The observation that concepts used by social scientists are often problematic is not new; they have been described as Ballung concepts, cluster concepts, essentially contested, and reflexive; however, the need to work with these concepts remains. This article addresses the problem of variable choice in the social sciences by exploring and extending Woodward’s recommendations. This article demonstrates why Woodward’s criteria are difficult to apply in the social sciences and proposes an alternative, but complementary, framework for assessing (...) class='Hi'>variables. (shrink)

This article argues that it is far from trivial to convert social science concepts into accurate categories on which algorithms work best. The literature raises this concern in a general way; for example, Deeks notes that legal concepts, such as proportionality, cannot be easily converted into code noting that ‘The meaning and application of these concepts is hotly debated, even among lawyers who share common vocabularies and experiences’ (Deeks in Va Law Rev 104, pp. 1529–1593, 2018). The example (...) discussed here is recidivism prediction, where the factors that are of interest are difficult to capture adequately through questionnaires because survey responses do not necessarily indicate whether the behaviour that is of interest is present. There is room for improvement in how questions are phrased, in the selection of variables, and by encouraging practitioners to consider whether a particular variable is the sort of thing that can be measured by questionnaires at all. (shrink)

This book presents a new perspective on the importance of social sciences through various studies held by the authors. The contributors to this book are researchers in the departments of Archaeology, Ethnology and Folklore, History, Culture and Tourism Management of Constantine the Philosopher University in Nitra.

We contend that social science variables are the product of multiple partly heritable traits. Genetic associations with socioeconomic status (SES) may differ across populations, but this is a consequence of the intermediary traits associated with SES differences also varying. Furthermore, genetic data allow social scientists to make causal statements regarding the aetiology and consequences of SES.

For the most part, American sociology has accepted the appealing formula of neutrality with regard to political and ideological values, a formula especially put forward by the functionalist school. It has the golden merit of posing issues in a seemingly natural science manner. The sociologist can adopt the physicist's pose toward his work. We provide society with carefully sifted information, comparative analysis of social structures, and at the upper range, the likely consequences of performing or not performing an (...) action in terms of the given diagnosis. The social scientist using a functionalist philosophy can feel free of responsibility at a decision making level. Whether society decides to employ or ignore the provided data is held to be a matter of indifference, a situation requiring moral wisdom rather than social theory. Without minimizing the sound contributions of the function-Structure approach, particularly in overcoming the provincialism and conceit of the pre-functionalist schools of anthropology, there is a sure moral undercurrent in a method which sees the social scientist as diagnostician and society as a patient. It has the appearance of satisfying the historic identification of social theory to social welfare, and no less an emotional identification with a neutral-objective image culled from physics. Social history becomes a variable in the preparation of trend reports and thereby trivialized into a moment in the functionalist scheme. (shrink)

The experimental revolution in the social sciences is one of the most significant methodological shifts undergone by the field since the ‘quantitative revolution’ in the nineteenth century. One of the often valued features of social science experimentation is precisely the fact that there are clear methodological rules regarding hypothesis testing that come from the methods of the natural sciences and from the methodology of RCTs in the biomedical sciences, and that allow for the adjudication among contentious causal (...) claims. We examine critically this claim and argue that some current understandings of the practices that surround social science experimentation overestimate the degree to which experiments can actually fulfil this role as “objective” adjudicators, by neglecting the importance of shared background knowledge or assumptions and of consensus regarding the validity of the constructs involved in an experiment. We take issue with the way the distinction between internal and external validity is often used to comment on the inferential import of experiments, used both among practitioners and among philosophers of science. We describe the ways in which the more common use of the internal/external distinction differs from Cook and Campbell’s original methodological project, in which construct validity and the four-fold validity typology were all important in assessing the inferential import of experiments. We argue that the current uses of the labels internal and external, as applied to experimental validity, help to encroach a simplistic view on the inferential import of experiments that, in turn, misrepresents their capacity to provide objective knowledge about the causal relations between variables. (shrink)

The fact that causal laws in the social sciences are most realistically expressed as both multivariate and stochastic has a number of very important implications for indirect measurement and generalizability. It becomes difficult to link theoretical definitions of general constructs in a one-to-one relationship to research operations, with the result that there is conceptual slippage in both experimental and nonexperimental research. It is argued that problems of this nature can be approached by developing specific multivariate causal models that incorporate (...) sources of measurement bias, along with the theoretical variables of interest. Many general concepts are defined in such a way that causal assumptions are built into the definitions themselves. Additionally, in any given piece of research it is necessary to omit many variables from consideration, and this is often done without careful consideration of the assumptions required to justify such omissions. Finally, generalization to more inclusive populations or a diversity of settings ordinarily requires one to replace "constants" by variables. It is concluded that the criteria of parsimony, generalizability, and precision are incompatible, given the multivariate nature of social causation, and the author expresses his own preference for sacrificing parsimony in favor of the objectives of achieving increased precision and generalizability of social science laws. (shrink)

