Scientific models are used to predict and understand the target phenomena in the reality. The kind of epistemic relationship between the model and the reality is always regarded by most of the philosophers as a representational one. I argue that, complementary to this representational role, some of the scientific models have a constructive role to play in altering and reconstructing the reality in a physical way. I hold that the idealized model assumptions and elements bestow the constructive force of a (...) model on the reality. By recognizing the physical constructive force of some scientific models, the merit of these models could be judged by how successful they are in the reality construction, rather than by the traditional criterion of model-world representation. (shrink)

ion is one of the important processes in scientific modeling. It has always been implied that abstraction is an agent-centric activity that involves the cognitive processes of scientists in model building. I contend that there is an autonomous aspect of abstraction in many modeling activities. I argue that the autonomous process of abstraction is continuous with the agent-centric abstraction but capable of evolving independently from the modeler’s abstraction activity.

Pictorial representations such as diagrams and figures are widely used in scientific literature for explanatory and descriptive purposes. The intuitive nature of pictorial representations coupled with texts foster a better understanding of the objects of study. Biological mechanisms and processes can be clearly illustrated and grasped in pictures. I argue that pictorial representations describe biological phenomena by telling stories. I elaborate on the role of narrative structures of pictures in the frontier research using a case study in immunology. I articulate (...) that pictures with an inherent narrative structure are crucial in biological sciences. (shrink)

Mechanisms consist of component parts and processes organized in a specific way to produce changes that may give rise to one or more phenomena. I aim to examine the generative mechanism of generative material models in the production of new material models. A generative material model in biology is a living material model that is capable of generating new material models. I contend that generative mechanisms of a generative material model are not to be conflated with biological mechanisms: the former (...) is a mechanism manipulated and altered by the modeler while the latter is a naturally occurring mechanism. I examine the ways in which idealization may contribute to the generative mechanism in generating new model organisms. I articulate that the component parts and activities in a generative mechanism are to a large extent shaped by idealization in generative material modeling. Although biological mechanisms do have a role to play in the generation of model organisms, I propose that we shall view the generative mechanism as a hybrid of biological mechanisms and modeling activities. I shall argue that the notion of generative mechanisms as hybrid mechanisms is different from the extant conceptions of mechanisms in various aspects. (shrink)

In a broad brush, biological models are often constructed in two general types: as a concrete model; as an abstract model. A concrete model is a material model such as model organisms, while an abstract model is a mathematical or computational model consists of equations or algorithms. Though there are types of biological models that cannot be strictly categorized as either concrete or abstract, they are falling somewhere in between this spectrum. In view of the fact that biological phenomena are (...) sui generis and distinct from physical phenomena in many respects, using the concepts in standard modeling fails to account for the differences between biological sciences and physical sciences. Drawing from the resources of a credible-world account of models in economic modeling, I propose to reinterpret abstract models and concrete models in the light of the credible world account of models. (shrink)

Conceptual constructive models are a type of scientific model that can be used to construct or reshape the target phenomenon conceptually. Though it has received scant attention from the philosophers, it raises an intriguing issue of how a conceptual constructive model can construct the target phenomenon in a conceptual way. Proponents of the conception of conceptual constructive models are not being explicit about the application of the constructive force of a model in the target construction. It is far from clear (...) that how a conceptual constructive model exerts its constructive force on the constructed phenomenon of interest. Consequently, the function and the epistemic status of a conceptual constructive model are dubious at best. Making use of the conception of abstraction-as-aggregation, I argue that a conceptual constructive model can be used to construct the phenomenon of interest conceptually via a two-step process of abstraction: (1) abstracting away the lower-level details; and (2) aggregating the relevant information into a higher-level composite element. I contend that this process of abstraction, which is not playing the representational role as in a typical representational model, confers the constructive force on a model. (shrink)

Computational modeling is one of the primary approaches to constructing protein–protein interfaces in the laboratory. The algorithm-driven computational protein design has been successfully applied to the construction of functional proteins with improved binding affinity and increased thermostability. It is intriguing how a computational protein modeling approach can construct and shape the reality of new functional proteins from scratch. I articulate an account of abstraction and exploration-driven strategies in this computational endeavor. I aim to show that how a computational modelling approach, (...) which is laden with mathematics and algorithms, can have a constructive force on the target protein. (shrink)

Scientific models consist of fictitious elements and assumptions. Various attempts have been made to answer the question of how a model, which is sometimes viewed as a fiction, can explain or predict the target phenomenon adequately. I examine two accounts of models-as-fictions which are aiming at disentangling the myth of representing the reality by fictional models. I argue that both views have their own weaknesses in spite of many virtues. I propose to re-evaluate the problems of representation from a novel (...) perspective in which some of the model representations can be regarded as fictional representations. I argue that this type of model representation is credible despite being a fictional representation of the reality. (shrink)

Generative models have been proposed as a new type of non-representational scientific models recently. A generative model is characterized with the capacity of producing new models on the basis of the existing one. The current accounts do not explain sufficiently the mechanism of the generative capacity of a generative model. I attempt to accomplish this task in this paper. I outline two antecedent accounts of generative models. I point out that both types of generative models function to generate new homogenous (...) models in the sense that the latter is a straightforward derivative of the former, both of which share many similar features. Unfortunately, both accounts are implicit about the generative capacity of generative models. Using a case study, I articulate that a two-staged process of abstraction and idealization in modeling may contribute to the generative capacity of a scientific model. I also demonstrate that this two-staged process may go beyond the capacity of generating new homogenous models to generating new heterogeneous models. (shrink)

