Comparing different causes’ importance, and apportioning responsibility between them, requires making good sense of the notion of partial explanation, that is, of degree of explanation. How much is this subjective, how much objective? If the causes in question are probabilistic, how much is the outcome due to them and how much to simple chance? I formulate the notion of degree of causation, or effect size, relating it to influential recent work in the literature on causation. I examine to (...) what extent mainstream social science methods--both quantitative and qualitative--succeed in establishing effect sizes so understood. The answer turns out to be, roughly: only to some extent. Next, the standard understanding of effect size, even though widespread, still has several underappreciated consequences. I detail some of those. Finally, I discuss the separate issue of explanandum-dependence, which is essential to assessing any cause’s explanatory importance and yet which has been comparatively neglected. (shrink)

_ Source: _Volume 5, Issue 2, pp 228 - 250 Despite inroads made by critical realism against the ‘scientific method’ in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as (...) a case study empirical research on the alleged empirical association between human resource management practices and organisational performance. By unpacking the confusion surrounding the two basic notions of prediction used, it reveals what is wrong with them, why the scientific method cannot actually make accurate predictions and why, therefore, the scientific method fails to meet its own criteria for scientificity. Finally, explanation is considered in order to prevent any confusion between it and prediction and to offer what we call _tendential prediction_. (shrink)

Criteria of the growth of knowledge proposed in modern philosophy of science are considered. It is argued that the model of growth that fits the peculiarities of social sciences&humanities is provided by the methodology of scientific research programmes. Yet one has to correct some drawbacks. The author concludes that the real growth of knowledge consists in the growth of causal explanations and in the corresponding growth of empirical content of the theories from superseeding scientific research programmes. -/- Key (...) words: R.Rorty, M.Weber,N.Cartwright -/- . (shrink)

This paper applies a pragmatic-retorical theory of explanation and interpretation to understand the methodological perspectivism of the social sciences.

The debates on the scientificity of social sciences in general, and sociology in particular, are recurring. From the original methodenstreitat the end the 19th Century to the contemporary controversy on the legitimacy of “regional epistemologies”, a same set of interrogations reappears. Are social sciences really scientific? And if so, are they sciences like other sciences? How should we conceive “research programs” Lakatos (1978) or “research traditions” for Laudan (1977) able to produce advancement of knowledge in the field of (...) social and human phenomena? Is the progress of knowledge in social sciences similar to the one generally observed in natural sciences? Is it possible to evaluate the relative merits of each one of these research programs? -/- These debates are important vectors of social and intellectual polarization. The historical divide between the positivist and the hermeneutics poles precedes the structure of the contemporary debate around the epistemic space of social sciences, It is not only a question of renewing the opposition between a monist view of sciences (e.g. McIntyre, 1996) and a dualistic one (e.g. Geertz, 1973) or even a trialist view of sciences (e.g. Lepenies, 1985). It is also a question of asserting dichotomies transformed into framework (including when it is a question of exceeding them): nature-culture, nomothetic-idiographic, models-narrative, structure-history, cause-reason, explanation-comprehension. -/- In this short introduction, we provide, in section 2, a first overview of this epistemological debate in social science. Section 3 proposes a different standpoint on the same questions, by introducing both ontological and methodological aspects in this basic epistemological debate. Namely, following (Hollis, 1994) oppositions of the explanation - understanding, causes - meaning, etc., types discussed in the firsts ection are comparatively examined together with oppositions of the structure - action, holism - individualism types. This allows us to discus show multi-agent design, by integrating various dimensions and standpoints in the same framework (Phan, Amblard, 2007, Chapters 1, 5, 14) can help us to shift these boundaries, and to bypass these oppositions. As model building and ontology design are at the core of this process (Phan, Amblard, 2007, Chapter 12), Section4 discusses various issues of the art of modelling, starting both from economists’ and sociologists’ current standpoints. (shrink)

The Philosophy of Social Science: A Contemporary Introduction examines the perennial questions of philosophy by engaging with the empirical study of society. The book offers a comprehensive overview of debates in the field, with special attention to questions arising from new research programs in the social sciences. The text uses detailed examples of social scientific research to motivate and illustrate the philosophical discussion. Topics include the relationship of social policy to social science, interpretive (...) research, action explanation, game theory, social scientific accounts of norms, joint intentionality, reductionism, causal modeling, case study research, and experimentation. (shrink)

