Mental model construction is supposed to be a useful cognitive devise for learning. Beyond human capacity of constructing mental models, scientists construct complex explanations about phenomena, named scientific or theoretical models. In this work we revisit three vissions: the first one concern about the polisemic term “model”. Our proposal is to discriminate between “mental models” and “explicit models”, being the former those “imaginistic” ideas constructed in scientists’—o teachers—minds, and the latter those teaching devices expressed in different languages that (...) tend to communicate any “scientific model”. From this point of view, the class is considered a place where teachers’ mental models should be learned by novice students by decoding their teaching devices which are expressed in different languages. Other proposal of this work claims to distinguish the term “representation” with respect to its artistical or instrumental origin, highlighting that they are types of teaching devices and that artistical representations are always analogies. Finally, data about the construction of freshmen’s wrong mental models related to the use of the analogy between the chemical combustion and the global process of cellular respiration from glucose is presented to reinforce previous epistemological reflections. (shrink)

In climate science, climate models are one of the main tools for understanding phenomena. Here, we develop a framework to assess the fitness of a climate model for providing understanding. The framework is based on three dimensions: representational accuracy, representational depth, and graspability. We show that this framework does justice to the intuition that classical process-based climate models give understanding of phenomena. While simple climate models are characterized by a larger graspability, state-of-the-art models have a higher representational accuracy (...) and representational depth. We then compare the fitness-for-providing understanding of process-based to data-driven models that are built with machine learning. We show that at first glance, data-driven models seem either unnecessary or inadequate for understanding. However, a case study from atmospheric research demonstrates that this is a false dilemma. Data-driven models can be useful tools for understanding , specifically for phenomena for which scientists can argue from the coherence of the models with background knowledge to their representational accuracy and for which the model complexity can be reduced such that they are graspable to a satisfactory extent. When citing this paper, please use the full journal title Studies in History and Philosophy of Science. (shrink)

We call for a new philosophical conception of models in physics. Some standard conceptions take models to be useful approximations to theorems, that are the chief means to test theories. Hence the heuristics of model building is dictated by the requirements and practice of theory-testing. In this paper we argue that a theory-driven view of models can not account for common procedures used by scientists to model phenomena. We illustrate this thesis with a case study: the construction (...) of one of the first comprehensive model of superconductivity by London brothers in 1934. Instead of theory-driven view of models, we suggest a phenomenologically-driven one. (shrink)

Cho and Martinez-Martin provide a wide-ranging analysis of what they label “digital simulacra”—which are in essence data-driven AI-based simulation models such as digital twins or models used for i...

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)

This thesis focuses on models of conceptual change in science and philosophy. In particular, I developed a new bootstrapping methodology for studying conceptual change, centered around the formalization of several popular models of conceptual change and the collective assessment of their improved formal versions via nine evaluative dimensions. Among the models of conceptual change treated in the thesis are Carnap’s explication, Lakatos’ concept-stretching, Toulmin’s conceptual populations, Waismann’s open texture, Mark Wilson’s patches and facades, Sneed’s structuralism, and Paul Thagard’s conceptual (...) revolutions. -/- In order to analyze and compare the conception of conceptual change provided by these different models, I rely on several historical reconstructions of episodes of scientific conceptual change. The historical episodes of scientific change that figure in this work include the emergence of the morphological concept of fish in biological taxonomies, the development of scientific conceptions of temperature, the Church-Turing thesis and related axiomatizations of effective calculability, the history of the concept of polyhedron in 17th and 18th century mathematics, Hamilton’s invention of the quaternions, the history of the pre-abstract group concepts in 18th and 19th century mathematics, the expansion of Newtonian mechanics to viscous fluids forces phenomena, and the chemical revolution. I will also present five different formal and informal improvements of four specific models of conceptual change. I will first present two different improvements of Carnapian explication, a formal and an informal one. My informal improvement of Carnapian explication will consist of a more fine-grained version of the procedure that adds an intermediate, third step to the two steps of Carnapian explication. I will show how this novel three-step version of explication is more suitable than its traditional two-step relative to handle complex cases of explications. My second, formal improvement of Carnapian explication will be a full explication of the concept of explication itself within the theory of conceptual spaces. By virtue of this formal improvement, the whole procedure of explication together with its application procedures and its pragmatic desiderata will be reconceptualized as a precise procedure involving topological and geometrical constraints inside the theory of conceptual spaces. My third improved model of conceptual change will consist of a formal explication of Darwinian models of conceptual change that will make vast use of Godfrey-Smith’s population-based Darwinism for targeting explicitly mathematical conceptual change. My fourth improvement will be dedicated instead to Wilson’s indeterminate model of conceptual change. I will show how Wilson’s very informal framework can be explicated within a modified version of the structuralist model-theoretic reconstructions of scientific theories. Finally, the fifth improved model of conceptual change will be a belief-revision-like logical framework that reconstructs Thagard’s model of conceptual revolution as specific revision and contraction operations that work on conceptual structures. -/- At the end of this work, a general conception of conceptual change in science and philosophy emerges, thanks to the combined action of the three layers of my methodology. This conception takes conceptual change to be a multi-faceted phenomenon centered around the dynamics of groups of concepts. According to this conception, concepts are best reconstructed as plastic and inter-subjective entities equipped with a non-trivial internal structure and subject to a certain degree of localized holism. Furthermore, conceptual dynamics can be judged from a weakly normative perspective, bound to be dependent on shared values and goals. Conceptual change is then best understood, according to this conception, as a ubiquitous phenomenon underlying all of our intellectual activities, from science to ordinary linguistic practices. As such, conceptual change does not pose any particular problem to value-laden notions of scientific progress, objectivity, and realism. At the same time, this conception prompts all our concept-driven intellectual activities, including philosophical and metaphilosophical reflections, to take into serious consideration the phenomenon of conceptual change. An important consequence of this conception, and of the analysis that generated it, is in fact that an adequate understanding of the dynamics of philosophical concepts is a prerequisite for analytic philosophy to develop a realistic and non-idealized depiction of itself and its activities. (shrink)