Model organisms are a living form of scientific models. Despite the widespread use of model organisms in scientific research, the actual representational relationship between model organisms and their target species is often poorly characterized in the context of cross-species research. Many model organisms do not represent the target species adequately, let alone accurately. This is partly due to the complex and emergent life phenomena in the organism, and partly due to the fact that a model organism is always taken to (...) represent a broad range of diverse organisms. More often than not, model organisms are taken as a reference point for an extrapolation to be made to the unknown characteristics of other species. I propose to view model organisms as analogue simulators which represent the emergent phenomenon in the context of cross-species research. A model organism represents a wide range of species by simulating their molecular microstates which underlie various emergent phenomena. I show that although model organisms represent the target species inadequately at many levels of complexity, they have epistemic values as a simulator in virtue of which the emergent phenomenon can be modeled dynamically, a virtue that is hardly attainable by non-dynamic models. (shrink)

[full article, abstract in English; only abstract in Lithuanian] Walton’s thesis of transparency of photographs has spurred much dispute among critics. One of the popular objections is spatial agnosticism, an argument that concerns the inertia of egocentric spatial information vis-a-vis a photograph. In this paper, I argue that spatial agnosticism fails. Spatial agnostics claim, for a wrong reason, that a photographic image cannot carry egocentric spatial information. I argue that it is the disjuncture of the photographic world in which the (...) depicted object situated from the space in which the viewer of the photograph resides that renders the photograph spatially agnostic. It is the timeless photographic world rather than the photographic object that renders egocentric spatial information inert. With this new formulation of spatial agnosticism, I propose that spatial agnosticism needs to be coupled with the temporal dimension in the efforts to refute the thesis of transparency of photographs. (shrink)

It is assumed that scientific models contain no superfluous model elements in scientific representation. A representational model is constructed with all the model elements serving the representational purpose. The received view has it that there are no redundant model elements which are non-representational. Contrary to this received view, I argue that there exist some non-representational model elements which are essential in scientific representation. I call them representation-supporting model elements in virtue of the fact that they play the role to support (...) the representational role of representational model elements. Representation-supporting model elements, which have a characteristic of dependability, are not to be eliminated in the process of modeling although they are playing second fiddle to representational model elements in scientific representation. (shrink)

Grasha–Riechmann Teaching Styles have a high potential to be applied in Mathematics especially to help increase teacher educators’ knowledge. However, very little attention has been paid to the study of identifying the teaching style patterns of Mathematics teachers at the primary school National-Type Chinese Primary Schools or Sekolah Jenis Kebangsaan Cina SJKC. There is increasing concern about how this teaching style related to the teaching experience. This study aims to identify the patterns of Grasha–Riechmann Teaching Styles among primary school Mathematics (...) teachers and the relationship between Grasha–Riechmann Teaching Styles with teaching experience. The quantitative approach through a survey was applied to 97 Mathematics teachers of SJKC Kepong, Kuala Lumpur using the simple random sampling method. The instrument was adapted from the Grasha–Riechmann Teaching Styles Questionnaire, which measures five teaching styles such as Personal Model Teaching Style, Expert Teaching Style, Formal Authority Teaching Style, Delegator Teaching Style, and Facilitator Teaching Style. The patterns showed that the Personal Model Teaching Style is the most dominant, and the Facilitator Teaching as the least dominant style. The Spearman’s Rho Correlation also reported a very weak significant correlation between Grasha–Riechmann Teaching Styles with the teachers’ Mathematics teaching experience, specifically for Expert, Formal Authority, and Facilitator Teaching Styles. The study provides practical implications for educators’ professional development to diversify the training of teachers by experience and adapt them to the needs of student learning in primary school. These findings trigger ideas to get a better understanding by other demographic variables such as gender, age, and complexity of Mathematics subject. (shrink)

A discussion of the intersections between Aristotle's works: Ethics and Metaphysics. It debates the ways in which - and even the extent to which - the two texts illuminate one another, examine Aristotle's methods and intellectualism and analyse issues of matter, form, potency and art.

Historical study of the humanism in Indian thought.

Comparative study of discipline in Theravada and Sarvastivada Buddhism.

Contributed research papers on theoretical and practical aspect of Dharma in Vedic and classical Sanskrit literature.

Study of Jaina logic and philosophy with reference to Tattvabodhavidhāyinī of Abhayadeva, 10th century, commentary on Sammatitarkaprakaraṇa of Siddhasena Divakara.

Conversation with Navjyoti Singh, philosopher, chiefly about his views of modern Indic philosophy.

Influence of the fundamentals of Sankhya and Yoga on Indic philosophy; a study.

Research on religion can advance understanding of social cognition by building connections to sociology, a field in which much cognitively oriented work has been done. Among the schools of sociological thought that address religious cognition are: structural functionalism, symbolic interactionism, conflict theory, phenomenology, and, most recently, exchange theory. The gulf between sociology and cognitive science is an unfortunate historical accident.

We propose a theoretical framework that highlights the most important consequences of complexity for the form and evolution of projects and use it to develop a typology of project complexity. This framework also enables us to deepen the understanding of how knowledge production and flexibility strategies enable project participants to address complexity. Based on this understanding, we advance a number of propositions regarding the strategies that can be most effective for different categories of complexity. These results contribute to the integration (...) of various strands in the research on project complexity and provide a roadmap for further research on the strategies for addressing it. (shrink)

One.The Glass is Always Half-full? Countering the Optimists -- Two. The `Doomsday Clock' is Always with Us: Pessimism in History -- Three. Optimists v. Pessimists: Economics and Politics -- Four. I Think, Therefore I Expect the Worst: Pessimism in Philosophy -- Five. A World Without Meaning: Pessimism in Literary Fiction -- Six. Visions of Despair: Pessimism in the Arts -- Seven. The Benefits of a Half-empty Glass: Pessimism as a Lifestyle.