The kinds of real or natural kinds that support explanation and prediction in the social sciences are difficult to identify and track because they change through time, intersect with one another, and they do not always exhibit their properties when one encounters them. As a result, conceptual practices directed at these kinds will often refer in ways that are partial, equivocal, or redundant. To improve this epistemic situation, it is important to employ open-ended classificatory concepts, to understand when (...) different research programs are tracking the same real kind, and to maintain an ongoing commitment to interact causally with real kinds to focus reference on those kinds. A tempting view of these non-idealized epistemic conditions should be avoided: that they signal an ontological structure of the social world so plentiful that it would permit ameliorated classificatory schemes to achieve their normative aims regardless of whether they defer to real-kind classificatory schemes. To ground these discussions, the essay appeals to an overlooked convergence in the systematic naturalistic frameworks of Richard Boyd and Ruth Millikan. (shrink)

, whereby some causes are deemed more important than others, are ubiquitous in historical studies. Drawing from influential recent work on causation, I develop a definition of causal-explanatory strength. This makes clear exactly which aspects of explanatory weighting are subjective and which objective. It also sheds new light on several traditional issues, showing for instance that: underlying causes need not be more important than proximate ones; several different causes can each be responsible for most of an effect; small causes need (...) not be less important than big ones; and non-additive interactive effects between causes present no particular difficulty. Key Words: causation • explanation • history • interaction • proximate • underlying. (shrink)

This article makes three claims concerning the concept of contingency. First, we argue that the word contingency is used in far too many ways to be useful. Its many meanings are detrimental to clarity of discussion and thought in history and the social sciences. We show how there are eight distinct uses of the word and illustrate this with numerous examples from the social sciences and history, highlighting the scope for confusion caused by the many, often contradictory uses (...) of the term. Second, we impose some order on these uses through developing a threefold classification of contingency based on assumptions about possible worlds and determinism. Finally, we discuss why we believe that one of the classes is a special use of the word without relevance to the social sciences, while the two remaining classes are nothing more than a variety of the “no hidden factors” argument in the debate on indeterminism and determinism. (shrink)

In clinical medicine, a diagnosis can offer an explanation of a patient's symptoms by specifying the pathology that is causing them. Diagnoses in psychiatry are also sometimes presented in clinical texts as if they pick out pathological processes that cause sets of symptoms. However, current evidence suggests the possibility that many diagnostic categories in psychiatry are highly causally heterogeneous. For example, major depressive disorder may not be associated with a single type of underlying pathological process, but with a range (...) of different causal pathways, each involving complex interactions of various biological, psychological, and social factors. This paper explores the implications of causal heterogeneity for whether psychiatric diagnoses can be said to serve causal explanatory roles in clinical practice. I argue that while they may fall short of picking out a specific cause of the patient's symptoms, they can nonetheless supply different sorts of clinically relevant causal information. In particular, I suggest that some psychiatric diagnoses provide negative information that rules out certain causes, some provide approximate or disjunctive information about the range of possible causal processes, and some provide causal information about the relations between the symptoms themselves. (shrink)

In the social sciences, within the explanatory paradigm of structural individualism, a theory of action – like rational choice theory – models how individuals behave and interact at the micro level in order to explain macro observations as the aggregation of these individuals actions. A central epistemological issue is that such theoretical models are stuck in a dilemma between falsity of their basic assumptions and triviality of their explanation. On the one hand, models which have a great empirical (...) success often rest on unrealistic or even knowingly false assumptions; on the other hand, more complex models, with additional more realistic hypotheses, can (trivially) adapt to a wide range of situations and thus loose their explanatory power. Our purpose here is epistemological and consists in wondering to which extent demanding realistic assumptions in such cases is a relevant criterion with respect to the acceptance of a given explanatory model. Via an analogical reasoning with physics, we argue that this criterion seems too strong and actually irrelevant. General physical principles are not just idealized or unrealistic, they can also be formulated in many different yet equivalent ways which do not imply the same fundamental unobservable entities or phenomena. However, the classification of phenomena that such principles allow to highlight does not depend, at the end, on any particular formulation of these basic assumptions. This suggests that some hypotheses in theoretical models are actually not genuine empirical statements that could be independently tested but only substrates of modeling embodying a classification principle. Thus, we develop a structural invariance criterion that we then apply to rational choice models in the social sciences. We argue that this criterion allows to escape from the epistemological dilemma without condemning formal approaches like rational choice theory for their lack of realisticness nor being stuck to any antirealist viewpoint. (shrink)