A traditional social scientific divide concerns the centrality of the interpretation of local understandings as opposed to attending to relatively general factors in understanding human individual and group differences. We consider one of the most common social scientific variables, race, and ask how to conceive of its causal power. We suggest that any plausible attempt to model the causal effects of such constructed social roles will involve close interplay between interpretationist and more general elements. Thus, we (...) offer a case study that one cannot offer a comprehensive model of the causal power of racial categories as social constructions without careful attention both to local meanings and more general mechanisms. (shrink)

The fact that causal laws in the social sciences are most realistically expressed as both multivariate and stochastic has a number of very important implications for indirect measurement and generalizability. It becomes difficult to link theoretical definitions of general constructs in a one-to-one relationship to research operations, with the result that there is conceptual slippage in both experimental and nonexperimental research. It is argued that problems of this nature can be approached by developing specific multivariate causal models that incorporate (...) sources of measurement bias, along with the theoretical variables of interest. Many general concepts are defined in such a way that causal assumptions are built into the definitions themselves. Additionally, in any given piece of research it is necessary to omit many variables from consideration, and this is often done without careful consideration of the assumptions required to justify such omissions. Finally, generalization to more inclusive populations or a diversity of settings ordinarily requires one to replace constants by variables. It is concluded that the criteria of parsimony, generalizability, and precision are incompatible, given the multivariate nature of social causation, and the author expresses his own preference for sacrificing parsimony in favor of the objectives of achieving increased precision and generalizability of social science laws. (shrink)

American social scientists, with the possible exception of the anthropologists, have typically been ethnocentric in their writings and research. Most of their studies are simply unique to a particular institutional complex, possessing little generality beyond a single socio-cultural system. Nevertheless, social scientists nowadays are evincing increased interest in comparative studies. They are coming to realize that many of their generalizations may be found wanting when tested in the laboratory of world cultures. For the solution of many significant problems (...) cross-cultural comparison seems essential—the relationships among the variables involved must be examined under diverse cultural conditions. (shrink)

A traditional social scientific divide concerns the centrality of the interpretation of local understandings as opposed to attending to relatively general factors in understanding human individual and group differences. We consider one of the most common social scientific variables, race, and ask how to conceive of its causal power. We suggest that any plausible attempt to model the causal effects of such constructed social roles will involve close interplay between interpretationist and more general elements. Thus, we (...) offer a case study that one cannot offer a comprehensive model of the causal power of racial categories as social constructions without careful attention both to local meanings and more general mechanisms. (shrink)

Suspicion of “physics envy” surrounds the standard statistical toolbox used in the empirical sciences, from biology to psychology. Mainstream methods in these fields, various lines of criticism point out, often fall short of the basic requirements of measurement. Quantitative scales are applied to variables that can hardly be treated as measurable magnitudes, like preferences or happiness; hypotheses are tested by comparing data with conventional significance thresholds that hardly mention effect sizes. This article discusses what I call “shmeasurement.” To “shmeasure” (...) is to fail to apply quantitative tools to quantitative questions. We “shmeasure” when we try to measure what cannot be measured, or, conversely, when we ask binary questions of continuous measurements. Following the critics of standard statistical tools, it is argued that our statistical toolbox is indeed less concerned with the measurement of magnitudes than we take it to be. This article adds, however, that measurement is not all there is to scientific activity. Most techniques of proof do not resemble measurement as much as voting—a practice that makes frequent use of numbers, figures, or measurements, yet is not chiefly concerned with assessing quantities. Measurement is only one among three functions of the scientific toolbox, the other two being collating observations and deciding which hypotheses to relinquish. I thus make a plea for “shmeasurement”: the mismeasure of things starts to make more sense once we take into account the nonquantitative side of scientific practice. (shrink)

Suspicion of “physics envy” surrounds the standard statistical toolbox used in the empirical sciences, from biology to psychology. Mainstream methods in these fields, various lines of criticism point out, often fall short of the basic requirements of measurement. Quantitative scales are applied to variables that can hardly be treated as measurable magnitudes, like preferences or happiness; hypotheses are tested by comparing data with conventional significance thresholds that hardly mention effect sizes. This article discusses what I call “shmeasurement.” To “shmeasure” (...) is to fail to apply quantitative tools to quantitative questions. We “shmeasure” when we try to measure what cannot be measured, or, conversely, when we ask binary questions of continuous measurements. Following the critics of standard statistical tools, it is argued that our statistical toolbox is indeed less concerned with the measurement of magnitudes than we take it to be. This article adds, however, that measurement is not all there is to scientific activity. Most techniques of proof do not resemble measurement as much as voting—a practice that makes frequent use of numbers, figures, or measurements, yet is not chiefly concerned with assessing quantities. Measurement is only one among three functions of the scientific toolbox, the other two being collating observations and deciding which hypotheses to relinquish. I thus make a plea for “shmeasurement”: the mismeasure of things starts to make more sense once we take into account the nonquantitative side of scientific practice. (shrink)

