While Thomas Kuhn's theory of scientific revolutions does not specifically deal with validation, the validation of simulations can be related in various ways to Kuhn's theory: 1) Computer simulations are sometimes depicted as located between experiments and theoretical reasoning, thus potentially blurring the line between theory and empirical research. Does this require a new kind of research logic that is different from the classical paradigm which clearly distinguishes between theory and empirical observation? I argue that this (...) is not the case. 2) Another typical feature of computer simulations is their being ``motley'' (Winsberg 2003) with respect to the various premises that enter into simulations. A possible consequence is that in case of failure it can become difficult to tell which of the premises is to blame. Could this issue be understood as fostering Kuhn's mild relativism with respect to theory choice? I argue that there is no need to worry about relativism with respect to computer simulations, in particular. 3) The field of social simulations, in particular, still lacks a common understanding concerning the requirements of empirical validation of simulations. Does this mean that social simulations are still in a pre-scientific state in the sense of Kuhn? My conclusion is that despite ongoing efforts to promote quality standards in this field, lack of proper validation is still a problem of many published simulation studies and that, at least large parts of social simulations must be considered as pre-scientific. (shrink)

The terms ‘verification’ and ‘validation’ are widely used in science, both in the natural and the social sciences. They are extensively used in simulation, often associated with the need to evaluate models in different stages of the simulation development process. Frequently, terminological ambiguities arise when researchers conflate, along the simulation development process, the technical meanings of both terms with other meanings found in the philosophy of science and the social sciences. This article considers the problem of verification and (...) class='Hi'>validation in social science simulation along five perspectives: The reasons to address terminological issues in simulation; the meaning of the terms in the philosophical sense of the problem of “truth”; the observation that some debates about these terms in simulation are inadvertently more terminological than epistemological; the meaning of the terms in the technical context of the simulation development process; and finally, a comprehensive outline of the relation between terminology used in simulation, different types of models used in the development process and different epistemological perspectives. (shrink)

This paper proposes an extensionalist analysis of computer simulations (CSs). It puts the emphasis not on languages nor on models, but on symbols, on their extensions, and on their various ways of referring. It shows that chains of reference of symbols in CSs are multiple and of different kinds. As they are distinct and diverse, these chains enable different kinds of remoteness of reference and different kinds of validation for CSs. Although some methodological papers have already underlined the (...) role of these various relationships of reference in CSs and of cross-validations, this diversity is still overlooked in the epistemological literature on CSs. As a consequence, a particular outcome of this analytical view is an ability to classify existing epistemological theses on CSs according to what their authors choose to select and put at the forefront: either the extensions of symbols, or the symbol-types, or the symbol-tokens, or the internal denotational hierarchies of the CS or the reference of these hierarchies to external denotational hierarchies. Through the adoption of this extensionalist view, it also becomes possible to explain more precisely the reasons why some complete reduction of CSs to classical epistemic paradigms such as “experiment” or “theoretical argument” remains doubtful. On this last point, in particular, this paper is in agreement with what many epistemologists already have acknowledged. (shrink)

There is an ongoing debate on whether or to what degree computer simulations can be likened to experiments. Many philosophers are sceptical whether a strict separation between the two categories is possible and deny that the materiality of experiments makes a difference (Morrison 2009, Parker 2009, Winsberg 2010). Some also like to describe computer simulations as a “third way” between experimental and theoretical research (Rohrlich 1990, Axelrod 2003, Kueppers/Lenhard 2005). In this article I defend the view that computer (...) simulations are not experiments but that they are tools for evaluating the consequences of theories and theoretical assumptions. In order to do so the (alleged) similarities and differences between simulations and experiments are examined. It is found that three fundamental differences between simulations and experiments remain: 1) Only experiments can generate new empirical data. 2) Only Experiments can operate directly on the target system. 3) Experiments alone can be employed for testing fundamental hypotheses. As a consequence, experiments enjoy a distinct epistemic role in science that cannot completely be superseded by computer simulations. This finding in connection with a discussion of border cases such as hybrid methods that combine measurement with simulation shows that computer simulations can clearly be distinguished from empirical methods. It is important to understand that computer simulations are not experiments, because otherwise there is a danger of systematically underestimating the need for empirical validation of simulations. (shrink)

This paper is intended as a critical examination of the question of when and under what conditions the use of computer simulations is beneficial to scientific explanations. This objective is pursued in two steps: First, I try to establish clear criteria that simulations must meet in order to be explanatory. Basically, a simulation has explanatory power only if it includes all causally relevant factors of a given empirical configuration and if the simulation delivers stable results within the measurement (...) inaccuracies of the input parameters. -/- In the second step, I examine a few examples of Axelrod-style simulations as they have been used to understand the evolution of cooperation (Axelrod, Schüßler). These simulations do not meet the criteria for explanatory validity and it can be shown, as I believe, that they lead us astray from the scientific problems they have been addressed to solve. (shrink)

The credibility of digital computer simulations has always been a problem. Today, through the debate on verification and validation, it has become a key issue. I will review the existing theses on that question. I will show that, due to the role of epistemological beliefs in science, no general agreement can be found on this matter. Hence, the complexity of the construction of sciences must be acknowledged. I illustrate these claims with a recent historical example. Finally I temperate (...) this diversity by insisting on recent trends in environmental sciences and in industrial sciences. (shrink)