For some the gene-centered reductionism that permeates contemporary neo-Darwinism is an obstacle for finding a common explanatory framework for both biological and cultural evolution. Thus social scientists are tempted to find new concepts that might bridge the divide between biology and sociology. Yet since Aristotle we know that the level of explanation must be commensurate with the particular question to be answered. In modern natural science there are many instances where a reductionist approach has failed to provide (...) the right answer to the corresponding question. Thus social scientists risk becoming non-relevant when mimicking some features of the natural sciences (such as hard or soft reductionism) just for the sake of it, instead of finding autonomous explanations commensurate with the level of phenomena studied by social science. (shrink)

This article aims to combine the strengths of Erich Fromm’s and John Dewey’s social philosophies. I argue that the merits of this comparison become particularly clear when the theories are outlined and compared in the following three steps. First, a social theoretical common ground of Dewey and Fromm will be illustrated. Their “World War genealogies” share the same defense mechanism as the major explanation of the Germans’ tendency to voluntary submission, which involves a strong feeling of powerlessness. (...) Against this background, the next step elaborates the ethical side of their argument. Already the World War genealogies are written with melioristic intent, and especially later works (in case of both authors) elaborate the respective ethical theory as well as the ideas concerning melioristic social science and social psychology. These ethics aim at good communication (in a broad sense), while the melioristic social research focuses on the concrete manifestations of social character, allowing to empirically identify hindering and facilitating factors of social amelioration. Both can be linked using the concept of communicative power(lessness). By way of outlook, I will finally consider the combination of a democratic, communication-oriented ethics with qualitative sociopsychoanalytic research in Fromm’s sense as a straightforward and promising approach for an interdisciplinary social philosophy. (shrink)

Academia is a competitive environment. Early Career Researchers (ECRs) are limited in experience and resources and especially need achievements to secure and expand their careers. To help with these issues, this book offers a new approach for conducting research using the combination of mindsponge innovative thinking and Bayesian analytics. This is not just another analytics book. 1. A new perspective on psychological processes: Mindsponge is a novel approach for examining the human mind’s information processing mechanism. This conceptual framework is used (...) to construct models in studies. The framework is highly flexible and widely applicable for many different types of information processes. The mindsponge approach can help researchers discover interesting ideas or even formulate their very own theories when investigating psychosocial phenomena. This approach brings a fresh wind to the current landscape of social sciences and humanities (SSH). 2. Easy-to-follow analysis protocol: The Bayesian Mindsponge Framework (BMF analytics) is useful in terms of computing and visualizing power but also easy to learn and apply. Contrary to being intimidating, the Bayesian analytics section of this book is presented in a reader-friendly manner with a detailed yet clear step-by-step procedure. Examples are from published BMF articles, allowing readers to immediately practice the method and quickly create their own applications. With educational purposes in mind, the book is very suitable for ECRs who are looking to innovate their research methods. 3. Advocating for low-cost, high-quality research: Doing science can be very costly. Mindsponge innovative thinking and BMF analytics help produce impactful studies using openly available data on online repositories. This is based on the authors’ previous works and experiences. The book presents examples of employing the open R package bayesvl on secondary data from different sources. With less financial constraints, researchers can have more freedom of thought to pursue their curiosity and creativity. ECRs in low- and middle-income countries may find this aspect crucial in their careers. 4. Support and collaboration: The authors share their insights from experiences in the academic publishing system to help readers get through the processes of manuscript writing and peer-reviewing more easily. The authors are also ready to support other researchers with further inquiries and collaboration opportunities at the following website, mindsponge(dot)info. This book is for: a) ECRs whose only abundant resources are their innovation capacity and strength of will; b) Researchers in SSH who want to explore a novel approach to thinking and study conducting; c) Low- and middle-income countries’ researchers looking for a cost-effective research protocol; and, d) Innovative thinkers who want to turn their interesting thoughts into good publications. (shrink)

Political science is divided between methodological individualists, who seek to explain political phenomena by reference to individuals and their interactions, and holists (or nonreductionists), who consider some higher-level social entities or properties such as states, institutions, or cultures ontologically or causally significant. We propose a reconciliation between these two perspectives, building on related work in philosophy. After laying out a taxonomy of different variants of each view, we observe that (i) although political phenomena result from underlying individual attitudes (...) and behavior, individual-level descriptions do not always capture all explanatorily salient properties, and (ii) nonreductionistic explanations are mandated when social regularities are robust to changes in their individual-level realization. We characterize the dividing line between phenomena requiring nonreductionistic explanation and phenomena permitting individualistic explanation and give examples from the study of ethnic conflicts, social-network theory, and international-relations theory. (shrink)