Unlike most other sciences, psychology has no true core theory to guide a coherent research programme. It does have James J Gibson’s ecological approach to visual perception, however, which we suggest should serve as an example of the benefits a good theory brings to psychological research. Here we focus on an example of how the ecological approach has served as a guide to discovery, shaping and constraining a recent hypothesis about how humans perform coordinated rhythmic movements (Bingham 2004a, b). Early (...) experiments on this task were framed in a dynamic pattern approach. This phenomenological, behavioural framework (e.g. Jeka & Kelso 1989) classifies the behaviour of complex action systems in terms of the key order parameters, and describes the dynamical stability of the system as it responds to perturbations. Dynamical systems, however, while a valuable toolkit, is not a theory of behaviour, and this style of research is unable to successfully predict data it is not explicitly designed to fit. More recent work by Bingham & colleagues has used dynamical systems to formalise hypotheses derived from Gibson’s ecological approach to perception and action, with a particular emphasis on perceptual information. The resulting model (Bingham 2001, 2004a, b; Snapp-Childs et al. 2011) has had great success with both the phenomena it was designed to explain as well as a wide range of empirical results from a version of the task it is not specifically designed to explain (specifically, learning a novel coordination). This model and the research programme that produced it stand as an example of the value of theory driven research, and we use it to illustrate the contemporary importance the ecological approach has for psychology. (shrink)

Computer models and simulations have become, since the 1960s, an essential instrument for scientific inquiry and political decision making in several fields, from climate to life and social sciences. Philosophical reflection has mainly focused on the ontological status of the computational modeling, on its epistemological validity and on the research practices it entails. But in computational sciences, the work on models and simulations are only two steps of a longer and richer process where operations on data are as important as, (...) and even more time and energy-consuming than modeling itself. Drawing on two study cases—computational embryology and computational epidemiology—this article contributes to filling the gap by focusing on the operations of producing and re-using data in computational sciences. The different phases of the scientific and artisanal work of modelers include data collection, aggregation, homogenization, assemblage, analysis and visualization. The article deconstructs the ideas that data are self-evident informational aggregates and that data-driven approaches are exempted from theoretical work. More importantly, the paper stresses the fact that data are constructed and theory laden not only in their fabrication, but also in their reusing. (shrink)

In the 1960s, theoretical biologist Richard Levins criticised modellers in his own discipline of population biology for pursuing the “brute force” strategy of building hyper-realistic models. Instead of exclusively chasing complexity, Levins advocated for the use of multiple different kinds of complementary models, including much simpler ones. In this paper, I argue that the epistemic challenges Levins attributed to the brute force strategy still apply to state-of-the-art climate models today: they have big appetites for unattainable data, they are limited by (...) computational tractability, and they are incomprehensible to the human modeller. Along the lines Levins described, this uncertainty generates a trade-off between realistic, precise models with predictive power and simple, highly idealised models that facilitate understanding. In addition to building ensembles of highly complex dynamical models, climate modellers can address model uncertainty by comparing models of different types, such as dynamical and data-driven models, and by systematically comparing models at different levels of what climate modellers call the model hierarchy. Despite its age, Levins’ paper remains incredibly insightful and should be considered an important entry into the philosophy of computational modelling. (shrink)

The data-driven approach to psychiatric science leverages large volumes of patient data to construct machine learning models with the goal of optimizing clinical decision making. Advocates claim that this methodology is well-placed to deliver transformative improvements to psychiatric science. I argue that talk of a data-driven revolution in psychiatry is premature. Transformative improvements, cashed out in terms of better patient outcomes, cannot be achieved without addressing patient understanding. That is, how patients understand their own mental illnesses. (...) I conceptualize understanding as the possession of adaptive mental constructs through which experience is mediated. I suggest that this notion of understanding serves as a bottleneck which any prospective approach to psychiatry must address to be efficacious. Subsequently I argue that, though the data-driven approach is undoubtedly powerful, it does not have a straightforward means of unblocking the bottleneck of understanding. I suggest that the data-driven approach must be supplemented with significant theoretical progress if it is to transform psychiatry. (shrink)

Our aim is to point out the role of scientific research in contemporary technological developments. Interactions between science and technology in the context of application-driven research projects of the 20th century are discussed. We define science and technology as two separate domains, and provide elementary models for their interaction by the means of applied and engineering sciences. These elementary models constitute linear and cascade models of science-technology interaction. We apply these elementary models for the purpose of (...) further methodological analysis of Soviet nuclear warfare project. The special role of organization and management in research and development activities is being emphasized. The new science-technology interaction model is devised in the course of nuclear project. This new interaction model is referred as non-linear or spiral. The model is seen as more collaborative and risk aware than linear and cascade interaction models present in twentieth century. The conclusion is the new model was of great impact to modern social forms in which research is carried out in the present. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Driven from Home: Protecting the Rights of Forced Migrants Edited by David Hollenbach, SJ, and: Kinship across Borders: A Christian Ethic of Immigration by Kristen HeyerRené M. Micallef SJDriven from Home: Protecting the Rights of Forced Migrants EDITED BY DAVID HOLLENBACH, SJ Washington DC: Georgetown University Press, 2010. 296 pp. $20.46Kinship across Borders: A Christian Ethic of Immigration KRISTEN HEYER Washington DC: Georgetown University Press, 2012. 210 (...) pp. $29.23Although based on a conference held at Boston College in November 2008, Driven from Home is no less timely today, given the context of current debates on immigration in the United States, the European Union, Australia, and the Middle East. David Hollenbach’s introduction explains how the book brings together Christian (mostly Catholic) theologians, human rights activists, humanitarian practitioners, and legal scholars to help us focus on a class of persons referred to as “forced migrants” or “persons needing protection.” These individuals are neither classical “convention refugees” (according to international law definitions) nor are they simply “migrant workers” (in the classical sense) since their basic human rights to security and subsistence cannot [End Page 230] be adequately guaranteed in their home country or region. They do not emigrate merely in search of a higher standard of living; rather, forced migrants enter and settle in foreign lands seeking some sort of “protection” similar to that afforded to “conventional” refugees. More concretely, the book focuses on persons on the move—individuals fleeing violence and the extreme poverty rampant in regions devastated by ecological degradation and natural disasters.Extending the logic of the 1952 Refugee Convention and adapting it to the realities of today, one can argue convincingly that the international community has a duty to protect such persons when their states of origin are structurally unable or unwilling to afford protection (as argued in Susan Martin’s essay). However, paternalistic approaches that diminish rather than augment the agency of local governments and migrants are to be avoided (as maintained in M. Brinton Lykes’ essay). The book helps us reflect on what can be done to guarantee the basic rights of forced migrants not only at the level of international law and institutions but also through domestic and regional policymaking spurred and inspired by both Christian and secular global-humanitarian values. Such values are eminently compatible when applied to this particular issue (see Silvano Tomasi’s contribution). Agbonkhianmeghe Orobator’s essay—which offers insightful reflections (albeit rather general ones) from Christian ethics, ecclesiology, and biblical theology—likewise points to the need for a truly interdisciplinary approach to the issue. The other authors help the book achieve precisely this. Theological ethics finds its own distinctive place and voice in dialogue with a range of perspectives: legal and political sciences and case studies (Frank Brennan, Daniel Kanstroom); philosophical approaches (Arash Abizadeh); and sociological research on particular migrant populations (M. Brinton Lykes, Maryanne Loughry). The book includes essays that integrate case studies, technical reflections, useful summaries of theological principles and doctrines (J. Bryan Hehir, Mary M. DeLorey, and Tomasi), and philosophical stances (Abizadeh, Thomas G. Weiss), and present practical and legal proposals (see Martin’s essay). A stimulating read for scholars and for the general public, the volume provides good training material for faith-based activists and practitioners.The argumentation strategy in many of the essays in Driven from Home is to appeal to the reader’s sense of solidarity with the needy or suffering neighbor. It promotes the virtues of hospitable citizenship and hospitable disciple-ship while carefully trying to convince national and international policymakers to reinforce and expand the international protection regime. Emboldened by the 2005 “Responsibility to Protect” breakthrough at the United Nations, the authors seek to remain acceptable to a wide audience in an atmosphere of resurgent nationalism, nativism, and protectionism. The authors generally avoid harsh critiques of Westphalian models of sovereignty and do not dwell [End Page 231] on the Catholic doctrines of the universal destination of created goods and the (circumscribed) right to immigrate (and not only to emigrate). Rather, they seek to introduce a new protection niche without fundamentally challenging the prevailing ideology of sovereignty, gently proposing new legal instruments as though they... (shrink)