The formal and empirical-generative perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the social sciences. Simulation does not resemble formal demonstrations or generative mechanisms that deductively explain how certain models are sufficient to generate emergent macrostructures of interest. The description of scientific practice implies additional epistemic conceptions of scientific knowledge. Three kinds of knowledge that account for a comprehensive description of the discipline were identified: formal, empirical and intentional knowledge. The use of formal (...) conceptions of computation for describing simulation is refuted; the roles of programming languages according to intentional accounts of computation are identified; and the roles of iconographic programming languages and aesthetic machines in simulation are characterized. The roles that simulation and intentional decision making may be able to play in a participative information society are also discussed. (shrink)

The classical theory of computation does not represent an adequate model of reality for simulation in the social sciences. The aim of this paper is to construct a methodological perspective that is able to conciliate the formal and empirical logic of program verification in computer science, with the interpretative and multiparadigmatic logic of the social sciences. We attempt to evaluate whether social simulation implies an additional perspective about the way one can understand the concepts of program and computation. We demonstrate (...) that the logic of social simulation implies at least two distinct types of program verifications that reflect an epistemological distinction in the kind of knowledge one can have about programs. Computer programs seem to possess a causal capability (Fetzer, 1999) and an intentional capability that scientific theories seem not to possess. This distinction is associated with two types of program verification, which we call empirical and intentional verification. We demonstrate, by this means, that computational phenomena are also intentional phenomena, and that such is particularly manifest in agent-based social simulation. Ascertaining the credibility of results in social simulation requires a focus on the identification of a new category of knowledge we can have about computer programs. This knowledge should be considered an outcome of an experimental exercise, albeit not empirical, acquired within a context of limited consensus. The perspective of intentional computation seems to be the only one possible to reflect the multiparadigmatic character of social science in terms of agent-based computational social science. We contribute, additionally, to the clarification of several questions that are found in the methodological perspectives of the discipline, such as the computational nature, the logic of program scalability, and the multiparadigmatic character of agent-based simulation in the social sciences. (shrink)

Simulation models of the Reiterated Prisoner's Dilemma have been popular for studying the evolution of cooperation since more than 30 years now. However, there have been practically no successful instances of empirical application of any of these models. At the same time this lack of empirical testing and confirmation has almost entirely been ignored by the modelers community. In this paper, I examine some of the typical narratives and standard arguments with which these models are justified by their authors despite (...) the lack of empirical validation. I find that most of the narratives and arguments are not at all compelling. None the less they seem to serve an important function in keeping the simulation business running despite its empirical shortcomings. (shrink)

Simulation models of the Reiterated Prisoner's Dilemma have been popular for studying the evolution of cooperation since more than 30 years now. However, there have been practically no successful instances of empirical application of any of these models. At the same time this lack of empirical testing and confirmation has almost entirely been ignored by the modelers community. In this paper, I examine some of the typical narratives and standard arguments with which these models are justified by their authors despite (...) the lack of empirical validation. I find that most of the narratives and arguments are not at all compelling. None the less they seem to serve an important function in keeping the simulation business running despite its empirical shortcomings. (shrink)

This article reports an exploratory survey of the structure of interdisciplinary research in Agent-Based Social Simulation. One hundred and ninety six researchers participated in the survey completing an on-line questionnaire. The questionnaire had three distinct sections, a classification of research domains, a classification of models, and an inquiry into software requirements for designing simulation platforms. The survey results allowed us to disambiguate the variety of scientific goals and modus operandi of researchers with a reasonable level of detail, and to identify (...) a classification of agent-based models used in simulation. In particular, in the interdisciplinary context of social-scientific modelling, agent-based computational modelling and computer engineering, we analyse the extent to which these paradigmatic models seem to be mutually instrumental in the field. We expect that our proposal may improve the viability of submitting, explaining and comparing agent-based simulations in articles, which is an important methodological requirement to consolidate the field. We also expect that it will motivate other proposals that could further validate, extend or change ours, in order to refine the classification with more types of models. (shrink)

Mathematical models are a well established tool in most natural sciences. Although models have been neglected by the philosophy of science for a long time, their epistemological status as a link between theory and reality is now fairly well understood. However, regarding the epistemological status of mathematical models in the social sciences, there still exists a considerable unclarity. In my paper I argue that this results from specific challenges that mathematical models and especially computer simulations face in the social (...) sciences. The most important difference between the social sciences and the natural sciences with respect to modeling is that in the social sciences powerful and well confirmed background theories (like Newtonian mechanics, quantum mechanics or the theory of relativity in physics) do not exist in the social sciences. Therefore, an epistemology of models that is formed on the role model of physics may not be appropriate for the social sciences. I discuss the challenges that modeling faces in the social sciences and point out their epistemological consequences. The most important consequences are that greater emphasis must be placed on empirical validation than on theoretical validation and that the relevance of purely theoretical simulations is strongly limited. (shrink)