This paper considers the question of whether the influential distinction between levels of explanation introduced by David Marr can be used as a general framework for contemplating levels of explanation in cognitive sciences. Marr introduced three levels at which we can explain cognitive processes: the computational, algorithmic, and implementational levels. Some argue that Marr’s levels of explanation can only be applied to modular cognitive systems. However, since many psychological processes are non-modular, it seems that Marr’s levels of (...) explanation cannot explain such psychological processes. To show that the latter claim is not convincing, the paper draws upon an influential paradigm from cognitive sciences that is based on the principle of free energy. Based on this paradigm, the paper argues that even non-modular psychological processes can be computationally analyzed and algorithmically implemented. The conclusion of the paper is that, at least under the assumption that the func- tion of the mind is to minimize free energy, Marr’s levels of explanation can be successfully used as a general framework for understanding psychological processes at different levels of description. (shrink)

I identify two versions of the scientific anti-realist’s selectionist explanation for the success of science: Bas van Fraassen’s original and K. Brad Wray’s newer interpretation. In Wray’s version, psycho-social factors internal to the scientific community – viz. scientists’ interests, goals, and preferences – explain the theory-selection practices that explain theory-success. I argue that, if Wray’s version were correct, then science should resemble art. In art, the artwork-selection practices that explain artwork-success appear faddish. They are prone to (...) radical change over time. Theory-selection practices that explain theory-success in science are however not faddish. They are mostly stable; that is, long-lived and consistent over time. This is because scientists (explicitly or implicitly) subscribe to what I will call the testability norm: scientific theories must make falsifiable claims about the external physical world. The testability norm and not psycho-sociology explains the theory-selection practices that explain theory-success in science. Contra Wray, scientific anti-realists can then maintain that the external physical world (as expressed in the testability norm) explains theory-success. (shrink)

This paper challenges the first Gettier counterexample to the tripartite account of knowledge. Noting that 'the man who will get the job' is a description and invoking Donnellan's distinction between their 'referential' and 'attributive' uses, I argue that Smith does not actually believe that the man who will get the job has ten coins in his pocket. Smith's ignorance about who will get the job shows that the belief cannot be understood referentially, his ignorance of the coins in his pocket (...) shows that it cannot be understood attributively. An explanation for why Smith appeared to have justified true belief is given by distinguishing between 'belief' and 'belief in truth'. Smith believes the sentence 'the man who will get the job has ten coins in his pocket' to be true (he mistakenly believes that Jones will get the job, of whom he knows that he has ten coins in his pocket) (hence his 'belief'), the sentence is true (hence 'truth'), and he has sufficient reason to assent to it (hence his 'justification'). But he does not believe the proposition expressed. Hence he does not know it either. (shrink)

The subject of this chapter is the complex and confusing course of the discussion of cause and teleology before and during the period of Mill and Comte, and its aftermath up to the early years of the twentieth century in the thinking of several of the major founding figures of disciplinary social science. The discussion focused on the problem of the sufficiency of causal explanations, and particularly the question of whether some particular fact could be explained without appeal (...) to purpose. In response to such questions, the defenders of the new conception attempted to replace older terminology with new (“function” for “purpose,” for example), sometimes muddling the issues, sometimes turning them into terminological disputes, and sometimes making the different positions difficult to distinguish. The problem of methodological unity in the social sciences is rooted in the discussions of the time. (shrink)

The paper revisits the rationality principle from the particular perspective of the unity of social sciences. It has been argued that the principle was the unique law of the social sciences and that accordingly there are no deep differences between them (Popper). It has also been argued that the rationality principle was specific to economics as opposed to the other social sciences, especially sociology (Pareto). The paper rejects these opposite views on the grounds that the rationality principle (...) is strictly metaphysical and does not have the logical force required to deliver interesting deductions. Explanation in the social sciences takes place at a level of specialization that is always higher than that of the principle itself. However, what is peculiar about economics is that it specializes the explanatory rational schemes to a degree unparalleled in history and sociology. As a consequence, there is a backward-and-forward move between specific and general formulations of rationality that takes place in economics and has no analogue in the other social sciences. (shrink)

This article discusses the rationality principle, especially in Popper's version, on the occasion of a commentary of Maurice Lagueux's book, Rationality and Explanation in Economics (2010).