Nietzsche distinguished between two forces in art: Apollonian, which represents order and reason, and Dionysian, which represents chaos and energy. Economists, Ward argues, have operated for too long under the assumption that their work reflects the scientific, Apollonian principals that inform physics when they simply do not apply to economics: 'constants' in economics stand in for variables, and the core scientific principles of prediction and replication are all but ignored by economists. Ward encourages economists to reintegrate the standard rigor (...) of the scientific method into their work while embracing the fact of the shape-shifting changeability of human beings. Economists can still aspire to scientific standards, as is demonstrated by the success of biology, in which there is considerable Dionysian variability. Economists must avoid the temptation to wish away dynamic complexity and diversity and must recognize, among other things, that the desire to take risks is fundamentally human. The second half of the book takes some first steps toward creating this new Dionysian Economics. (shrink)

Stipulating universal propositions with a ceteris paribus clause is normal practice in science and especially in economics. Yet there are several problems associated with the use of ceteris paribus clauses in theorising and in policy matters. This paper first investigates three questions: how can ceteris paribus clauses be non-vacuous? How can ceteris paribus laws be true? And how can they help in formulating successful policy interventions in a diversity of contexts? It turns out that ceteris paribus clauses are not (...) always used legitimately. They are meant to fence off a theory from disturbing factors, but economists who do not specify the clause well enough tend to fence variables in rather than off. In such cases, it would be better to use theoretical abstraction, which is something very different from the use of ceteris paribus clauses. However, abstract theorising conceptually leads one away from the concrete detail of real world situations in which policies take place. Hence, a fourth question arises: how can policy interventions be properly designed on the basis of abstract laws? To answer this question, I defend interdisciplinarity in concept choice. (shrink)

Palabras claves. Métodos estadísticos, pruebas de hipótesisResumen. Se presentan de forma simple, breve y por medios de los ejemplos prácticos, los métodos estadísticos que sirven para demostrar la representatividad de una, dos o varias muestras basada en los parámetros poblacionales . Se indican la manera de reducir el tamaño del error experimental para aclarar el efecto significativo de los grupos o muestras bajo el interés . Además, se demuestran la forma de eliminar el efecto de las variables auxiliares o (...) colaterales causante del ruido o error en la estadística . También se nota el uso del modelo ANOVA Anidada para indicar la forma de segmentar la ANOVA en varias partes y de esta manera poder contestar preguntas más complejas. Finalmente, se describen e explican la forma de optimizar los recursos en la conducción de los experimentos y descubrir el efecto de la interacción entre las variables .Keywords. Hypothesis testing, statistical methods. Statistical methods that serve to represent, based upon population parameters of mean and variance, for one, tow or various samples taken from study populations are discussed. Ways to reduce the amount of experimental error in order to clarify the real effect of the treatments are demonstrated . The use of Covariance Analysis to show the pure effect of treatment free from the effect of collateral variables is also indicated. Nested ANOVA that allows division of ANOVA in several parts in order to answer complex questions is described and explained. Finally, the utility of Factorial Analysis for optimization of resource use as well as the illustration of interaction effects are noted and analyzed. (shrink)

The social science approach to risk has matured over the past two decades, with distinct paradigms developing in disciplines such as anthropology, economics, geography, psychology, and sociology. Social Theories of Risk traces the intellectual origins and histories of twelve of the established and emerging paradigms from the perspective of their principal proponents. Each contributor examines the underlying assumptions of his or her paradigm, the foundational issue it seeks to address, and likely future directions of research. Taken together, (...) these essays illustrate that the principal achievement of social sciences has been to broaden the debate about risk beyond the narrow, technical considerations of engineers and the physical and life sciences. The authors conclude that expert knowledge is not value-free, that public perceptions of and attitudes toward risks vary according to a wide range of social, psychological, and cultural variables, and that public opposition to particular risks cannot be assuaged by technical fixes. The essays reveal the circuitous paths that lead people to the study of risk, highlight how these paths have crossed and discuss some of the seminal influences on individuals and the field in general. Social Theories of Risk presents a broad, retrospective view of the state of the theory in the social sciences, written by many who have been on the cutting edge of risk research since its early days. The book includes both established and novel perspectives that address the theoretical foundations of the field and reflect what we know about risk as a psychological, social, and cultural phenomenon. The collection of papers not only informs us of the tributary ideas that spawned the social studies of risk, but also how the field has matured. The biographical flavor of the essays provides fascinating reading for established members of the field, and a valuable entree for newcomers. It is an ideal college text for courses in the history of science, environmental policy, and science, technology, and society, as well as the burgeoning array of more specialized courses in risk assessment and management. (shrink)

This paper argues that research on the business case for corporate social responsibility (CSR) must account for the path dependent nature of firm-stakeholderrelations, and develops the construct of stakeholder influence capacity (SIC) to fill this void. SIC helps to explain why the effects of CSR on corporate financial performance (CFP) vary across firms and across time, therein providing a missing link in the study of the business case. This paper distinguishes CSR from related and confounded corporate resource allocations and (...) from corporate social performance (CSP), then incorporates SIC into a model that explains how acts of CSR are transformed into CFP through stakeholder relationships. This paper also develops a set of propositions to aid future research on the contingencies that produce variable financial returns to investments in CSR. (shrink)

Rendell and Whitehead state that marine ecosystems are more variable than terrestrial ecosystems over time scales of months or longer. The marine environment is actually less variable than the terrestrial at these shorter time scales, and probably equally variable over centuries. This issue is important when considering claims that environmental variability affects benefits of social learning versus individual learning and genetics.