The simulation hypothesis is a view of the nature of reality, suggesting that our world is likely a computer simulation created by an advanced civilization. In contrast, illusionism is a theory about the nature of phenomenal consciousness, arguing that phenomenal consciousness is an illusion and can be fully explained in physical terms. I argue that if our world is a simulated construct, illusionism could be incorrect. Specifically, even if our phenomenal experiences can be explained as illusionism suggests, advanced civilizations could (...) still create subjectively indistinguishable experiences by constructing a psychological system external to our world. Since we cannot determine which scenario we belong to, the illusionist explanation is not universally valid. Furthermore, I argue that even if the simulation hypothesis is impossible, illusionism remains flawed. Consequently, while the simulation hypothesis may function as a mere assumption, it exposes the inherent limitations of both illusionism and physicalism. (shrink)

In this paper we investigate with a case study from chemistry under what conditions a simulation can serve as a surrogate for an experiment. The case-study concerns a simulation of H2-formation in outer space. We find that in this case the simulation can act as a surrogate for an experiment, because there exists comprehensive theoretical background knowledge in form of quantum mechanics about the range of phenomena to which the investigated process belongs and because any particular modelling assumptions as can (...) be justified. If these requirements are met then direct empirical validation may even be dispensable. We conjecture that this is not the case in the absence of comprehensive theoretical background knowledge. (shrink)

The aim of this paper is to discuss the “Framework for M&S with Agents” (FMSA) proposed by Zeigler et al. [2000, 2009] in regard to the diverse epistemological aims of agent simulations in social sciences. We first show that there surely are great similitudes, hence that the aim to emulate a universal “automated modeler agent” opens new ways of interactions between these two domains of M&S with agents. E.g., it can be shown that the multi-level conception at the core (...) of the FMSA is similar in both contexts: notions of “levels of system specifi cation”, “behavior of models”, “simulator”and “endomorphic agents” can be partially translated in the terms linked to the “denotational hierarchy” (DH) recently introduced in a multi-level centered epistemology of M&S. Second, we suggest considering the question of “credibility” of agent M&S in social sciences when we do not try to emulate but only to simulate target systems. Whereas a stringent and standardized treatment of the heterogeneous internal relations (in the DH) between systems of formalisms is the key problem and the essential challenge in the scope of Agent M&S driven engineering, it is urgent too to address the problem of the external relations (and of the external validity, hence of the epistemic power and credibility) of such levels of formalisms in the specific domains of agent M&S in social sciences, especially when we intend to introduce the concepts of activity tracking. (shrink)

The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational (...) explanation, I argue that large-scale simulations require that the explanandum phenomenon is identified; otherwise, the explanatory value of such explanations is difficult to establish, and testing the model empirically by comparing its behavior with the explanandum remains practically impossible. The completeness of the explanation, and hence of the explanatory value of the explanatory model, is to be assessed vis-à-vis the explanandum phenomenon, which is not to be conflated with raw observational data and may be idealized. I argue that idealizations, which include building models of a single phenomenon displayed by multi-functional mechanisms, lumping together multiple factors in a single causal variable, simplifying the causal structure of the mechanisms, and multi-model integration, are indispensable for complex systems such as brains; otherwise, the model may be as complex as the explanandum phenomenon, which would make it prone to so-called Bonini paradox. I conclude by enumerating dimensions of empirical validation of explanatory models according to new mechanism, which are given in a form of a “checklist” for a modeler. (shrink)

In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [Boulnois 1999]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...) relationship between the representation and the represented object. Criteria of evaluation such as “validity”, “adequacy” or “truth”, as mentioned in chapter 4, make sense only with respect to these three dimensions. An evaluation can thus (1) depend on the ontological nature of the object of knowledge, (2) relate to the relationship between subject and object—including the structures (cognitive, social) which organize this relationship, or (3) relate to the relation of similarity between the object and its representation as well. The relevant criteria of evaluation thus depend on the points of view adopted on these questions. As there are indeed a plurality of points of view in this field, the goal of this appendix is to summarize, as briefly as possible, the various positions adopted by the philosophers and to refer to the relevant texts of reference for more information. The first section introduces useful discussions about the philosophy of theoretical knowledge and general epistemology, from a quasi-historical perspective. Section two discusses the intermediary but central notion of models. Section three, more exploratory, intro-duces an approach to simulation as “concrete experiment”. It suggests that such a frequent claim in the literature, when precisely evaluated, can, to some extent, renew both the representational and the linguistic views on simulation. (shrink)

In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [BOU 99]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...) relationship between the representation and the represented object. Criteria of evaluation such as “validity”, “adequacy” or “truth”, as mentioned in [AMB 07], make sense only with respect to these three dimensions. An evaluation can thus (1) depend on the ontological nature of the object of knowledge, (2) relate to the relationship between subject and object—including the structures (cognitive, social) which organize this relationship, or (3) relate to the relation of similarity between the object and its representation as well. The relevant criteria of evaluation thus depend on the points of view adopted on these questions. As there are indeed a plurality of points of view in this field, the goal of this appendix is to summarize, as briefly as possible, the various positions adopted by the philosophers and to refer to the relevant texts of reference for more information (for a first outline [CHA 76, SCH 01]). The first section 1 introduces useful discussions about the philosophy of theoretical knowledge and general epistemology, from a quasi-historical perspective. Section two 2 discusses the intermediary but central notion of models. Section three 3, more exploratory, introduces an approach to simulation as “concrete experiment”. It suggests that such a frequent claim in the literature, when precisely evaluated, can, to some extent, renew both the representational and the linguistic views on simulation. (shrink)

