optimization case study was re-examined regarding how four controlling factors affected three paper mill recycling characteristic responses using a combination of statistical and machine learning methods. Comparative machine learning screening predictions were provided by (1) quadratic support vector regression and (2) optimizable support vector regression, in contrast to quadratic linear regression. NMMFFD optimization was performed by employing Pareto fronts. Pseudo-screening was applied by decomposing the replicated NMMFFD dataset to single replicates and then testing their replicate repeatability by introducing belief functions that sought to maximize credibility and plausibility estimates. Various versions of belief functions were considered, since the novel role of the three process characteristics, as independent sources, created a high level of conflict during the information fusion phase, due to the inherent divergent belief structures. Correlations between two characteristics, but with opposite goals, may also have contributed to the source conflict. The active effects for the NMMFFD dataset were found to be the transmembrane pressure and the molecular weight cut-off. The modified adjustment was pinpointed to the molecular weight cut-off at 50 kDa, while the optimal transmembrane pressure setting persisted at 2.0 bar. This mixed-methods approach may provide additional confidence in determining improved recycling process adjustments. It would be interesting to implement this approach in polyfactorial wastewater screenings with a greater number of process characteristics.

Evidence combination with multi-granularity belief structure for pattern classification

Belief function (BF) theory provides a framework for effective modeling, quantifying uncertainty, and combining evidence, rendering it a potent tool for tackling uncertain decision-making problems. However, with the expansion of the frame of discernment, the increasing number of focal elements processed during the fusion procedure leads to a rapid increase in computational complexity, which limits the practical application of BF theory. To overcome this issue, a novel multi-granularity belief structure (MGBS) method was proposed in this study. The construction of MGBS reduced the number of focal elements and preserved crucial information in the basic belief assignment. This effectively reduced the computational complexity of fusion while ensuring the highest possible classification accuracy. We applied the proposed MGBS algorithm to a human activity recognition task and verified its effectiveness using the University of California, Irvine mHealth, PAMAP2, and Smartphone datasets.

A fuzzy evidential reasoning-based approach for assessing the navigation obstruction risk of shipwrecks in the Yangtze river

ABSTRACT This paper aims to evaluate the navigation obstruction risk represented by shipwrecks in shallow waters based on a fuzzy evidential reasoning approach. The purpose of this approach is to establish a hierarchical decision-making framework that considers ship conditions, traffic environment, distance from sensitive areas, and natural environment; to derive the belief rule base using the IF-THEN rule with a belief structure; and to obtain the crisp values of navigation obstruction risk of shipwrecks via evidential reasoning. This approach is applied to the navigation obstruction risk assessment of 10 historical shipwrecks in the Yangtze River, and the evaluation results are consistent with historical data. Consequently, this approach can be used for assisting in shipwreck salvage decision-making in navigable waters.

Mind Over Misinformation: Investigating the Factors of Cognitive Influences in Information Acceptance

ABSTRACTMany scholars have tried to investigate the identification, characterization, dissemination, and prevention of misinformation in recent years. But a fundamental question that lies behind these investigations is ‘Why do people believe in a piece of information, whether true or false?’. The primary objective of this study is to understand the psychological drivers of belief systems that makes individuals believe any information prior assessing its veracity. The study specifically tries to understand cognitive biases that influence an individual's decision making about information in digital settings. Based on a quantitative survey with 41 participants, we try to induce cognitivity among the participants and try to measure the effect in their decision making. We find a major portion of our participants being cognitively induced which in turn had a significant effect on their decision making while engaging with information. Furthermore, we try to assess whether an individual's political affiliation has any effects in perceived truthfulness while engaging with political information. This study shows us how easily cognitive bias can be induced and how it affects an individual's belief structure in digital platforms.