Food safety risk is becoming a vital issue for public health, and improving public awareness of FSR through social media is necessary. This study aims to explore specific mechanisms of FSR perception; it first categorizes 19 risk characteristics into two variables, dread and efficacy, and then examines how social media use affects perceived FSR through both variables. Additionally, the study explores the moderating effects of source credibility and science literacy on the mechanisms of FSR perception. (...) Based on a nationwide online survey of more than six salient food safety issues in China, the study found that exposure to food safety risk information on social media can help improve perceived FSR based on the proposed “dread–efficacy processing model”, where dread stimulates perceived risk, while efficacy suppresses risk perception. Moreover, source credibility intensifies the effect of social media use on efficacy appraisal, whereas science literacy exerts a “double-weakening” influence on dread appraisal. Theoretical and practical implications of the findings are discussed. (shrink)

Ghost variables are variables in program languages that do not correspond to physical entities. This special issue, based on a panel on “Race as a Ghost Variable” at the 2017 Meeting of the Society for Social Studies of Science, traces ideas of “race” in particular niches of science, technology, and medicine where it is submerged and disavowed, yet wields power. Each paper is a case study exploring ghosts that emerge through the resonance among things as (...) heterogeneous as hair patterns, hormone levels, food tastes, drug use, clinic locations, proximity to disaster, job classifications, and social belonging and suspicion, all of which vibrate with meanings accumulated over long racial histories. Together, the papers further elaborate methods and analytic models for identifying the operations of race—the relations and processes that make it, the effects that it has. A chief appeal of the metaphor of the ghost is that it brings the importance of history to the fore. Ghosts are simultaneously history and the present, not just an accretion of earlier experiences, but the palimpsest left when one tries to erase them. Sometimes faint and hard to discern, sometimes rambunctious and disruptive, ghosts refuse our attempts to simply move on. (shrink)

What exactly do social scientists and biologists say when they make causal claims? This question is one of the central puzzles in philosophy of science. Alexander Reutlinger sets out to answer this question. He aims to provide a theory of causation in the special sciences (that is, a theory causation in the social sciences, the biological sciences and other higher-level sciences). According one recent prominent view, causation is that causation is intimately tied to manipulability and the possibility (...) of intervene. Reutlinger's main negative target is to argue interventionist account of causation is not adequate. Where do interventionist accounts go wrong? Reutlinger argues that the central concept of the interventionist theories – that is, the very concept of an intervention – is tremendously problematic. Reutlinger's main positive claim consists in replacing the interventionist approach by an alternative explication of causation in the special sciences, the comparative variability theory of causation. This alternative preserves many insights of the interventionist account without a commitment to the claim that causation and interventions are intimately tied together. (shrink)

In Making Science, Cole shows how social variables and cognitive variables interact in the evaluation of frontier knowledge.

Measurement is any process by which a value is assigned to the level or state of some quality of an object of study. This value is given numerical form, and measurement therefore involves the expression of information in quantities rather than by verbal statement. It provides a powerful means of reducing qualitative data to more condensed form for summarization, manipulation and analysis. The classical distinctions made by S S S Stevens between nominal, ordinal, interval and ratio measurement are a common (...) starting point for discussion of social science measurement and the use of statistical techniques. This article considers the applicability of this model to research in the social sciences, particularly sociology and political science. Differences between classical measurement theory and practice in the social sciences are discussed. Problems in social science conceptualization, operationalization and measurement are examined, and a number of issues raised. Three cases are given particular attention, the Social Indicators movement, the variable of social class, and measures of race and ethnicity. The article concludes that the 'ineluctable fuzziness' of many social science concepts is inescapable, and that social measurement remains a difficult and challenging issue. (shrink)

The goal of research in social epidemiology is not simply conceptual clarification or theoretical understanding, but more importantly it is to contribute to, and enhance the health of populations (and so, too, the people who constitute those populations). Undoubtedly, understanding how various individual risk factors such as smoking and obesity affect the health of people does contribute to this goal. However, what is distinctive of much on-going work in social epidemiology is the view that analyses making use of (...) individual-level variables is not enough. In the spirit of Durkheim and Weber, S. Leonard Syme makes this point by writing that just “as bad water and food may be harmful to our health, unhealthful forces in our society may be detrimental to our capacity to make choices and to form opinions” conducive to health and well-being. Advocates of upstream (distal) causes of adverse health outcomes propose to identify the most important of these “unhealthful forces” as the fundamental causes of adverse health outcomes. However, without a clear, theoretically precise and well-grounded understanding of the characteristics of fundamental causes, there is little hope in applying the statistical tools of the health sciences to hypotheses about fundamental causes, their outcomes, and policies intended to enhance the health of populations. This paper begins the process of characterizing the social epidemiological concept of fundamental cause in a theoretically respectable and robust way. (shrink)