In the last 20 years, a stream of research emerged under the label of „complex problem solving“ (CPS). This research was intended to describe the way people deal with complex, dynamic, and intransparent situations. Complex computer-simulated scenarios were as stimulus material in psychological experiments. This line of research lead to subtle insights into the way how people deal with complexity and uncertainty. Besides these knowledge-rich, realistic, intransparent, complex, dynamic scenarios with many variables, a second line of research used more simple, (...) knowledge-lean scenarios with a low number of variables („minimal complex systems“, MCS) that have been proposed recently in problem-solving research for the purpose of educational assessment. In both cases, the idea behind the use of microworlds is to increase validity of problem solving tasks by presenting interactive environments that can be explored and controlled by participants while pursuing certain action goals. The main argument presented here is: both types of systems - CPS and MCS – can only be dealt with successfully if causal dependencies between input and output variables are identified and used for system control. System knowledge is necessary for control and intervention. But CPS and MCS differ in their way of how causal dependencies are identified and how the mental model is constructed; therefore, they cannot be compared directly to each other with respect to the cognitive processes that are necessary for solving the tasks. Knowledge-poor MCS tasks address only a small fraction of the cognitive processes and structures needed for knowledge-rich CPS situations. (shrink)

An inference is valid if it guarantees the transferability of knowledge from the premisses to the conclusion. If knowledge is here understood as demonstrative knowledge, and demonstration is explained as a chain of valid inferences, we are caught in an explanatory circle. In recent lectures, Per Martin-Löf has sought to avoid the circle by specifying the notion of knowledge appealed to in the explanation of the validity of inference as knowledge of a kind weaker than demonstrative knowledge. The resulting explanation (...) is the main topic of this article. (shrink)

In computer science, Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Deep Learning is a new field of research. One of the branches of Artificial Intelligence Science deals with the creation of theories and algorithms that (...) allow the machine to learn by simulating neurons in the human body. Most in-depth learning research focuses on finding high-level methods. The strippers analyze a large data set using linear and nonlinear transformations. The method of deep learning is used in the detection of several diseases including blood cell diseases and their classification using the radiography of blood cells to help decision makers to know the type of blood cell and its associated diseases and the results will be presented in detail and discussed. This thesis is using python language and deep learning to detect blood cell diseases and their classifications. The proposed deep learning model was trained, validated and the tested. The accuracy of proposed model was 98.00%. (shrink)

In Kant’s Critique of Pure Reason and the Method of Metaphysics (CUP 2023), I argue that the first Critique is not only a ‘propaedeutic’ to metaphysics, but actually already establishes parts of metaphysics. These parts belong to what Kant calls transcendental philosophy. Additionally, I also provide an account of Kant’s critique of dogmatism and Wolff as its main defender. In this paper, I take up Luigi Filieri’s and Davide Dalla Rosa’s invitation to further develop my characterization of transcendental philosophy and (...) I respond to Michael Walschots’s objections against my interpretation of Kant’s critique of Wolff’s dogmatism. (shrink)

Behavior oftentimes allows for many possible interpretations in terms of mental states, such as goals, beliefs, desires, and intentions. Reasoning about the relation between behavior and mental states is therefore considered to be an effortful process. We argue that people use simple strategies to deal with high cognitive demands of mental state inference. To test this hypothesis, we developed a computational cognitive model, which was able to simulate previous empirical findings: In two-player games, people apply simple strategies at first. They (...) only start revising their strategies when these do not pay off. The model could simulate these findings by recursively attributing its own problem solving skills to the other player, thus increasing the complexity of its own inferences. The model was validated by means of a comparison with findings from a developmental study in which the children demonstrated similar strategic developments. (shrink)

Behavior oftentimes allows for many possible interpretations in terms of mental states, such as goals, beliefs, desires, and intentions. Reasoning about the relation between behavior and mental states is therefore considered to be an effortful process. We argue that people use simple strategies to deal with high cognitive demands of mental state inference. To test this hypothesis, we developed a computational cognitive model, which was able to simulate previous empirical findings: In two-player games, people apply simple strategies at first. They (...) only start revising their strategies when these do not pay off. The model could simulate these findings by recursively attributing its own problem solving skills to the other player, thus increasing the complexity of its own inferences. The model was validated by means of a comparison with findings from a developmental study in which the children demonstrated similar strategic developments. (shrink)

Behavior oftentimes allows for many possible interpretations in terms of mental states, such as goals, beliefs, desires, and intentions. Reasoning about the relation between behavior and mental states is therefore considered to be an effortful process. We argue that people use simple strategies to deal with high cognitive demands of mental state inference. To test this hypothesis, we developed a computational cognitive model, which was able to simulate previous empirical findings: In two-player games, people apply simple strategies at first. They (...) only start revising their strategies when these do not pay off. The model could simulate these findings by recursively attributing its own problem solving skills to the other player, thus increasing the complexity of its own inferences. The model was validated by means of a comparison with findings from a developmental study in which the children demonstrated similar strategic developments. (shrink)