Although work on computational and robotic modelling of cognition is highly diverse, as an empirical method it can be roughly divided into at least two clearly different, though non-exclusive branches, motivated to evaluate the sufficiency or the necessity of theories when it comes to accounting for data and/or other observations. With the rising profile of theories of situated/embodied cognition, a third non-exclusive avenue for investigation has also gained in popularity, the investigation of agent-environment embedding or more generally, exploration. Still in (...) its infancy, and often confused with sufficiency testing, this relatively new kind of modelling, which is theory- rather than data-driven, investigates the role of the environment in shaping the ontogenetic and/or phylogenetic development of situated agency. Each of these three approaches presents many issues that modellers must be sensitive to, both in the design of experiments, and in the conclusions that can be drawn from them. This paper highlights some of these issues, provides examples, and addresses the contribution of computational/robotic modelling to cognitive science, as well as some of its limitations. (shrink)

Psychological science is maturing and therefore transitioning from explorative to theory-driven research. While explorative research seeks to find something “new,” theory-driven research seeks to elaborate on already known and hence predictable effects. A consequence of these differences is that the quality of explorative and theory-driven research needs to be judged by distinct criterions that optimally support their respective development. Especially, theory-driven research needs to be judged by its methodological rigor. A focus on innovativeness, which is (...) typical for explorative research, will instead incentivize bad research practices (e.g., imprecise theorizing, ignoring previous research, parallel theories). To support the advancement of psychology, we must drop the innovation requirement for theory-driven research and instead require the strongest methods, which are marked by high internal and external validity. Precise theorizing needs to substitute novelty. Theories are advanced by requiring explicit, testable assumptions, and an explicit preference for one theory over another. These explicit and potentially wrong assumptions should not be silenced within the peer-review process, but instead be scrutinized in new publications. Importantly, these changes in scientific conduct need to be supported by senior researchers, especially, in their roles as editors, reviewers, and in the hiring process. An important obstacle to further theory-driven research is to measure scientific merit using researchers’ number of publications, which favors theoretically shallow and imprecise writing. Additionally, it makes publications the central target of scientific misconduct even though they are the main source of information for the scientific community and the public. To advance the field, researchers should be judged by their contribution to the scientific community (e.g., exchange with and support of colleagues, and mentoring). Another step to advance psychology is to clearly differentiate between measurement model and theory, and not to overgeneralize based on few stimuli, incidences, or studies. We will use ideas from the theory of science to underline the changes necessary within the field of psychology to overcome this existential replication crisis. (shrink)

After a wave of breakthroughs in image‐based medical diagnostics and risk prediction models, machine learning (ML) has turned into a normal science. However, prominent researchers are claiming that another paradigm shift in medical ML is imminent—due to most recent staggering successes of large language models—from single‐purpose applications toward generalist models, driven by natural language. This article investigates the implications of this paradigm shift for the ethical debate. Focusing on issues like trust, transparency, threats of patient autonomy, responsibility issues (...) in the collaboration of clinicians and ML models, fairness, and privacy, it will be argued that the main problems will be continuous with the current debate. However, due to functioning of large language models, the complexity of all these problems increases. In addition, the article discusses some profound challenges for the clinical evaluation of large language models and threats to the reproducibility and replicability of studies about large language models in medicine due to corporate interests. (shrink)

BACON.3 is a production system that discovers empirical laws. Although it does not attempt to model the human discovery process in detail, it incorporates some general heuristics that can lead to discovery in a number of domains. The main heuristics detect constancies and trends in data, and lead to the formulation of hypotheses and the definition of theoretical terms. Rather than making a hard distinction between data and hypotheses, the program represents information at varying levels of description. The lowest (...) levels correspond to direct observations, while the highest correspond to hypotheses that explain everything so for observed. To take advantage of this representation, BACON.3 has the ability to carry out and relate multiple experiments, collapse hypotheses with identical conditions, ignore differences to let similar concepts be treated as equal, and to discover and ignore irrelevant variables. BACON.3 has shown its generality by rediscovering versions of the ideal gas law, Kepler's third law of planetary motion, Coulomb's law, Ohm's law, and Galileo's laws for the pendulum and constant acceleration. (shrink)