We describe anytime search procedures that (1) find disjoint subsets of recorded variables for which the members of each subset are d-separated by a single common unrecorded cause, if such exists; (2) return information about the causal relations among the latent factors so identified. We prove the procedure is point-wise consistent assuming (a) the causal relations can be represented by a directed acyclic graph (DAG) satisfying the Markov Assumption and the Faithfulness Assumption; (b) unrecorded variables are not caused (...) by recorded variables; and (c) dependencies are linear. We compare the procedure with standard approaches over a variety of simulated structures and sample sizes, and illustrate its practical value with brief studies of social science data sets. Finally, we consider generalizations for non-linear systems. Keywords: latent variable models, causality, graphical models.. (shrink)

In comparative policy analysis (CPA), a generally accepted historic problem that transcends time is that of identifying common variables. Coupled with this problem is the unanswered challenge of collaboration and interdisciplinary research. Additionally, there is the problem of the rare use of text-as-data in CPA and the fact it is rarely applied, despite the potential demonstrated in other subfields. CPA is multi-disciplinary in nature, and this article explores and proposes a common variable candidate that is found in almost (if (...) not) all policies, using the science of conceptual systems (SOCS) as a pathway to investigate the structure found in policy as a lynchpin in CPA. Furthermore, the article proposes a new text-as-data approach that is less expensive, which could lead to a more accessible method for collaborative and interdisciplinary policy development. We find that the SOCS is uniquely positioned to serve in an alliance fashion in the larger qualitative comparative analysis that supports CPA. Because policies around the world are failing to reach their goals successfully, this article is expected to open a new path of inquiry in CPA, which could be used to support interdisciplinary research for knowledge of and knowledge in policy analysis. (shrink)

This paper argues that research on the business case for corporate social responsibility (CSR) must account for the path dependent nature of firm-stakeholderrelations, and develops the construct of stakeholder influence capacity (SIC) to fill this void. SIC helps to explain why the effects of CSR on corporate financial performance (CFP) vary across firms and across time, therein providing a missing link in the study of the business case. This paper distinguishes CSR from related and confounded corporate resource allocations and (...) from corporate social performance (CSP), then incorporates SIC into a model that explains how acts of CSR are transformed into CFP through stakeholder relationships. This paper also develops a set of propositions to aid future research on the contingencies that produce variable financial returns to investments in CSR. (shrink)

Abstract:This study examined the relationship between the individual difference variables of personal moral philosophy, locus of control, Machiavellianism, and just world beliefs and ethical judgments and behavioral intentions. A sample of 602 marketing practitioners participated in the study. Structural equation modeling was used to test hypothesized relationships. The results either fully or partially supported hypothesized direct effects for idealism, relativism, and Machiavellianism. Findings also suggested that Machiavellianism mediated the relationship between individual difference variables and ethical judgments/behavioral intentions.

What motives underlie the ways humans interact socially? Are these the same for all societies? Are these part of our nature, or influenced by our environments?Over the last decade, research in experimental economics has emphatically falsified the textbook representation of Homo economicus. Literally hundreds of experiments suggest that people care not only about their own material payoffs, but also about such things as fairness, equity and reciprocity. However, this research left fundamental questions unanswered: Are such social preferences stable components (...) of human nature; or, are they modulated by economic, social and cultural environments? Until now, experimental research could not address this question because virtually all subjects had been university students, and while there are cultural differences among student populations throughout the world, these differences are small compared to the full range of human social and cultural environments. A vast amount of ethnographic and historical research suggests that people's motives are influenced by economic, social, and cultural environments, yet such methods can only yield circumstantial evidence about human motives. Combining ethnographic and experimental approaches to fill this gap, this book breaks new ground in reporting the results of a large cross-cultural study aimed at determining the sources of social preferences that underlie the diversity of human sociality. The same experiments which provided evidence for social preferences among university students were performed in fifteen small-scale societies exhibiting a wide variety of social, economic and cultural conditions by experienced field researchers who had also done long-term ethnographic field work in these societies. The findings of these experiments demonstrated that no society in which experimental behaviour is consistent with the canonical model of self-interest. Indeed, results showed that the variation in behaviour is far greater than previously thought, and that the differences between societies in market integration and the importance of cooperation explain a substantial portion of this variation, which individual-level economic and demographic variables could not. Finally, the extent to which experimental play mirrors patterns of interaction found in everyday life is traced.The book starts with a succinct but substantive introduction to the use of game theory as an analytical tool and its use in the social sciences for the rigorous testing of hypotheses about fundamental aspects of social behaviour outside artificially constructed laboratories. The results of the fifteen case studies are summarized in a suggestive chapter about the scope of the project. (shrink)