This study developed and validated E-learning Self-directed Interactive Modules (E-SelfIMo) for Earth Science. The study employed Research and Development method, using the Borg and Gall development procedure, in creating eight e-modules using Kotobee software, evaluating them by experts and students, and determining their effectiveness in terms of students' conceptual understanding. Experts agreed that E-SelfIMo met the DepEd standards for non-printed learning materials, and students attested to their high validity in content, format, and usefulness. Pretest and posttest results for the effectiveness (...) of E-SelfIMo revealed that students exposed to the E-SelfIMo have progressed from “Near Mastery” to “Near Full Mastery” in the chosen Earth Science topics, showing more significant improvement in their conceptual understanding than the control group. This study concludes that E-SelfIMo supports interactive, active, and self-directed learning thereby, improving students’ motivation, engagement, interest, and performance. The E-SelfIMo could be used with technology integration as a teaching and learning tool. -/- . (shrink)

Havstad (2022) argues that the argument from inductive risk for the claim that non-epistemic values have a legitimate role to play in the internal stages of science is deductively valid. She also defends its premises and thus soundness. This is, as far as we are aware, the best reconstruction of the argument from inductive risk in the existing literature. However, there is a small flaw in this reconstruction of the argument from inductive risk which appears to render the argument invalid. (...) This flaw is superficial, and a small amendment to it rescues the claim of validity. (shrink)

In this paper we describe a few interrelated issues for validating theories that posit levels of consciousness. First, validating levels of consciousness requires consensus about the ordering of conscious states, which cannot be easily achieved. This problem is particularly severe if we believe conscious states can be irreducibly smeared over time. Second, the relationship between conscious states is probably sometimes intransitive, which means levels of consciousness will not be amenable to a single continuous measure. Finally, even if a multidimensional approach (...) to levels of consciousness is adopted, we argue that there are further problems for its validation. (shrink)

This study used a structural equation modelling approach to assess the association between employee work- life policies, psychological empowerment, and academic staff job commitment in universities in Cross River State, Nigeria. Three null hypotheses were formulated to guide the study following a descriptive survey research design. Multistage sampling procedure was adopted in the selection of 315 academic staff from two universities in the study area. “Work-Life Policies, Psychological Empowerment and Job Commitment Questionnaire (WPPEJCQ)” was used as the instrument for data (...) collection. The construct validity of the instrument was ascertained through an Exploratory Factor Analysis (EFA) using the Principal Component Analysis (PCA). The Kaiser-Meyer-Ohlin of .894 and the Bartlett coefficient of 7795.820 were obtained. Several fit indices of Confirmatory Factor Analysis were used to accept the model such as RMSEA=.031, TLI=.969, CFI=.971 and many others. The null hypotheses were all tested using Path analysis. Findings revealed, among others, that there is a significant effect of work-life policies on the affective (β=.774,t=21.636,p<.05), continuance (β=.450,t=8.932,p<.05), and normative (β=490,t=9.967,p<.05) dimensions of academic staff commitment; furthermore, psychological empowerment has a significant effect on the affective (β=.795,t=23.199,p<.05), continuance (β=.501,t=10.261,p<.05) and normative (β = .520, t = 10.795, p< .05) dimensions of staff commitment; and there is a significant composite effect of work-life policies and psychological empowerment on the affective, continuance, and normative commitment levels of academic staff in universities. Based on these findings, conclusions and recommendations were made. (shrink)

Interdisciplinary research collaboration is crucial for addressing complex global challenges, and measuring researchers' perceptions of it is vital. The Perception of Interdisciplinary Research Collaboration (PIRC) Scale was meticulously developed and validated in this study to enable researchers to assess these perceptions comprehensively. The scale was developed in line with the team science theory. This cross-sectional study involved concept analysis, face and content validity, item pretesting, and pilot testing. A panel of eight specialists from relevant fields meticulously reviewed the items in (...) the instrument, and their inputs and suggestions were followed to refine the instrument, resulting in a 64-item questionnaire. A sample of 1,932 academic staff members with interdisciplinary research experience were selected from six universities in South-South Nigeria for a pilot study. A simple random sampling technique was employed in selecting these participants. Exploratory factor analysis yielded six underlying dimensions within the PIRC Scale, such as: "challenges of Interdisciplinary Disciplinary Research (IDR) collaboration," "IDR collaborative experiences," "motivations for IDR collaboration," "benefits of IDR collaboration," "career impact of IDR collaboration," and "IDR team dynamics." Confirmatory factor analysis confirmed this structure and revealed the bifactor model as the best-fitting model over the unidimensional, oblique and higher-order models. Utilising the Fornell-Larcker approach, strong convergent and discriminant validity was established across all dimensions, with Average Variance Extracted (AVE) above .50 and the square root of the AVE for all factors being greater than the correlation coefficients of each factor with other factors. Cronbach's alpha and McDonald's omega values exceeded the acceptable threshold of 0.70, with item-total correlation analyses further supporting the reliability of each sub-scale and the overall instrument. In conclusion, the PIRC scale can be valuable for researchers, institutions, and policymakers to assess and enhance interdisciplinary research collaboration. It can empower stakeholders to obtain useful information about researchers' perceptions of interdisciplinary research, promote effective collaboration, allocate resources efficiently, and foster innovation. (shrink)