Understanding Barriers to STEM: Teachers' Insights on African American Underrepresentation

This study focuses on the development of a measurement instrument to identify Middle and High School mathematics and science teachers’ beliefs about the main factors of underrepresentation of African American students in STEM (Science, Technology, Engineering, and Mathematics) fields. The research method using the stages of instrument development were (1) test design which involved construction of initial item pool by conducting extensive review of literature and coding of participating teachers personal statements (2) determination of validity which involved expert review process to confirm construct and face validity of items, (3) pilot testing which involved collecting data from a second set of participants, (4) determination of reliability which involves conducting a reliability analysis based on data collected from pilot testing and (5) determination of factorial structure which involved Exploratory Factor Analysis (EFA) to identify underlying factors in participating teachers’ belief structures. First, to obtain trustworthy information, voluntary middle and high school mathematics and science teachers were asked to write personal statements where they explain their main reasons for choosing teaching as a career. Secondly, qualitative data obtained from participating teachers’ personal statements were coded. Coding was applied to identify and to group the phrases or sentences that convey the same or similar reasons. Then results from an extensive literature review on this topic were blended in teachers’ common expressions which were determined because of coding procedure. Then 8 content experts assessed content validity and face validity. Finally, the survey was piloted to African American middle and high school mathematics and science teachers. Fifty-three (53) surveys were completed and received back from teachers. Then, exploratory factor analysis was conducted to identify any underlying factors in the scale. Reliability analyses were also conducted for both the entire survey and for each of the factors. Results of the study suggested four underlying components: (1) Access and Resources, (2) Role Models and Representation, (3) Bias and Discrimination, (4) Curriculum and Pedagogy.

“Powered by emotions”: Exploring emotion induction in out‐of‐school authentic science learning

AbstractThis study explored the impact of authentic out‐of‐school learning on students' beliefs about their science learning efficacy and career aspirations. The learning activity, designed following an authentic learning framework, was led by research scientists. We examined how students' emotions, induced in an authentic scientific activity, mediated the connection between the perceived authenticity and the self‐efficacy/aspiration beliefs. Data were gathered from 177 secondary science students participating in an out‐of‐school activity using a scanning electron microscope (SEM). Three questionnaires were applied: (1) Perceived authenticity (Post, 7 items, Likert scale); (2) Semantic differential emotion questionnaire (SDEQ) (Pre‐Post, 5 items); and (3) Beliefs questionnaire in two parts: Self‐efficacy and science aspirations (pre‐post, 7 + 5 items, Likert scale). The collected data were integrated into quantitative models of affect with authenticity as an independent variable, the differences in the pre‐post belief structures as the dependent variable, and the emotions as mediators. Multiple regression analyses were performed to develop the models by evaluating the size and significance of the relationships between the variables. The results indicated the perceived authenticity significantly predicted both self‐efficacy and the career aspiration pre‐post differences. However, emotions behaved as a mediating variable only for self‐efficacy growth. An additional model evaluated the connection between students' emotions learning science in school and their experience of authenticity and emotions in the out‐of‐school activity. The study contributes to the literature by revealing underlying affective mechanisms related to out‐of‐school authentic science activities and suggesting theoretical and empirical justifications.

Prevalence, patterns and predictors of paranormal beliefs in The Netherlands: a several-analysts approach

Paranormal beliefs encompass a wide variety of phenomena, including the existence of supernatural entities such as ghosts and witches, as well as extraordinary human abilities such as telepathy and clairvoyance. In the current study, we used a nationally representative sample ( N = 2534 ) to investigate the presence and correlates of paranormal beliefs among the secular Dutch population. The results indicated that most single paranormal phenomena (e.g. belief in clairvoyance) are endorsed by 10–20% of Dutch respondents; however, 55.6% of respondents qualify as paranormal believers based on the preregistered criterion that they believe in at least one phenomenon with considerable certainty. In addition, we invited four analysis teams with different methodological expertise to assess the structure of paranormal beliefs using traditional factor analysis, network analysis, Bayesian network analysis and latent class analysis (LCA). The teams’ analyses indicated adequate fit of a four-factor structure reported in a 1985 study, but also emphasized different conclusions across techniques; network analyses showed evidence against strong connectedness within most clusters, and suggested a five-cluster structure. The application of various analytic techniques painted a nuanced picture of paranormal beliefs and believers in The Netherlands and suggests that despite increased secularization, subgroups of the general population still believe in paranormal phenomena.