Scientific reasoning represents complex argumentation patterns that eventually lead to scientific discoveries. Social epistemology of science provides a perspective on the scientific community as a whole and on its collective knowledge acquisition. Different techniques have been employed with the goal of maximization of scientific knowledge on the group level. These techniques include formal models and computer simulations of scientific reasoning and interaction. Still, these models have tested mainly abstract hypothetical scenarios. The present thesis instead presents data-driven approaches in (...) social epistemology of science. A data-driven approach requires data collection and curation for its further usage, which can include creating empirically calibrated models and simulations of scientific inquiry, performing statistical analyses, or employing data- mining techniques and other procedures. -/- We present and analyze in detail three co-authored research projects on which the thesis’ author was engaged during her PhD. The first project sought to identify optimal team composition in high energy physics laboratories using data-mining techniques. The results of this project are published in (Perović et al. 2016), and indicate that projects with smaller numbers of teams and team members outperform bigger ones. In the second project, we attempted to determine whether there is an epistemic saturation point in experimentation in high energy physics. The initial results from this project are published in (Sikimić et al. 2018). In the thesis, we expand on this topic by using computer simulations to test for biases that could induce scientists to invest in projects beyond their epistemic saturation point. Finally, in previous examples of data-driven analyses, citations are used as a measure of epistemic efficiency of projects in high energy physics. In order to additionally justify and analyze the usage of this parameter in their data-driven research, in the third project Perović & Sikimić (2019) analyzed and compared inductive patterns in experimental physics and biology with the reliability of citation records in these fields. They conclude that while citations are a relatively reliable measure of efficiency in high energy physics research, the same does not hold for the majority of research in experimental biology. -/- Additionally, contributions of the author that are for the first time published in this theses are: (a) an empirically calibrated model of scientific interaction of research groups in biology, (b) a case study of irregular argumentation patterns in some pathogen discoveries, and (c) an introductory discussion of the benefits and limitations of data- driven approaches to the social epistemology of science. Using computer simulations of an empirically calibrated model, we demonstrate that having several levels of hierarchy and division into smaller research sub-teams is epistemically beneficial for researchers in experimental biology. We also show that argumentation analysis in biology represents a good starting point for further data-driven analyses in the field. Finally, we conclude that a data-driven approach is informative and useful for science policy, but requires careful considerations about data collection, curation, and interpretation. (shrink)

In spite of the wide variety of approaches to ethics training it is still debatable which approach has the highest potential to enhance professionals’ integrity. The current effort assesses a novel curriculum that focuses on metacognitive reasoning strategies researchers use when making sense of day-to-day professional practices that have ethical implications. The evaluated trainings effectiveness was assessed by examining five key sensemaking processes, such as framing, emotion regulation, forecasting, self-reflection, and information integration that experts and novices apply in ethical decision-making. (...) Mental models of trained and untrained graduate students, as well as faculty, working in the field of physical sciences were compared using a think-aloud protocol 6 months following the ethics training. Evaluation and comparison of the mental models of participants provided further validation evidence for sensemaking training. Specifically, it was found that trained students applied metacognitive reasoning strategies learned during training in their ethical decision-making that resulted in complex mental models focused on the objective assessment of the situation. Mental models of faculty and untrained students were externally-driven with a heavy focus on autobiographical processes. The study shows that sensemaking training has a potential to induce shifts in researchers’ mental models by making them more cognitively complex via the use of metacognitive reasoning strategies. Furthermore, field experts may benefit from sensemaking training to improve their ethical decision-making framework in highly complex, novel, and ambiguous situations. (shrink)

Cognitive architectures (i.e., theorized blueprints on the structure of the mind) can be used to make predictions about the effect of multiregion brain activity on the systems level. Recent work has connected one high-level cognitive architecture, known as the “Common Model of Cognition,” to task-based functional MRI data with great success. That approach, however, was limited in that it was intrinsically top-down, and could thus only be compared with alternate architectures that the experimenter could contrive. In this paper, we (...) propose a bottom-up method to infer a cognitive architecture directly from brain imaging data itself, overcoming this limitation. Specifically, Granger causality modeling was applied to the same task-based fMRI data to infer a network of causal connections between brain regions based on their functional connectivity. The resulting network shares many connections with those proposed by the Common Model of Cognition but also suggests important additions likely related to the role of episodic memory. This combined top-down and bottom-up modeling approach can be used to help formalize the computational instantiation of cognitive architectures and further refine a comprehensive theory of cognition. (shrink)

Linkage (or genetic) maps are graphs, which are intended to represent the linear ordering of genes on the chromosomes. They are constructed on the basis of statistical data concerning the transmission of genes. The invention of this technique in 1913 was driven by Morgan's group's adoption of a set of hypotheses concerning the physical mechanism of heredity. These hypotheses were themselves grounded in Morgan's defense of the chromosome theory of heredity, according to which chromosomes are the physical basis of (...) genes. In this paper, I analyze the 1919 debate between William Castle and Morgan's group, about the construction of genetic maps. The official issue of the debate concerns the arrangement of genes on chromosomes. However, the disputants tend to carry out the discussions about how one should model the data in order to draw predictions concerning the transmission of genes; the debate does not bear on the data themselves, nor does it focus on the hypotheses explaining these data. The main criteria that are appealed to by the protagonists are simplicity and predictive efficacy. However, I show that both parties' assessments of the simplicity and predictive efficacy of different ways of modeling the data themselves depend on background theoretical positions. I aim at clarifying how preference for a given model and theoretical commitments articulate. (shrink)

Tsuda offers advanced concepts to model brain functions, includ-ing “chaotic itinerancy,” “attractor ruins,” “singular-continuous nowhere-differentiable attractors,” “Cantor coding,” “multi-Milnor attractor systems,” and “dynamically generated noise.” References to physiological descriptions of attractor landscapes governing activity over cortical fields maintained by millions of action potentials may facilitate their application in future experimental designs and data analyses.