This paper presents five studies on the development and validation of a scale of intellectual humility. This scale captures cognitive, affective, behavioral, and motivational components of the construct that have been identified by various philosophers in their conceptual analyses of intellectual humility. We find that intellectual humility has four core dimensions: Open-mindedness (versus Arrogance), Intellectual Modesty (versus Vanity), Corrigibility (versus Fragility), and Engagement (versus Boredom). These dimensions display adequate self-informant agreement, and adequate convergent, divergent, and discriminant validity. In particular, (...) Open-mindedness adds predictive power beyond the Big Six for an objective behavioral measure of intellectual humility, and Intellectual Modesty is uniquely related to Narcissism. We find that a similar factor structure emerges in Germanophone participants, giving initial evidence for the model’s cross-cultural generalizability. (shrink)

Do we live in a computer simulation? I will present an argument that the results of a certain experiment constitute empirical evidence that we do not live in, at least, one type of simulation. The type of simulation ruled out is very specific. Perhaps that is the price one must pay to make any kind of Popperian progress.

This article argues for the formal validity of and the truth of the premises and conclusion of a version of Aquinas' "Third Way" that says: If each of the parts of nature is contingent, the whole of nature is contingent. Each of the parts of nature is contingent. Therefore, the whole of nature is contingent--where "contingent" means having a cause and not existing self-sufficiently.

Historically, the hypothesis that our world is a computer simulation has struck many as just another improbable-but-possible “skeptical hypothesis” about the nature of reality. Recently, however, the simulation hypothesis has received significant attention from philosophers, physicists, and the popular press. This is due to the discovery of an epistemic dependency: If we believe that our civilization will one day run many simulations concerning its ancestry, then we should believe that we are probably in an ancestor simulation right now. This (...) essay examines a troubling but underexplored feature of the ancestor-simulation hypothesis: the termination risk posed by both ancestor-simulation technology and experimental probes into whether our world is an ancestor simulation. This essay evaluates the termination risk by using extrapolations from current computing practices and simulation technology. The conclusions, while provisional, have great implications for debates concerning the fundamental nature of reality and the safety of contemporary physics. (shrink)

Instructional material is an integral part of teaching and learning process. Validating instructional materials is imperative to ensure quality before widespread utilization. This study validated the developed Gamified Instructional Material (GIM) in genetics for grade 12 STEM students. It employed the descriptive-developmental research design involving 41 STEM students and 11 Biology education experts chosen through purposive sampling. Findings revealed that students and experts strongly agreed that the GIM satisfied the criteria for a sound and valid instructional material. Further, the significant (...) change in the pretest and posttest scores of students indicated an improvement of their knowledge in genetics. It is recommended that the GIM be used as supplementary instructional material in teaching genetics. (shrink)

We report on an exploratory study of the way eight mid-level undergraduate mathematics majors read and reflected on four student-generated arguments purported to be proofs of a single theorem. The results suggest that mid-level undergraduates tend to focus on surface features of such arguments and that their ability to determine whether arguments are proofs is very limited -- perhaps more so than either they or their instructors recognize. We begin by discussing arguments (purported proofs) regarded as texts and validations of (...) those arguments, i.e., reflections of individuals checking whether such arguments really are proofs of theorems. We relate the way the mathematics research community views proofs and their validations to ideas from reading comprehension and literary theory. We then give a detailed analysis of the four student-generated arguments and finally analyze the eight students' validations of them. (shrink)

I want to model a finite, fallible cognitive agent who imagines that p in the sense of mentally representing a scenario—a configuration of objects and properties—correctly described by p. I propose to capture imagination, so understood, via variably strict world quantifiers, in a modal framework including both possible and so-called impossible worlds. The latter secure lack of classical logical closure for the relevant mental states, while the variability of strictness captures how the agent imports information from actuality in the imagined (...) non-actual scenarios. Imagination turns out to be highly hyperintensional, but not logically anarchic. Section 1 sets the stage and impossible worlds are quickly introduced in Sect. 2. Section 3 proposes to model imagination via variably strict world quantifiers. Section 4 introduces the formal semantics. Section 5 argues that imagination has a minimal mereological structure validating some logical inferences. Section 6 deals with how imagination under-determines the represented contents. Section 7 proposes additional constraints on the semantics, validating further inferences. Section 8 describes some welcome invalidities. Section 9 examines the effects of importing false beliefs into the imagined scenarios. Finally, Sect. 10 hints at possible developments of the theory in the direction of two-dimensional semantics. (shrink)