A Marxist Approach to Bostonian Missionaries in Hawaii

For centuries, the United States has euphemized their imperial endeavours across the North American continent as they have continued to rely on providential rhetoric to justify their means of colonial expansion. This research critiques beliefs of American exceptionalism in an attempt to expose the hidden ills of America’s colonial efforts. It looks at the activities of Boston’s missionaries in Honolulu, Hawaii, in the nineteenth century and examines the way American identity and understandings of their own exceptionalism manifested on the ground via imperial pursuits. Sponsored by the American Board of Commissioners for Foreign Missions (ABCFM), Boston’s missionaries entered Hawaii in 1819 with the intent to civilize what they perceived as an uncivilized nation. In colonial Hawaii, we will see the extensive blurring of lines between informal and formal empire, which this paper positions as a deliberate transition pivotal for the archipelago’s 1898 annexation. These actions will be observed through a Marxists-based approach to examine how the gradual subjugation of Hawaii’s Indigenous population occurred through religious and educational institutions. Religion and education will therefore be observed as tools used for grander imperial pursuits in colonial Hawaii. As this paper attempts to deconstruct beliefs associated with American exceptionalism, it will look at its origins—that is, Christian belief structures that informed ideas of America’s superiority—and its practical workings on behalf of Bostonian missionaries.

Consumption dynamics with law of small numbers

We propose an intertemporal consumption-saving model by exploring the implications of the Law of Small Numbers (LSN), a belief heuristic stating that any sample realization of a population should be representative of the population. First, the existence of the LSN reduces the precautionary savings demand. More importantly, we show that the LSN belief structure provides an alternative explanation for two fundamental anomalies in consumption theory: (1) excess sensitivity by showing that past changes in income predict future changes in consumption; and (2) excess smoothness by lowering consumption volatility and generating the empirical magnitude.

The structure of ability beliefs in EFL classrooms: A cross-theoretical analysis bridging self-efficacy and perceived competence needs satisfaction

Theoretical parsimony represents one avenue forward for the study of positive psychology in language education. This study examined two well-recognized but interconnected concepts in the context of second language classrooms: academic self-efficacy rooted in Social Cognitive Theory and competence need satisfaction derived from Self Determination Theory. The investigation sought to show the distinctions and intersections in these constructs, underscoring the necessity for empirical scrutiny to establish their coherent definitions. We aim to present both concepts within a unified framework in order to facilitate a meaningful connection between the two theories. A sample comprising 181 students attending a private junior-high school in urban Japan participated in this study by completing widely used scales measuring self-efficacy and perceived competence. The research employed conventional independent cluster confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), bifactor-CFA, bifactor-ESEM, and the S-1 model for comparative analysis. Among these, the S-1 model emerged as the most theoretically sound model with a good fit and absence of anomalies. Furthermore, the factor representing global perceived competence needs satisfaction exhibited a strong association with students’ later academic achievements. These results indicate the potential cross-theoretical nature of competence beliefs and carry implications for both theory and practice in the psychology of language learning.

Rethinking child behavior: Attribution retraining improves child educators' understanding and response

Adults' explanations for child behavior influence their response and, in turn, how child behavior and development progress. Various social-psychological factors (e.g., cognitive belief structures, developmental expectations) help determine the formation of attributions, which are characterized as largely stable. Nonetheless, research demonstrates that attributions can be restructured via attribution retraining (AR). The following study was the first to examine the impact of an AR intervention embedded within training in child development and traumatic stress response. Of particular interest was the malleability and stability of attributions of child behavior, and their contribution to discipline responses among 114 child educators (e.g., teachers, administrators). Post-training, there was a significant decrease in participants' causal attributions and unsupportive intervention preference and a significant increase in trauma-informed attitudes, largely maintained at one-year follow-up, suggesting that this training intervention offers a feasible and scalable method to integrate child development and trauma-informed care to improve perceptions of child behavior.

‘Out of the mouths of babes’ – capturing young children's perceptions of disability through the use of diversity dolls

ABSTRACT This study utilises diversity dolls to elicit young children's perceptions of visual disabilities. The study which involved 20 participants aged between six to seven years old suggests that although many children have positive attitudes towards peers with physical disabilities, attitudes are often grounded in the deficit medical model, with concepts related to assistive devices, medical causes, social consequences, and dependency. The study contributes to the literature through its use of a child centred method and open discussion, which enabled children to offer their innermost thoughts that might have otherwise remained hidden. Some of the comments gathered were quite derogatory, particularly with regards to facial features, and without disability awareness education children risk carrying negative and hostile views into adulthood. Methods which help to unearth children's core belief structures about disability provide an important foundation on which early years practitioners can build intervention programs which critically examine social inequalities and deconstruct dominant discourses, helping young children to develop positive attitudes towards disability.