Recent frameworks, models, and reports highlight the critical need to address social determinants of health for achieving health equity in the United States and around the globe. In the United States, data play an important role in better understanding community‐level and population‐level disparities particularly for local health departments. However, data‐driven decision‐making—the use of data for public health activities such as program implementation, policy development, and resource allocation—is often presented theoretically or through case studies in the literature. We sought to (...) develop a preliminary model that identifies the factors that contribute to data‐driven decision‐making in US local health departments and describe relationships between them. Guided by implementation science literature, we examined organizational‐level capacity and individual‐level factors contributing to using data for decision‐making related to social determinants of health and the reduction of county‐level disparities. This model has the potential to improve implementation of public health interventions and programs aimed at upstream structural factors, by elucidating the factors critical to incorporating data in decision‐making. (shrink)

Weisberg (2006) and Godfrey-Smith (2006, 2009) distinguish between two forms of theorising: data-driven ‘abstract direct representation’ and modeling. The key difference is that when using a data-driven approach, theories are intended to represent specific phenomena, so directly represent them, while models may not be intended to represent anything, so represent targets indirectly, if at all. The aim here is to compare and analyse these practices, in order to outline an account of model-based theorising that involves direct representational (...) relationships. This is based on the way that computational templates Humphreys (2002, 2004) are now used in cognitive neuroscience, and draws on the dynamic and tentative process of any kind of theory construction, and the idea of partial, purpose-relative representation. (shrink)

In this article, I focus on the role of computer simulations as exploratory strategies. I begin by establishing the non-theory-driven nature of simulations. This refers to their ability to characterize phenomena without relying on a predefined conceptual framework that is provided by an implemented mathematical model. Drawing on Steinle’s notion of exploratory experimentation and Gelfert’s work on exploratory models, I present three exploratory strategies for computer simulations: (1) starting points and continuation of scientific inquiry, (2) varying the parameters, (...) and (3) scientific prototyping. (shrink)

Traxler, Pickering, and Clifton found that ambiguous sentences are read faster than their unambiguous counterparts. This so-called ambiguity advantage has presented a major challenge to classical theories of human sentence comprehension because its most prominent explanation, in the form of the unrestricted race model, assumes that parsing is non-deterministic. Recently, Swets, Desmet, Clifton, and Ferreira have challenged the URM. They argue that readers strategically underspecify the representation of ambiguous sentences to save time, unless disambiguation is required by task demands. (...) When disambiguation is required, however, readers assign sentences full structure—and Swets et al. provide experimental evidence to this end. On the basis of their findings, they argue against the URM and in favor of a model of task-dependent sentence comprehension. We show through simulations that the Swets et al. data do not constitute evidence for task-dependent parsing because they can be explained by the URM. However, we provide decisive evidence from a German self-paced reading study consistent with Swets et al.'s general claim about task-dependent parsing. Specifically, we show that under certain conditions, ambiguous sentences can be read more slowly than their unambiguous counterparts, suggesting that the parser may create several parses, when required. Finally, we present the first quantitative model of task-driven disambiguation that subsumes the URM, and we show that it can explain both Swets et al.'s results and our findings. (shrink)

In this paper, I discuss the discovery of the DNA structure by Francis Crick and James Watson, which has provoked a large historical literature but has yet not found entry into philosophical debates. I want to redress this imbalance. In contrast to the available historical literature, a strong emphasis will be placed upon analysing the roles played by theory, model, and evidence and the relationship between them. In particular, I am going to discuss not only Crick and Watson's well-known (...) model and Franklin's x-ray diffraction pictures (the evidence) but also the less well known theory of helical diffraction, which was absolutely crucial to Crick and Watson's discovery. The insights into this groundbreaking historical episode will have consequences for the ‘new’ received view of scientific models and their function and relationship to theory and world. The received view, dominated by works by Cartwright and Morgan and Morrison ([1999]), rather than trying to put forth a ‘theory of models’, is interested in questions to do with (i) the function of models in scientific practice and (ii) the construction of models. In regard to (i), the received view locates the model (as an idealized, simplified version of the real system under investigation) between theory and the world and sees the model as allowing the application of the former to the latter. As to (ii) Cartwright has argued for a phenomenologically driven view and Morgan and Morrison ([1999]) for the ‘autonomy’ of models in the construction process: models are determined neither by theory nor by the world. The present case study of the discovery of the DNA structure strongly challenges both (i) and (ii). In contrast to claim (i) of the received view, it was not Crick and Watson's model but rather the helical diffraction theory which served a mediating purpose between the model and the x-ray diffraction pictures. In particular, Cartwright's take on (ii) is refuted by a comparison of Franklin's bottom-up approach with Crick and Watson's top-down approach in constructing the model. The former led to difficulties, which only a strong confidence in the structure incorporated in the model could circumvent. How to Get to the Structure 1.1 X-ray diffraction and its synthesis 1.2 Model building and Pauling's panache 1.3 The structure of proteins 1.3.1 A failed inference to the best explanation 1.3.2 The misleading 5.1 Å spot in proteins and how to get rid of it 1.3.3 Derived predictions from Pauling's alpha-helix of protein molecules The CCV Theory of Helical X-Ray Diffraction 2.1 The role of the CCV theory in the discovery of the DNA structure Killing the Helix 3.1 Appreciating all evidence—in vain Conclusion Epilogue: Chargaff's Ratios CiteULike Connotea Del.icio.us What's this? (shrink)

Multiscale modeling techniques have attracted increasing attention by philosophers of science, but the resulting discussions have almost exclusively focused on issues surrounding explanation (e.g., reduction and emergence). In this paper, I argue that besides explanation, multiscale techniques can serve important exploratory functions when scientists model systems whose organization at different scales is ill-understood. My account distinguishes explanatory and descriptive multiscale modeling based on which epistemic goal scientists aim to achieve when using multiscale techniques. In explanatory multiscale modeling, scientists (...) use multiscale techniques to select information that is relevant to explain a particular type of behavior of the target system. In descriptive multiscale modeling scientists use multiscale techniques to explore lower-scale features which could be explanatorily relevant to many different types of behavior, and to determine which features of a target system an upper-scale data pattern could refer to. Using multiscale models from data-driven neuroscience as a case study, I argue that descriptive multiscale models have an exploratory function because they are a sources of potential explanations and serve as tools to reassess our conception of the target system. (shrink)

ABSTRACT Is there something specific about modelling that distinguishes it from many other theoretical endeavours? We consider Michael Weisberg’s thesis that modelling is a form of indirect representation through a close examination of the historical roots of the Lotka–Volterra model. While Weisberg discusses only Volterra’s work, we also study Lotka’s very different design of the Lotka–Volterra model. We will argue that while there are elements of indirect representation in both Volterra’s and Lotka’s modelling approaches, they are largely due (...) to two other features of contemporary model construction processes that Weisberg does not explicitly consider: the methods-drivenness and outcome-orientedness of modelling. 1Introduction 2Modelling as Indirect Representation 3The Design of the Lotka–Volterra Model by Volterra 3.1Volterra’s method of hypothesis 3.2The construction of the Lotka–Volterra model by Volterra 4The Design of the Lotka–Volterra Model by Lotka 4.1Physical biology according to Lotka 4.2Lotka’s systems approach and the Lotka–Volterra model 5Philosophical Discussion: Strategies and Tools of Modelling 5.1Volterra’s path from the method of isolation to the method of hypothesis 5.2The template-based approach of Lotka 5.3Modelling: methods-driven and outcome-oriented 6Conclusion. (shrink)