Background: Moral Growth Mindset (MGM) is a belief about whether one can become a morally better person through efforts. Prior research showed that MGM is positively associated with promotion of moral motivation among adolescents and young adults. We developed and tested the English version of the MGM measure in this study with data collected from college student participants. Methods: In Study 1, we tested the reliability and validity of the MGM measure with two-wave data (N = 212, Age mean = (...) 24.18 years, SD = 7.82 years). In Study 2, we retested the construct validity of the MGM measure once again and its association with other moral and positive psychological indicators to test its convergent and discriminant validity (N = 275, Age mean = 22.02 years, SD = 6.34 years). Results: We found that the MGM measure was reliable and valid from Study 1. In Study 2, the results indicated that the MGM was well correlated with other moral and positive psychological indicators as expected. Conclusions: We developed and validated the English version of the MGM measure in the present study. The results from studies 1 and 2 supported the reliability and validity of the MGM measure. Given this, we found that the English version of the MGM measure can measure one’s MGM as we intended. (shrink)

This paper provides a historical analysis of a shift in the way animal models of mental disorders were conceptualized: the shift from the mid-twentieth-century view, adopted by some, that animal models model syndromes classified in manuals such as the Diagnostic and Statistical Manual of Mental Disorders (DSM), to the later widespread view that animal models model component parts of psychiatric syndromes. I argue that in the middle of the twentieth century the attempt to maximize the face validity of animal models (...) sometimes led to the pursuit of the ideal of an animal model that represented a behaviorally defined psychiatric syndrome as described in manuals such as the DSM. I show how developments within psychiatric genetics and related criticism of the DSM in the 1990s and 2000s led to the rejection of this ideal and how researchers in the first decade of the twenty-first century came to believe that animal models of mental disorders should model component parts of mental disorders, adopting a so-called endophenotype approach. (shrink)

Starting from some remarks about the use of models in psychology, Human Information Processing (henceforth called H.I.P.) models which sometimes use computer simulation will be examined. An attempt to show that simulation in psychology does not necessarily imply an H.I.P. approach is then made.

This research was carried out in order to verify by simulation Mendel’s laws and seek for the clarification, from the author’s point of view, the Mendel-Fisher controversy. It was demonstrated from: the experimental procedure and the first two steps of the Hardy-Weinberg law, that the null hypothesis in such experiments is absolutely and undeniably true. Consequently, repeating hybridizing experiments as those showed by Mendel, it makes sense to expect a highly coincidence between the observed and the expected cell frequencies. By (...) simulation, 30 random samples were generated with size equal to the number of observations reported by Mendel for his single trait trial, in this case, seed shape; assuming complete dominance, with genes A and a; likewise, it was simulated the results for the experiment with two traits, segregating in separate chromosomes, in this case seed shape, as before, and albumen color, with genes B and b, both loci with complete dominance. In the case of a single trait, the data only showed evidence for rejecting the null hypothesis (Ho ) in 1/30 samples, with (P<0.05). In the case of the 30 samples of the two traits experiment, (Ho ) was rejected only on 3/30 times, when it was set a = 0.05. In both simulations there was a high correspondence between the observed and expected cell frequencies, which is simply due to the fact that (Ho ) is true, and under these conditions, that is what would to expect. It was concluded, that Mendel had no reason to manipulate his data in order to make them to coincide with his beliefs. Therefore, in experiment with a single trait, and in experiments with two traits assuming complete dominance, segregation ratios are 3:1; and 9:3:3:1, respectively. Consequently, Mendel’s laws, under the conditions as were described are absolutely valid and universal. (shrink)

Korea Atomic Energy Research Institute (KAERI) has been carrying out a scaled-down moderator test program to simulate the CANDU-6 moderator circulation phenomena during steady state operation and accident conditions. The Moderator Circulation Test (MCT) facility was designed and constructed as 1/4 scale of the prototype of CANDU-6 reactor. In the present work spatial distribution of two-dimensional velocity in the MCT facility under isothermal condition was measured using planar Particle Image Velocimetry (PIV) system which consists of double pulsed laser, synchronizer, and (...) high speed camera. TSI’s Insight TM 4G software was used to perform PIV image capturing, PIV calculation and post processing. 10 μm sized silver-coated hollow sphere particles were used as flow tracer particles. Multiple experiments were conducted to cover large area of the MCT facility with limited field of view of a single camera. Instantaneous and averaged velocity field were analyzed for each spatial position and flow rate. This research is capable of offering validation data for self-reliant CFD tools to predict moderator subcooling margin in CANDU-6 reactor. (shrink)

We simulate trial data to test speculative claims about research methods, such as the impact of publication bias.

The rapid advancement of artificial intelligence (AI) has generated an increasing demand for tools that can assess public attitudes toward AI. This study proposes the development and the validation of the AI Attitude Scale (AIAS), a concise self-report instrument designed to evaluate public perceptions of AI technology. The first version of the AIAS that the present manuscript proposes comprises five items, including one reverse-scored item, which aims to gauge individuals’ beliefs about AI’s influence on their lives, careers, and humanity (...) overall. The scale is designed to capture attitudes toward AI, focusing on the perceived utility and potential impact of technology on society and humanity. The psychometric properties of the scale were investigated using diverse samples in two separate studies. An exploratory factor analysis was initially conducted on a preliminary 5-item version of the scale. Such exploratory validation study revealed the need to divide the scale into two factors. While the results demonstrated satisfactory internal consistency for the overall scale and its correlation with related psychometric measures, separate analyses for each factor showed robust internal consistency for Factor 1 but insufficient internal consistency for Factor 2. As a result, a second version of the scale is developed and validated, omitting the item that displayed weak correlation with the remaining items in the questionnaire. The refined final 1-factor, 4-item AIAS demonstrated superior overall internal consistency compared to the initial 5-item scale and the proposed factors. Further confirmatory factor analyses, performed on a different sample of participants, confirmed that the 1-factor model (4-items) of the AIAS exhibited an adequate fit to the data, providing additional evidence for the scale’s structural validity and generalizability across diverse populations. In conclusion, the analyses reported in this article suggest that the developed and validated 4-items AIAS can be a valuable instrument for researchers and professionals working on AI development who seek to understand and study users’ general attitudes toward AI. (shrink)