An analysis of the theses of social holism and individualism, and arguments for the metaphysical integrity and irreducibility of both social properties and social entities. The last chapter discusses explanation in social science.

I show how archaeologists have two problems. The construction of scenarios accounting for the raw data of Archaeology, the material remains of the past, and the explanation of pre-history. Within Archaeology, there has been an ongoing debate about how to constrain speculation within both of these archaeological projects, and archaeologists have consistently looked to biological mechanisms for constraints. I demonstrate the problems of using biology, either as an analogy for cultural processes or through direct application of biological principles to (...) material remains. This is done through setting out the requirements of a Darwinian Archaeology, and then measuring various approaches against these requirements. This approach leads to the conclusion that archaeologist's explanations of the past must include within their formulations an account of human cognitive capacities within their explanatory framework. The limits of our understanding of the human past will be the limits of our understanding of Homo sapiens. (shrink)

Rival causal and interpretive approaches to explaining social phenomena have important ethical differences. While human actions can be explained as a result of causal mechanisms, as a meaningful choice based on reasons, or as some combination of the two, it is morally important that social scientists respect others by recognizing them as persons. Interpretive explanations directly respect their subjects in this way, while purely causal explanations do not. Yet although causal explanations are not themselves expressions of respect, they (...) can be used in respectful ways if they are incorporated into subjects’ self-directed projects. This can occur when subjects correctly understand and freely adopt researchers’ goals through a process of informed consent. It can also occur when researchers correctly understand and adopt their subject’s goals, using their research to empower those they study. (shrink)

Deception of subjects is used frequently in the social sciences. Examples are provided. The ethics of experimental deception are discussed, in particular various maneuvers to solve the problem. The results have implications for the use of deception in the biomedical sciences.

Social scientists appeal to various “structures” in their explanations including public policies, economic systems, and social hierarchies. Significant debate surrounds the explanatory relevance of these factors for various outcomes such as health, behavioral, and economic patterns. This paper provides a causal account of social structural explanation that is motivated by Haslanger (2016). This account suggests that social structure can be explanatory in virtue of operating as a causal constraint, which is a causal factor with unique (...) characteristics. A novel causal framework is provided for understanding these explanations–this framework addresses puzzles regarding the mysterious causal influence of social structure, how to understand its relation to individual choice, and what makes it the main explanatory (and causally responsible) factor for various outcomes. (shrink)

The approach of structuralism came to philosophy from social science. It was also in social science where, in 1950–1970s, in the form of the French structuralism, the approach gained its widest recognition. Since then, however, the approach fell out of favour in social science. Recently, structuralism is gaining currency in the philosophy of mathematics. After ascertaining that the two structuralisms indeed share a common core, the question stands whether general structuralism could not find its (...) way back into social science. The nature of the major objections raised against French structuralism – concerning its alleged ahistoricism, methodological holism and universalism – are reconsidered. While admittedly grounded as far as French structuralism is concerned, these objections do not affect general structuralism as such. The fate of French structuralism thus does not seem to preclude the return of general structuralism into social science, rather, it provides some hints where the difficulties may lie. (shrink)

"Explanation and Understanding" (1971) by Georg Henrik von Wright is a modern classic in analytic hermeneutics, and in the philosophy of the social sciences and humanities in general. In this work, von Wright argues against naturalism, or methodological monism, i.e. the idea that both the natural sciences and the social sciences follow broadly the same general scientific approach and aim to achieve causal explanations. Against this view, von Wright contends that the social sciences are qualitatively different (...) from the natural sciences: according to his view, the natural sciences aim at causal explanations, whereas the purpose of the social sciences is to understand their subjects. In support of this conviction, von Wright also puts forward a version of the so-called logical connection argument. -/- Von Wright views scientific explanation along the lines of the traditional covering law model. He suggests that the social sciences, in contrast, utilize what he calls “practical syllogism” in understanding human actions. In addition, von Wright presents in this work an original picture on causation: a version of the manipulability theory of causation. -/- In the four decades following von Wright’s classic work, the overall picture in in the philosophy of science has changed significantly, and much progress has been made in various fronts. The aim of the contribution is to revisit the central ideas of "Explanation and Understanding" and evaluate them from this perspective. The covering law model of explanation and the regularity theory of causation behind it have since then fallen into disfavor, and virtually no one believes that causal explanations even in the natural sciences comply with the covering law model. No wonder then that covering law explanations are not found in the social sciences either. Ironically, the most popular theory of causal explanation in the philosophy of science nowadays is the interventionist theory, which is a descendant of the manipulability theory of von Wright and others. However, this theory can be applied with no special difficulties in both the natural sciences and the social sciences. -/- Von Wright’s logical connection argument and his ideas concerning practical syllogisms are also critically assessed. It is argued that in closer scrutiny, they do not pose serious problems for the view that the social sciences too provide causal explanations. In sum, von Wright’s arguments against naturalism do not appear, in today’s perspective, particularly convincing. (shrink)