Mixed uncertainty analysis on pumping by peristaltic hearts using Dempster-Shafer theory.

In this paper, we introduce the numerical strategy for mixed uncertainty propagation based on probability and Dempster-Shafer theories, and apply it to the computational model of peristalsis in a heart-pumping system. Specifically, the stochastic uncertainty in the system is represented with random variables while epistemic uncertainty is represented using non-probabilistic uncertain variables with belief functions. The mixed uncertainty is propagated through the system, resulting in the uncertainty in the chosen quantities of interest (QoI, such as flow volume, cost of transport and work). With the introduced numerical method, the uncertainty in the statistics of QoIs will be represented using belief functions. With three representative probability distributions consistent with the belief structure, global sensitivity analysis has also been implemented to identify important uncertain factors and the results have been compared between different peristalsis models. To reduce the computational cost, physics constrained generalized polynomial chaos method is adopted to construct cheaper surrogates as approximations for the full simulation.

Defeatist Beliefs and Schizotypy in Adolescents and Emerging Adults

Defeatist beliefs involved overgeneralized negative beliefs regarding the ability to successfully perform tasks and accomplish goals. These cognitive errors have been shown to affect one’s ability to accurately assess and react in social situations and serve as hallmarks of many mood disorders. These negative beliefs also exist at high rates in adults with schizophrenia spectrum diagnoses. There is evidence for these beliefs existing during prodromal periods in young adults at-risk for psychosis, especially if they exhibit motivational or interpersonal difficulties (negative symptoms). However, there is little known about when these beliefs first emerge and whether they predate clinical disorder during earlier life stages where only subclinical presentations of risk (schizotypy) may be present. To address this research gap and help to inform cognitive-behavioral interventions targeting defeatist belief structures, we investigated the relations between defeatist beliefs and schizotypy in a sample of adolescents and emerging adults. Participants were 86 high school students (ages 14-17) and 270 college students (ages 18-22). Participants completed a 30-minute, self-report survey on defeatist beliefs and schizotypy. Our analyses found little difference in mean or standard deviation in defeatist beliefs or schizotypy between our two samples, with a robust positive association (r=0.46) when the samples where aggregated. These findings suggests that defeatist beliefs correspond with subclinical risk more-or-less on a continuum during this wider period of life potentially helping to understand variability in symptom severity. Future research is needed to clarify the nature of this relationship and to inform future interventions. Our finding suggests that cognitive behavioral approaches, which are well suited to target and modify defeatist beliefs, could serve a preventative role in the risk for future psychosis in at-risk adolescents and emerging adults.

Psychologists return to the first question of Western philosophy.

When ancient humans gained the ability to investigate abstract questions, what first question did they pose? This article offers a novel, sweeping, historical analysis with important implications for psychological theory. The story begins with identifying the first question in Ancient Greek philosophy as "Where am I?" with particular interest in the world's overarching basic traits. For example, Pythagoras proposed the world was defined by beauty and Heraclitus suggested change. Though this discourse has traditionally puzzled historians, recent psychological research suggests it might have been largely a debate over primal world beliefs, an emerging research topic that this article introduces and situates historically. Recently, the latent structure of primal world beliefs was mapped statistically, revealing 26 dimensions. Most of these beliefs were new to psychologists, yet already posed by ancient philosophers-including Pythagoras' Beautiful world belief and Heraclitus' Changing world belief. Identifying first questions in early history may have value for psychological theorizing because it hints at something that social psychologists have long suspected: that humans are creatures fundamentally driven to understand their situation and what it calls for. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Reacting to the Past Games in the Criminal Justice Classroom

While student engagement and student-centered learning have been demonstrated, at length, to increase academic achievement, how can criminal justice as an academic field continue to effectively engage students in a contemporary society that appears to be ever more based on dogmatic tribes and beliefs? The answer might be reacting to the past (RTTP) games which utilize “elaborately designed role-playing games set in pivotal historical moments of clashing ideas and interests” to increase student engagement and academic performance. When confronted with a controversial topic in criminal justice, one that fits well into the aforementioned dogmatic tribal belief structure, instructors might see the task of student engagement daunting. Utilizing RTTP as part of their pedagogical approach would provide instructors with a tool that places students in similar controversial moments with little to argue as the historical events the RTTP game is based on is well recorded.