We consider the use of interventions for resolving a problem of unidentified statistical models. The leading examples are from latent variable modelling, an influential statistical tool in the social sciences. We first explain the problem of statistical identifiability and contrast it with the identifiability of causal models. We then draw a parallel between the latent variable models and Bayesian networks with hidden nodes. This allows us to clarify the use of interventions for dealing with unidentified statistical models. We end (...) by discussing the philosophical and methodological import of our result. (shrink)

This is an exploratory study of corporate social performance in firms with family members in executive, governance, or strong ownership positions. Family firmsdominate the economy in most countries, including the United States, and families are thought to be more concerned with personal wealth creation and risk avoidance than social performance. Although such firms have been shown to have superior financial performance, I found no evidence of superior (or inferior) social performance among family firms in the S&P 500. (...) In a departure from the methodological norm in business and society, I used KLD data as dependent variables instead of independent variables. I was able to predict KLD scores from firm size, industry, and strategy variables, but family firm status rarely played a role. (shrink)

In the last several decades, a confluence of work in the social sciences, philosophy, statistics, and computer science has developed a theory of causal inference using directed graphs. This theory typically rests either explicitly or implicitly on two major assumptions.

. Implicit in the cognitive social learning model of personality as articulated by Walter Mischel, Albert Bandura, and others, is an epistemology which emphasizes the activity of the mind in the construction of knowledge. Using Mischel's five person variables as an outline, the epistemic implications of this model of personality are developed and then illustrated by application to William James's typology of the religious personality and to the current debate over hermeneutic and empirical approaches to studying human behavior. (...) This approach explicates the connection between personality characteristics and epistemological approaches in terms of cognitive social learning theory. (shrink)

Abstract: One approach to alignment with human values in AI and robotics is to engineer artiTicial systems isomorphic with human beings. The idea is that robots so designed may autonomously align with human values through similar developmental processes, to realize project ideal conditions through iterative interaction with social and object environments just as humans do, such as are expressed in narratives and life stories. One persistent problem with human value orientation is that different human beings champion different values as (...) ideal, meaning that the values to which an AI should be aligned are ambiguous. Prior work considered human development of purpose and source of meaning in life in terms of project ideal conditions, in effect establishing lifelong value orientations according to which intermediate situations are evaluated. The present work compares views on motivating values from St. Augustine and from popular cognitive science. These accounts are described as divergent error theories which present to their proponents as mutually exclusive yet accurate accounts of personal experience due to differential development of variable innate potentials. SpeciTically, the hypothesis proposed is that differential development of spindle neural projections establishes enduring connections between prior established relatively immediate routine processes entrained during childhood and prioritized in popular cognitive science, and later developing higher-level social and self-processes entrained during adolescence and emphasized in Augustine's account, with these projections hard-wiring lifelong motivating value orientations more or less inaccessible to modiTication through material interaction. Robot experiments informed by this study may evaluate variable value orientation by design, with for example autonomous robots developing motivating associations with temporally distal project ideal conditions through love for humanity, as described by Augustine, and others pursuing adaptive Tit to passing norms consistent with popular contemporary accounts. (shrink)

Investigation of Indigenous concepts and their meanings is highly inspirational for contemporary science because these concepts represent adaptive solutions in various environmental and social milieus. Past research has shown that conceptualizations of consciousness can vary widely between cultural groups from different geographical regions. The present study explores variability among a few of the thousands of Indigenous cultural understandings of consciousness. Indigenous concepts of consciousness are often relational and inseparable from environmental and religious concepts. Furthermore, this exploration of variability (...) reveals the layers with which some Indigenous peoples understand their conscious experience of the world. Surprisingly, Indigenous understandings of global consciousness was found not to be in opposition to local consciousness. The final concluding section of this study discusses the usability of Indigenous concepts and meanings for recent scientific debates. (shrink)

The psychology of science typically lacks integration between cognitive and social variables. We present a new framework of team innovation in multidisciplinary science and engineering groups that ties factors from both literatures together. We focus on the effects of a particularly challenging social factor, knowledge diversity, which has a history of mixed effects on creativity, most likely because those effects are mediated and moderated by cognitive and additional social variables. In addition, we highlight (...) the distinction between team innovative processes that are primarily divergent versus convergent; we propose that the social and cognitive implications are different for each, providing a possible explanation for knowledge diversity’s mixed results on team outcomes. Social variables mapped out include formal roles, communication norms, sufficient participation and information sharing, and task conflict; cognitive variables include analogy, information search, and evaluation. This framework provides a roadmap for research that aims to harness the power of multidisciplinary teams. (shrink)

As much in the processes of education of sciences like in the methodological and epistemological analyses, usually are not examples of social theories that they allow to show how they are resisted with the experience. This work tries to show not only the methodological skeleton used by E. Durkheim i..