Some explanations in social science, psychology and biology belong to a higher level than other explanations. And higher explanations possess the virtue of abstracting away from the details of lower explanations, many philosophers argue. As a result, these higher explanations are irreplaceable. And this suggests that there are genuine higher laws or patterns involving social, psychological and biological states. I show that this ‘abstractness argument’ is really an argument schema, not a single argument. This is because the (...) argument uses the ‘is lower than’ relation, and this relation admits of different readings. I then suggest four rigorous definitions of the ‘is lower than’ relation, and show that the abstractness argument’s prospects are much brighter for some of these definitions than for others. To show this, I evaluate the so-called ‘disjunctive threat’ to the abstractness argument. (shrink)

Power is often taken to be a central concept in social and political thought that can contribute to the explanation of many different social phenomena. This article argues that in order to play this role, a general theory of power is required to identify a stable causal capacity, one that does not depend on idiosyncratic social conditions and can thus exert its characteristic influence in a wide range of cases. It considers three promising strategies for such (...) a theory, which ground power in (1) the ability to use force, (2) access to resources, or (3) collective acceptance. It shows that these strategies fail to identify a stable causal capacity. The lack of an adequate general theory of power suggests that the concept lacks the necessary unity to play the broad explanatory role it is often accorded. (shrink)

The orthodox view of social cognition maintains that mentalizing is an important and pervasive element of our ordinary social interactions. The orthodoxy has come under scrutiny from various sources recently. Critics from the phenomenological tradition argue that phenomenological reflection on our social interactions tells against the orthodox view. Proponents of pluralistic folk psychology argue that our ordinary social interactions extend far beyond mentalizing. Both sorts of critics argue that emphasis in social cognition research ought to (...) be on other elements of our social practices. In this paper, I consider social explanations specifically and argue that social explanations are implicated in many of the social practices highlighted by critics of the orthodox view. (shrink)

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the (...) nature of complex systems in general. -/- Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. -/- Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. -/- Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. -/- With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. -/- Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework. (shrink)

My contribution to this Symposium focuses on the links between sexuality and reproduction from the evolutionary point of view.' The relation between women's sexuality and reproduction is particularly importantb ecause of a vital intersectionb etweenp olitics and biology feminists have noticed, for more than a century, that women's identity is often defined in terms of her reproductive capacity. More recently, in the second wave of the feminist movement in the United States, debates about women'si dentityh ave explicitlyi ncludeds exuality;m uch (...) feminist argument in the late 1960's and early 1970's involved an attempt to separate out an autonomous female sexuality from women's reproductive functions. It is especially relevant, then, to examine biological arguments, particularlye volutionarya rgumentst, o see what they say about whether and how women's sexuality is related to reproduction. We shall find that many evolutionarya rgumentss eem to supportt he direct linkingo f female sexualitya nd reproductionY. et I will argue that this supporti s not well-groundedI. n fact, I think evolutionarye xplanationso f female sexuality exemplify how social beliefs and social agendas can influence very basic biological explanations of fundamental physiological processes. In this paper, I shall spend some time spelling out a few examples in which assumptions about the close link between reproduction and sexuality yield misleading results, then I shall conclude with a discussion of the consequences of this case study for issues in the philosophy of science. (shrink)

A careful elaboration and defence of holism in the philosophy of the social sciences, with regard both to particulars and properties. The last chapter addresses the issue of the irreducibility of holistic explanation in the social sciences.

The paper aims at identifying, explaining and illustrating the affordances of “creative nonfiction” as a style of writing social science. The first part introduces creative nonfiction as a method of writing which brings together empirical material and fiction. In the second part, based on illustrations from my ethnographic research of European “crisis reporters,” written in the form of a novel about a fictional journalist, but also based on a review of existing social science research that employs (...) a creative method of writing, I identify several main affordances of creative nonfiction in social-scientific research. In particular, I argue that creative nonfiction allows scientists to illustrate their findings, to express them in an allegorical way, to organize data into a narrative, to let their pieces of research act in the social world, and to permeate research accounts with self-reflexive moments. I also discuss some apparent negative affordances: challenges that creative nonfiction poses to readers and to the institutionalized academic discourse. Finally, I suggest that writing about sociological problems in the style of creative nonfiction can help to produce more engaging and engaged texts, and I discuss the ethical implications of the approach. (shrink)

The persistence of “stargazing,” p-hacking and HARKing4 are among the main causes for the severity of the irreproducibility problem in social sciences.