According to standard rational choice theory, as commonly used in political science and economics, an agent's fundamental preferences are exogenously fixed, and any preference change over decision options is due to Bayesian information learning. Although elegant and parsimonious, such a model fails to account for preference change driven by experiences or psychological changes distinct from information learning. We develop a model of non-informational preference change. Alternatives are modelled as points in some multidimensional space, only some of (...) whose dimensions play a role in shaping the agentís preferences. Any change in these "motivationally salient" dimensions can change the agent's preferences. How it does so is described by a new representation theorem. Our model not only captures a wide range of frequently observed phenomena, but also generalizes some standard representations of preferences in political science and economics. (shrink)

Abstraction and generalization are two processes of reasoning that have a special role in the construction of scientific theories and models. They have been important parts of the scientific method ever since the nineteenth century. A philosophical and historical analysis of scientific practices shows how abstraction and generalization found their way into the theory of the logic of science of the nineteenth-century philosopher Charles S. Peirce. Our case studies include the scientific practices of Francis Galton and John Herschel, who (...) introduced composite photographs and graphical methods, respectively, as technologies of generalization and thereby influenced Peirce’s logic of abstraction. Herschel’s account of generalization is further supported by William Whewell, who was very influential on Peirce. By connecting Herschel’s scientific technology of abstraction to Peirce’s logical technology of abstraction—namely, diagrams—we highlight the role of judgments in scientific observation by hypostatic abstractions. We also relate Herschel’s discovery-driven logic of science and Peirce’s open-ended diagrammatic logic to the use of models in science. Ultimately, Peirce’s theory of abstraction is a case of showing how logic applies to reality. (shrink)

E-science, or networked, collaborative and multidisciplinary scientific research on a shared e-infrastructure using computational tools, methods and applications, has also brought about new networked organizational forms in the transition of higher education towards the entrepreneurial academy. While the under-representation of women in ICTs is well-recorded, it is also known that the potential of new organizational forms such as networked structures to promote gender equality remains ambiguous, as they tend to perpetuate already existing inequalities due to their embeddedness in larger (...) and longer-term structural or institutional gender effects. Based on a year-long ethnographic study in a networked academic e-science collaboration in Sweden and 45 in-depth, semi-structured interviews with its affiliated researchers, this article analyzes the multi-level obstacles to achieving gender equality in e-science to highlight the ways in which gendered disparities persist in this new, project-based academic networked organization in Sweden, hereafter called eSec. At the _organizational level_ eSec remains deeply embedded in the traditional disciplinary and institutional academic setting, inadvertently reproducing existing gender imbalances across sciences. Furthermore, as a project-based organization, it is also embedded in the shift towards an entrepreneurial university model driven by new managerialism, the latter having a well-documented adverse effect in gender equality. This represents _a structural-level_ obstacle which leads to especially female junior faculty leaving academy for industry. An _individual level_ obstacle is observed alongside these as disavowal (_Verleugnung_) of gender disparities, an affect identified as a key mechanism of subjectivation in neoliberalism. (shrink)

This paper describes model building and manipulation in the solution of problems in mechanics. An automatic problem solver, MECHO, solving problems in several areas of mechanics, employs (1) a knowledge base representing the semantic content of the particular problem area, (2) a means-ends search strategy similar to GPS to produce sets of simultaneous equations and (3) a “focusing” technique, based on the data within the knowledge base, to guide the GSP-like search through possible equation instantiations. Sets of predicate logic (...) statements are employed to describe this model building activity. These clauses are used to give information content to the knowledge base and provide both basis and guidance for the goal driven search.It is hypothesized that humon subjects solving mechanics problems employ similar model building techniques. Protocols of several subjects are presented and comparisons are drawn with the traces of the automated problem solver. Adjustments are made to the program to provide a better fit of traces to protocols. Some implications are presented for using a rule based model for describing human problem solving performance in solving mechanics problems. (shrink)

Infants' own activities create and actively select their learning experiences. Here we review recent models of embodied information seeking and curiosity-driven learning and show that these mechanisms have deep implications for development and evolution. We discuss how these mechanisms yield self-organized epigenesis with emergent ordered behavioral and cognitive developmental stages. We describe a robotic experiment that explored the hypothesis that progress in learning, in and for itself, generates intrinsic rewards: The robot learners probabilistically selected experiences according to their potential (...) for reducing uncertainty. In these experiments, curiosity-driven learning led the robot learner to successively discover object affordances and vocal interaction with its peers. We explain how a learning curriculum adapted to the current constraints of the learning system automatically formed, constraining learning and shaping the developmental trajectory. The observed trajectories in the robot experiment share many properties with those in infant development, including a mixture of regularities and diversities in the developmental patterns. Finally, we argue that such emergent developmental structures can guide and constrain evolution, in particular with regard to the origins of language. (shrink)

We call for a new philosophical conception of models in physics. Some standard conceptions take models to be useful approximations to theorems, that are the chief means to test theories. Hence the heuristics of model building is dictated by the requirements and practice of theory-testing. In this paper we argue that a theory-driven view of models can not account for common procedures used by scientists to model phenomena. We illustrate this thesis with a case study: the construction (...) of one of the first comprehensive model of superconductivity by London brothers in 1934. Instead of theory-driven view of models, we suggest a phenomenologically-driven one. (shrink)

This paper investigates how social movements generate new and profit-driven organizational forms in the context of Socially Responsible Investment. Building on empirical evidence from previous research, we highlight the transformation of SRI from an activist-driven movement aimed at lobbying corporations for social causes to a profit-driven industry focused on generating revenue for investors. We first show this change as it occurs across time in the US. Then, we discuss the cross-cultural diffusion of this practice from US to (...) two continental European countries. We provide a collective action model framework to account for this process of institutional commodification. (shrink)