This is the first book to explore the connections and interactions between social epistemology and epistemic relativism. The essays in the volume are organized around three distinct philosophical approaches to this topic: 1) foundational questions concerning deep disagreement, the variability of epistemic norms, and the relationship between relativism and reliabilism; 2) the role of relativistic themes in feminist social epistemology; and 3) the relationship between the sociology of knowledge, philosophy of science, and social epistemology. Recent trends (...) in social epistemology seek to rectify earlier work that conceptualized cognitive achievements primarily on the level of isolated individuals. Relativism insists that epistemic judgements or beliefs are justified or unjustified only relative to systems of standards-there is not neutral way of adjudicating between them. By bringing together these two strands of epistemology, this volume offers unique perspectives on a number of central epistemological questions. Social Epistemology and Relativism will be of interest to researchers working in epistemology, feminist philosophy, and the sociology of knowledge. (shrink)

Various laws and theories in the natural and social sciences are presented with a view to discerning the syntactic and semantic characteristics of many idealizations in science. Three different kinds of idealizations are discussed: ideal conditions, ideal cases, and idealized theories. An ideal condition is a formula in which state variables occur, whose existential closure is false, and for which there is another formula that can be constructed out of the original formula such that the existential closure (...) of the new formula is true. An ideal case is a statement which is logically equivalent to a universal conditional which has an ideal condition as its antecedent. And an idealized theory is a set of false universal conditional statements. Alternative syntactic and semantic analyses are viewed and criticized. (shrink)

This paper contributes to the underdeveloped field of experimental philosophy of science. We examine variability in the philosophical views of scientists. Using data from Toolbox Dialogue Initiative, we analyze scientists’ responses to prompts on philosophical issues (methodology, confirmation, values, reality, reductionism, and motivation for scientific research) to assess variance in the philosophical views of physical scientists, life scientists, and social and behavioral scientists. We find six prompts about which differences arose, with several more that look promising for future (...) research. We then evaluate the difference between the natural and social sciences and the challenge of interdisciplinary integration across scientific branches. (shrink)

In this paper, I investigate the study of causal mechanisms in the social sciences. I argue that unless one adopts a clear notion of causation, such as Woodward's manipulability theory of causation, one does not find evidence for causal claims. I show that adopting Woodward’s theory entails that a researcher must take into account both the observable implications of the mechanisms, and possible interventions on those mechanisms. In a backlash against the pervasiveness of statistical methods, in the last decade (...) or so social scientists have become more focused on finding the causal mechanisms behind observed correlations. To provide evidence for such causal claims, researchers often rely on process-tracing, a method which involves contrasting the observable implications of several alternative mechanisms. Although process-tracing has gained prominence as a technique, researchers do not share a fundamental framework of what causation is. I will show what process-tracers’ reasoning would look like if they were to commit to Woodward’s manipulability theory. This theory tells us that any successful explanation of an effect must refer to causal factors that could be manipulated to change the phenomenon under study. Specifically, a variable X is a cause of another variable Y if there exists some ‘intervention variable’ I. I is an intervention variable if we can use I to change X, which will then in turn change Y without any interference of other variables linked to Y. In other words, using I we will be able to ascertain that it was X that made the change in Y happen. I will argue that if a process-tracing researcher were to adopt the manipulability notion of causation, she would not only have to find observable implications of the alternative mechanisms under study, but also information regarding an intervention variable for each link of the causal chain. (shrink)

To formally understand cyclicity in innovation and to tie to Schumpeter’s idea about waves of creative destruction, we elaborate upon Thomas Kuhn’s (1962) hypothesis that science evolves through a succession of paradigm life cycles by noting that entrepreneurs recognize the profitability of new scientific theories through a delay. The delay from innovation to entrepreneurship may be due to technological inertia, the time taken in recognizing the applications of basic research, or related to how quickly technological change evolves over time (...) and its returns are realized. In our model, a profit-maximizing entrepreneur uses the latest scientific knowledge to create innovative technologies, which generates cycles between science and innovation. The necessary conditions for the existence of cycles are that human capital employed in science creation and high valued innovations is high, and the interest rate is low. The findings also tie to the notion about the variability of innovation over the business cycle and can provide useful inputs into the formulation of more effective technology policies. (shrink)

Covid data show that wealth is not health. What then are the major variables that affect public health in the Covid–19 pandemic? Based on onsite research in 26 countries across the world this paper singles out three variables – knowledge, state capability and social cooperation. If one of these is dysfunctional or absent Covid–19 performance suffers. The variables work best in combination. Under consideration are three phases of Covid–19 – virus control, vaccines, and the race with (...) variants. Which types of society best combine these variables? Comparing varieties of market economies – liberal, coordinated and state-led market economies, Covid–19 data indicate that coordinated and developmental state-led market economies tend to generate the best combination of variables and public health outcomes, and liberal market economies and rightwing populist countries produce the worst combination. Comparative Covid–19 research points to the limitations of macro theories and methodological nationalism, the importance of the unit of analysis and the database, and how variables interact. At a time when multiple crises interact it leads to reflection on glaring limitations of global governance. (shrink)