Given the reproducibility crisis (or replication crisis), more psychologists and social-cultural scientists are getting involved with Bayesian inference. Therefore, the current article provides a brief overview of programs (or software) and steps to conduct Bayesian data analysis in social sciences.

Advocating a sociological explanation of scientific knowledge, David Bloor protests against the adherents of the autonomy of knowledge; i.e., those who asymmetrically explain the credibility of theories in the history of science. These philosophers and historians regard the credibility of true and rational theories due to their proper reasons, while accounting for the acceptance of false or irrational beliefs by citing social causes. Bloor assumes that the credibility of all beliefs is socially influenced, and therefore considers all (...) in need of sociological explanation. To substantiate this claim, he argues that all epistemic factors that are appealed to in explaining true or rational beliefs are really social. However, this argument aligns rational entities with social factors, and thus, undermines the ground of this division. Therefore, his prior complaint of the autonomy of knowledge would be invalidated. Hence, there is a conflict between Bloor’s objection to the asymmetrical explanation of scientific theories and his account of the social construction of epistemic reasons. In this paper, we reveal this concealed conflict and attempt to suggest ways to resolve it. (shrink)

The attempt to construct an applied science of social change raises certain concerns, both theoretical and ethical. The theoretical concerns relate to the feasibility of predicting human behavior with sufficient reliability to ground a science that aspires to the management of social processes. The ethical concerns relate to the moral hazards involved in the modification of human social arrangements, given the unreliability of predicting human action.

The article discusses some aspects of the narrative explanation, and its nature and role in explaining the historical entities. The author defends possibility of formulating status of narrative explanation as scientific and adequate for all historical sciences, here defined as sciences concerned with the spatio-temporally restricted entities. lie suggests that uniqueness and particularity of historical objects are not in contradiction with the claims based on the classical model of explanation in the way of logical inferring. Results of (...) discussion are that undeveloped explanations, like explanation sketches, could be adopt, not just in accordance with pragmatic reasons, but also as the step toward full-fledged or complete explanation trough mediation of developing the scientific research programs on which they are based. (shrink)

This is a forthcoming section for the book "Theism and Atheism: Opposing Arguments in Philosophy", edited by Graham Oppy, Gregory Dawes, Evan Fales, Joseph Koterski, Mashhad Al-Allaf, Robert Fastiggi, and David Shatz. I was asked to write a brief essay on whether naturalism or theism can successfully explain the distribution of suffering in our world. Wheras another section covers the possibility that suffering is evidence against theism, my essay is concerned only with the ability for either naturalism or theism to (...) explain suffering. I argue that, for naturalists, suffering is not to be explained by either philosophers of religion or theologians. Instead, naturalists believe that suffering should be explained by the cognitive and social sciences, perhaps in conjunction with political philosophy and philosophy of mind. Moreover, naturalists may take suffering to be an important reason for action. In a world without a transcendent, supernatural being to watch over us, we can only depend upon each other to ameliorate existing conditions, to the extent that they can be ameliorated. On the other hand, theistic explanations of the distibution of suffering slip very easily into problematic theologies when they try to offer explicit explanations for suffering. For example, the world's most vulnerable people are often those who suffer the most, whereas oppressors are often able to prosper. That is, theistic explanations of our world's suffering easily slip into, e.g., the just world fallacy, racist ideology (i.e., that God favors some race(s) of people over others), or patriarchal ideology. Instead of offering an explicit explanation, theists should instead be skeptical theists -- i.e., they should argue that an explanation for our world's suffering is beyond our ken. While skeptical theism avoids the aforementioned problematic implications, if skeptical theism is true, then our world's suffering cannot be fully explained. (shrink)

The study primarily aimed at determining and utilizing extent of the Social Science instructors on instructional materials, and framing a capacity development framework to secure the quality of instructional delivery in the changing times. It employed the descriptive design undertaking the purposive sampling which resulted in obtaining 26 respondents from the total population, thus descriptive statistics had been used in analyzing and interpreting the collected data. The results reflected how social sciences are being taught by the 26 (...) purposively sampled respondents and showed that the underlying instructional materials or the non-technological ones remained as top materials that are often and occasionally being utilized, collectively implying that regardless that these are categorized as traditional and commonly used, are still being perceived as efficient and effective, such that optimizing and redesigning them to adapt to the changing landscape of instruction is elucidated in this paper through a capacity development program paradigm, in which the implementation is urgently recommended. (shrink)