This study developed an instrument that measures the attitude of Filipino high school students towards mathematics, with reliable predictors and factors. Using the responses of 300 high school students from Zamboanga Sibugay, the validity and reliability of the Mathematics Attitude Scale (MAS) was tested using Exploratory Factor Analysis (EFA) and reliability analyses. The EFA showed that four-factor structures of the instrument, regarding the mathematics attitude for high school students, explained 27.48% of the variance in the pattern of relationships among the (...) items. The Average Variance Extracted (AVE), Composite Reliability, and Cronbach’s Alpha coefficients were reported. They proved that the extracted constructs have obtained and satisfied convergent validity. Thirty-three items remained in the final questionnaire after deleting the twenty-seven items with factor loadings of less than 0.4 (Students’ Perceived Motivation and Support in Learning Mathematics: twelve items; Students’ Perceived Anxiety in Learning Mathematics: ten items; Students’ Perceived Self-Efficacy in Learning Mathematics: six items; and Teachers and Parents’ Influences to Students in Learning Mathematics: five items). This study has confirmed the four-factor structure of the MAS. Educators and researchers can use the MAS to better understand the attitudes of Filipino high school students towards mathematics. (shrink)

Social robotics designed to enhance anthropomorphism and zoomorphism seeks to evoke feelings of empathy and other positive emotions in humans. While it is difficult to treat these machines as mere artefacts, the simulated lifelike qualities of robots easily lead to misunderstandings that the machines could be intentional. In this post-anthropocentrically positioned article, we look for a solution to the dilemma by developing a novel concept, “abiozoomorphism.” Drawing on Donna Haraway’s conceptualization of companion species, we address critical aspects of why robots (...) should not be categorized with animals by showing that the distinction between nonliving beings and living beings is still valid. In our phenomenologically informed approach to social robotics, we propose that the concept of abiozoomorphism makes it possible to transcend the strong ethos of biotism that prevails in both robot design and academic research on social robots. (shrink)

Objective: Otitis media is one of the most common ear disorders occurring in childhood, which causes alterations in communication between parents and children, thereby having a significant effect on the health-related quality of life. Otitis Media-6 questionnaire (OM-6) is a Likert-type scale used to assess the health-related quality of life in children with otitis media. In this study, our aim was to create a consistent, reliable, and valid Turkish version of the OM-6. Methods: Children with otitis media presenting with effusion (...) and healthy children were enrolled in this study between February 2019 and September 2019. The OM-6 test was administered to three different groups, including preoperative, postoperative, and control, among the children who had undergone ventilation tube insertion operation and among the healthy children. Results: The overall scores of children with otitis media presenting with effusion exhibited a changing pattern, indicating a statistical significance in the evaluation of the health-related quality of life. The Turkish version of OM-6 includes the scores of construct validity (Spearman values between 0, 58-0, 89), internal consistency (Cronbach’s alpha values between 0, 88-0, 96), and reliability (Pearson correlation value between 0, 67-0, 91). These scores exhibited a statistical significance. Conclusion: The Turkish version of OM-6 is a stable, valid questionnaire with internal consistency. (shrink)

Defined as vicarious sensorimotor experiencing, mental imagery is a powerful source of aesthetic enjoyment in everyday life and, reportedly, one of the commonest things readers remember about literary narratives in the long term. Furthermore, it is positively correlated with other dimensions of reader response, most notably with emotion. Until recent decades, however, the phenomenon of mental imagery has been largely overlooked by modern literary scholarship. As an attempt to strengthen the status of mental imagery within the literary and, more generally, (...) aesthetic discipline, this dissertation proposes an analysis positioned at a confluence of literary theory and the cognitive sciences, especially the emergent research framework of embodied cognition. Questions asked throughout the dissertation include the following: a) What are the basic varieties of mental imagery in the reading of literary narrative? b) By what contents or narrative strategies are they most likely to be prompted? c) What is it like to experience a mental image of a particular variety? d) What are its psychophysiological underpinnings? e) How does a mental image of a particular variety relate to perception? f) How does it relate to higher-order meaning-making? Four prototypical imagery varieties are distinguished on the basis of two variables with two values each (referential vs. verbal domain; inner vs. outer stance). Gradual transitions and in-between imagery varieties are acknowledged. The imagery typology and related hypotheses are grounded in introspection but carefully supported with indirect empirical evidence and, whenever possible, formulated so as to facilitate direct validation. (shrink)