_Purpose._ The paper attempts to investigate the constructivist approach to the social world and its implications for social forecasting. _Theoretical basis._ Social forecasting is mainly based on the idea that a human is "determined ontologically". Using the methodology of the natural sciences, most predictions and forecasts fail to encompass all the multiplicity and variability of the future. The postmodern interpretation of reality gave impetus to the development of the new approaches to it. A constructivist approach to (...) class='Hi'>social reality began to compete with essentialism. Social constructivism asserts that reality is a set of mental constructs, that it is ultimately a text. Radical constructivism interprets reality as a specific system of meanings emphasizing the artifact aspects of our reality. An interpretation of the social actors’ behavior is based on the ways of understanding accepted in a given society/community and do not possess ontological universality. The creators of social space are also its creations. _Originality._ Within the framework of the postmodern approach to reality, the second-order forecasting, or forecasting of forecasting, is particularly relevant. That means that the observers-forecasters must be included in the forecast as a part of one-unified process. At this stage, a forecaster must realize that he/she is a part of a larger system, a part of the world he/she observes (and actually creates). The situation changes dramatically – the forecaster is forced to take responsibility for his/her own observations. This ultimately leads to the "humanization" of forecasting. Acting in our world full of uncertainty, unpredictability, and turbulence, modern researchers of the future should be mindful of powerful social constructs of reality. _Conclusions._ Social forecasting should be embedded in a wider context, which requires a joint effort of philosophers, foresight practitioners, historians, psychologists, sociologists, political scientists, religious scholars, anthropologists, etc. To develop promising visions and scenarios of the future, it is necessary to answer the question "Why?", which is the task of philosophically oriented research, because without this answer, we will deal with the consequences; and the implementation of the negative scenarios will reproduce itself in new socio-cultural and historical conditions. An in-depth understanding of this "Why?" provides opportunities to be in the flow of transformations. The study of the deep mental processes of the actors of social changes, the multidimensional influence on the transformation of social structures can gradually expand an answer to the question "Why?", that can cause positive changes and, accordingly, allow to create fruitful projects of the future and form effective behavioral strategies that correspond to the desired level of social development. (shrink)

This essay, written by a biologist, a microbial ecologist, a biological anthropologist, and an anthropologist‐historian, examines tensions and translations in microbiome research on animals in the laboratory and field. The authors trace how research questions and findings in the laboratory are extrapolated into the field and vice versa, and the shifting evidentiary standards that these research settings require. Showing how complexities of microbiomes challenge traditional standards of causation, the authors contend that these challenges require new approaches to inferences used in (...) ecology, anthropology, and history. As social scientists incorporate investigations of microbial life into their human studies, microbiome researchers venture into field settings to develop mechanistic understandings about the functions of complex microbial communities. These efforts generate new possibilities for cross‐fertilizations and inference frameworks to interpret microbiome findings. Microbiome research should integrate multiple scales, levels of variability, and other disciplinary approaches to tackle questions spanning conditions from the laboratory to the field. (shrink)

The study assesses how a social desirability (SD) bias influences the relationship between several independent and dependent variables commonly investigated in ethics research. The effect of a SD bias was observed when a questionnaire was administered under varying conditions of anonymity and with different measurement techniques for the SD construct. Findings reveal that a SD bias is present in the majority of relationships studied, and it most frequently plays a moderating role. While the measure of SD influences the (...) strength and type of relationship, condition of anonymity has relatively little effect on the level of SD. (shrink)

Background Voluntary post-mortem donation to science (PDS) is the most appropriate source for body dissection in medical education and training, and highly useful for biomedical research. In Mexico, unclaimed bodies are no longer a legal source, but PDS is legally possible, although scarcely facilitated, and mostly ignored by the general population. Therefore, we aimed to evaluate the attitude and willingness for PDS and to identify a sociodemographic profile of people with willingness toward PDS. Methods A validated on-line survey was (...) distributed by the convenience method via the social networks of a Catholicism-inspired, private university in northern Mexico. Frequency analyses of all variables and coded free comments were complemented with association studies. Results Although the responder cohort (n = 143) was too small and biased to be representative of the university community (n = 13,500), willingness to post-mortem organ donation was 90.7% and to PDS 70.7%. In this cohort, PDS willingness had the strongest association with mature age (> 40 years old; P, 0.0008). Among young adults, willingness to PDS was the lowest among volunteers from technical and business schools and the highest among those from the social sciences (P, 0.009). Respondents from the social sciences were also the most consistent between attitude and behavior with respect to organ donation. A free comment option revealed respondents were interested in the unusual taboo topic. Conclusions A small, but sufficiently large proportion expressed willingness toward PDS. In our university cohort, which was biased in higher education and altruism, mature age and social interest were associated with PDS willingness. (shrink)