Advancements in computing, instrumentation, robotics, digital imaging, and simulation modeling have changed science into a technology-driven institution. Government, industry, and society increasingly exert their influence over science, raising questions of values and objectivity. These and other profound changes have led many to speculate that we are in the midst of an epochal break in scientific history. -/- This edited volume presents an in-depth examination of these issues from philosophical, historical, social, and cultural perspectives. It offers arguments both (...) for and against the epochal break thesis in light of historical antecedents. Contributors discuss topics such as: science as a continuing epistemological enterprise; the decline of the individual scientist and the rise of communities; the intertwining of scientific and technological needs; links to prior practices and ways of thinking; the alleged divide between mode-1 and mode-2 research methods; the commodification of university science; and the shift from the scientific to a technological enterprise. Additionally, they examine the epochal break thesis using specific examples, including the transition from laboratory to real world experiments; the increased reliance on computer imaging; how analog and digital technologies condition behaviors that shape the object and beholder; the cultural significance of humanoid robots; the erosion of scientific quality in experimentation; and the effect of computers on prediction at the expense of explanation. -/- Whether these events represent a historic break in scientific theory, practice, and methodology is disputed. What they do offer is an important occasion for philosophical analysis of the epistemic, institutional and moral questions affecting current and future scientific pursuits. (shrink)

The social sciences face a problem of sample non-representation, where the majority of samples consist of undergraduate students from Euro-American institutions. The problem has been identified for decades with little trend of improvement. In this paper, I trace the history of sampling theory. The dominant framework, called the design-based approach, takes random sampling as the gold standard. The idea is that a sampling procedure that is maximally uninformative prevents samplers from introducing arbitrary bias, thus preserving sample representation. I show (...) how this framework, while good in theory, faces many challenges in application. Instead, I advocate for an alternative framework, called the model-based approach to sampling, where representative samples are those balanced in composition, however they were drawn. I argue that the model-based framework is more appropriate in the social sciences because it allows for systematic assessment of imperfect samples and methodical improvement in resource-limited scientific contexts. I end with practical proposals of improving sample quality in the social sciences. (shrink)

This chapter presents a historical study of how science has developed and of how philosophical theories of many sorts – philosophy of science, theory of the understanding, and philosophical theology – both enable and constrain certain lines of development in scientific practice. Its topic is change in the legitimacy or acceptability of scientific explanation that invokes purposes, or ends; specifically in the argument from design, in the natural science field of physico-theology, around the start of the (...) eighteenth century. ... The context that produced physico-theology was clearly religious and political. It is unsurprising that a large body of Protestant intellectuals well-placed in a relatively peaceful society with a strong tradition of open speech, would develop links between science and critical discussion of both divinity and the Bible. There were also bounds to the discussion, as Newton, who chose to sit on the sidelines, knew well. Many others on Europe’s continent lived much more intimately with religious division as well as the reminder, in 1633, of Galileo’s failure to arrange a peaceable arrangement between science and religion. These aspects of the rise of physico-theology have not been the focus of this chapter, which has surveyed the philosophical and social origins found in the English context. Science, philosophy of science and other English philosophical currents – most particularly the theory of ideas and understanding that we are familiar with in its later development by John Locke – were formative for a field that might alternatively have been called ‘empirical natural theology.’ Prior shifts in religious sensibility that emptied the Book of Nature of much of its content also prepared the ground. Other philosophical and theological currents not discussed here – most notably theories of divine agency and predestination – and other philosophical trends – the rise of Spinoza’s challenge to such natural theology on the continent – also had both shaping and limiting influences upon the field. Finally, philosophers, including natural philosophers, did much more to promote physico-theology than just write about it: Boyle in particular provided a very important launch pad for the further development of an already healthy tradition of natural theology with his named lectureship, which drew the interest of others in the Royal Society, most notably Isaac Newton, and which spawned two of the most influential physico-theological tracts shortly before and shortly after the turn of the eighteenth century. (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)

We researchers in the humanities and social sciences, similar to the archaeologists but only less literally, are constantly digging through unknown dirt and even uncharted territories in hopes of finding “diamonds.”.