ArgumentIn the theory-dominated view of scientific experimentation, all relations of theory and experiment are taken on a par; namely, that experiments are performed solely to ascertain the conclusions of scientific theories. As a result, different aspects of experimentation and of the relations of theory to experiment remain undifferentiated. This in turn fosters a notion of theory-ladenness of experimentation (TLE) that is toocoarse-grainedto accurately describe the relations of theory and experiment in scientific practice. By contrast, in this article, I suggest that (...) TLE should be understood as anumbrella conceptthat has different senses. To this end, I introduce a three-fold distinction among the theories of high-energy particle physics (HEP) as background theories, model theories, and phenomenological models. Drawing on this categorization, I contrast two types of experimentation, namely, “theory-driven” and “exploratory” experiments, and I distinguish between the “weak” and “strong” senses of TLE in the context of scattering experiments from the history of HEP. This distinction enables identifying the exploratory character of the deep-inelastic electron-proton scattering experiments – performed at the Stanford Linear Accelerator Center (SLAC) between the years 1967 and 1973 – thereby shedding light on a crucial phase of the history of HEP, namely, the discovery of “scaling,” which was the decisive step towards the construction of quantum chromo-dynamics as a gauge theory of strong interactions. (shrink)

Emotion is closely associated with language, but we know very little about how children express emotion in their own writing. We used a large‐scale, cross‐sectional, and data‐driven approach to investigate emotional expression via writing in children of different ages, and whether it varies for boys and girls. We first used a lexicon‐based bag‐of‐words approach to identify emotional content in a large corpus of stories (N>100,000) written by 7‐ to 13‐year‐old children. Generalized Additive Models were then used to model (...) changes in sentiment across age and gender. Two other machine learning approaches (BERT and TextBlob) validated and extended these analyses, converging on the finding that positive sentiments in children's writing decrease with age. These findings echo reports from previous studies showing a decrease in mood and an increased use of negative emotion words with age. We also found that stories by girls contained more positive sentiments than stories by boys. Our study shows the utility of large‐scale data‐driven approaches to reveal the content and nature of children's writing. Future experimental work should build on these observations to understand the likely complex relationships between written language and emotion, and how these change over development. (shrink)

This paper describes a computer simulation of reading that is strongly driven by eye fixation data from human readers. The simulation, READER, is a natural language understanding system that reads a text word by word and whose processing cycles on each word have some correspondence with the human gaze duration on that word. READER operates within a newly developed information processing architecture, a Collaborative, Activation‐based, Production System (CAPS) that permits the modeling of the temporal properties of human comprehension. CAPS (...) allows for concurrent, collaborative execution of processes operating at different levels of analysis. As READER encounters each successive word, the word is operated on by processes at the levels of word encoding, lexical access, syntactic and semantic analysis, and referential and schema‐level processes. Like human readers, READER uses a strategy of immediacy of comprehension, attempting to interpret each word as soon as it is encountered, rather than unnecessarily buffering information. A major contribution of this simulation is its use of human performance characteristics in constraining and determining the model's mechanisms. (shrink)

The automobile is a tool like no other. There is much excitement and enthusiasm for new and emerging transportation tools such as vehicle automation and driver assistance systems. Although there are high hopes for these technologies, there are many unknowns including the extent to which these new transportation tools can realistically and reliably improve driver safety and affect the subjective driving experience. This paper explores these questions in the context of evaluating collision warning systems on the behavior and perceptions of (...) drivers with different amounts of experience and places the results in the greater context of tool use and skilled learning focusing on the adoption and utilization of mental models. (shrink)

Once a central topic of philosophy of science, scientific explanation attracted less attention in the last two decades. My aim in this paper is to argue for a newsort of approach towards scientific explanation. In a first step I propose a classification of different approaches through a set of dichotomic characteristics. Taken into account the tendencies in actual philosophy of science I see a local, dynamic and non-theory driven approach as a plausible one. Considering models as bearers (...) of explanations will provide a proper frame for such an approach. In the second part I make some suggestions for a working agenda that will further articulate a sketchy account of explanation through models proposed by Hartmann and Frigg. (shrink)

In this paper we introduce a computational control framework that can keep AI-driven military autonomous devices operating within the boundaries set by applicable rules of International Humanitarian Law (IHL) related to targeting. We discuss the necessary legal tests and variables, and introduce the structure of a hypothetical IHL-compliant targeting system.

As a leading scientist of the 13th century C. E. Quṭb al-Dīn Shīrāzī wrote three substantial works on hay'a (or the configuration of the celestial orbs): Nihāyat al-idrāk fī dirāyat al-aflāk ("The Limits of Attainment in the Understanding of the Heavens"), al-Tuḥfa al-shāhīya fī 'ilm al-hay'a ("The Royal Offering Regarding the Knowledge of the Configuration of the Heavens"), and Ikhtīyārāt-i Muẓaffarī ("The Muẓaffarī Elections"). Completed in less than four years and written in two of the classical languages of the Islamic (...) world, Arabic and Persian, these works provide a fascinating window to the astronomical research carried out in Ilkhanid Persia. Shīrāzī and his colleagues were driven by their desire to rid Ptolemaic astronomy from its perceived shortcomings. An intriguing trail of revisions and emendations in Shīrāzī's hay'a texts serves to highlight both those features of Shīrāzī's astronomy that were inherited from his predecessors, as well as his original contributions to this branch of astronomical research. As a renowned savant, Shīrāzī spent a large portion of his career near centers of political power in Persia and Anatolia. A study of his scientific output and career as a scholar is an opportunity, therefore, for an examination of the patronage of science and of scientific works within the Ilkhanid realms. Not only was this patronage important to the work of scholars such as Shīrāzī but it was critical to the founding and operation of one of the foremost scientific institutions of the medieval Islamic world, the Marāgha observatory. The astronomical tradition in which Shīrāzī carried out his research has many links, as well, to the astronomy of Early Modern Europe, as can be seen in the astronomical models of Copernicus. (shrink)

The field of epistemic logic developed into an interdisciplinary area focused on explicating epistemic issues in, for example, artificial intelligence, computer security, game theory, economics, multiagent systems and the social sciences. Inspired, in part, by issues in these different ‘application’ areas, in this paper I propose an epistemic logic T for metadata extracted from scientific papers on COVID-19. More in details, I introduce a structure S to syntactically and semantically modelling metadata extracted with systems for extracting structured metadata from scientific (...) articles in a born-digital form. These systems will be considered, in the logical model created, as ‘Metadata extraction agents’. In this case MEA taken into consideration are CERMINE and TeamBeam. In an increasingly data-driven world, modelling data or metadata means to help systematise existing information and support the research community in building solutions to the COVID-19 pandemic. (shrink)

The research programme of the philosophy of information (PI) proposed in 2002 made it an independent area or discipline in philosophical research. The scientific concept of ‘information’ is formally accepted in philosophical inquiry. Hence a new and tool-driven philosophical discipline of PI with its interdisciplinary nature has been established. Philosophy of information is an ‘orientative’ rather than ‘cognitive’ philosophy. When PI is under consideration in the history of Western philosophy, it can be regarded as a shift of large tradition. (...) There are three large traditions at large, known as Platonic, Kantian and Leibniz-Russellian. In the discussion of the position of the possible worlds, we have modal Platonism and modal realism, but both of the theories are made in the framework of Western philosophy. In this essay, it is argued that possible worlds could be seen as worlds in information, which is then an interpretation of modal information theory (MIT). Our interpretation is made on the basis of Leibniz’s lifelong connection with China, a fact often overlooked by the Western philosophers. Possible world theory was influenced by the Neo-Confucianism flourishing since the Song Dynasty of China, the foundation of which is Yijing. It could be argued that Leibniz’s possible world theory was formulated in respect to the impact of the thoughts reflected in Yijing, in that one of the prominent features is the model-theoretic construction of theories. There are two approaches to theory construction, i.e., axiom-theoretic and model-theoretic. The origin of the former is from ancient Greece and the latter from ancient China. And they determined the different features of theoretic structures between the oriental and occidental traditions of science and technology. The tendency of the future development of science and technology is changing from the axiom-theoretic to the model-theoretic orientation, at least the two approaches being complementary each other. To some extent, this means the retrospective of tradition in the turning point of history, and some of the China’s cultural traditions might become the starting points in formulating the future Chinese philosophy of science and technology. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Science in a Democratic Society by Philip KitcherHenry S. RichardsonReview: Philip Kitcher, Science in a Democratic Society, Prometheus Books, 2011In examining the place of science in a democratic society, Philip Kitcher is ultimately asking what standards scientific activity is answerable to. Here, as in Science, Truth, and Democracy (Oxford University Press, 2001), he rejects two extreme possibilities: first, the suggestion that science is (...) autonomous, in the sense that it is answerable only to its own standards; and, second, the suggestion that it is answerable to “vulgar democracy”—that is, to unconstrained majority rule by untutored citizens. In this book, as in the earlier book, he deploys the idea of “well-ordered science,” which he seeks to characterize in part by leaning on the idea of a hypothetical, ideal conversation. Crucially informing this newer book is a much fuller account of nonvulgar democracy. Underlying that account is a much broader picture of “the ethical project”—the title idea of another important Kitcher book from 2011 (Harvard University Press).In order to motivate the friends of science to turn to these broader ethical ideas, Kitcher persuasively rehearses the case against value neutrality in science. Much current distrust of science and scientists, he argues, derives from scientists falsely pretending—whether deludedly or cynically—that science can proceed in a value-neutral way. It cannot do so in resolving competitions among theories, let alone in setting the research agenda or weighing in on practical problems of public concern. By wearing a false mask of value neutrality, scientists succeed only in convincing the public that they are ideologically driven. This, in turn, gives an opening for dissenters motivated by religion or by their own ideologies to develop supposedly scientific counter-claims of their own, such as those that assert creationism or deny the reality of climate change. Better, then, for science and scientists to be frank about its lack of value neutrality. [End Page E-106]What values ought to inform science? To answer this question, Kitcher turns to his conception of the ethical project, of which Chapter 2 gives a summary. As he conceives of ethics, it arose pre-historically as a set of mechanisms helping us to deal with deficiencies in altruistic motivation. Although inspired by evolutionary theory, Kitcher spurns the sociobiologist’s identification of the good with the adaptive. Instead, while giving an elaborate reconstruction of how our ethical practices may actually have arisen, he gives pride of place to the idea of conversation. On his reconstruction, the “egalitarian plateau” touted by Will Kymlicka (Contemporary Political Philosophy [Oxford University Press, 1990], p. 5) and others as the great achievement of the Enlightenment was merely a delayed philosophical echo of the ethical project’s initial feature, one that would have been found in the ethical discussions of human hunter-gatherer bands of forty-thousand years ago. Being more focused on how life is lived than on philosophy, Kitcher, fairly enough, is unwilling to see the Enlightenment as an egalitarian age. Rather, most recent incarnations of the ethical project have been distorted by hierarchies and inequalities. Emphasizing the word, Kitcher writes, “I propose... that we undo the distortion,” and model the ethical project, going forward, as involving an egalitarian conversation. This frankness disarms any worry about the move from ‘was’ to ‘ought’ that might have arisen in the minds of those already puzzled by the current popularity of the cave-man diet; and in any case, since Kitcher’s account of the ethical project is defended at length in his contemporaneous book of that title, doubts about it would be better addressed in that context. Rhetorically, since the ideal of treating persons fundamentally as equals is even more popular than eating meat, he is on strong ground here.The book develops this core egalitarian proposal in three distinct ways, thereby gaining a rich evaluative basis for considering the place of science in society. The first is an account of the purposes to which science is answerable. Kitcher dismisses as unrealistically high-minded and ultimately elitist a conception of scientists as driven by a disinterested quest for truth and a simple love of knowledge for its own sake. Rather, his... (shrink)

About three decades ago, the late Ronald Giere introduced a new framework for teaching scientific reasoning to science students. Giere’s framework presents a model-based alternative to the traditional statement approach—in which scientific inferences are reconstructed as explicit arguments, composed of (single-sentence) premises and a conclusion. Subsequent research in science education has shown that model-based approaches are particularly effective in teaching science students how to understand and evaluate scientific reasoning. One limitation of Giere’s framework, however, is (...) that it covers only one type of scientific reasoning, namely the reasoning deployed in hypothesis-driven research practices. In this paper, we describe an extension of the framework. More specifically, we develop an additional model-based scheme that captures reasoning in application-oriented practices (which are very well represented in contemporary science). Our own teaching experience suggests that this extended framework is able to engage a wider audience than Giere’s original. With an eye on going beyond such anecdotal evidence, we invite our readers to test out the framework in their own teaching. (shrink)