Quantitative researchers often discuss research ethics as if specific ethical problems can be reduced to abstract normative logics (e.g., virtue ethics, utilitarianism, deontology). Such approaches overlook how values are embedded in every aspect of quantitative methods, including ‘observations,’ ‘facts,’ and notions of ‘objectivity.’ We describe how quantitative research practices, concepts, discourses, and their objects/subjects of study have always been value-laden, from the invention of statistics and probability in the 1600s to their subsequent adoption as a logic made to appear as (...) if it exists prior to, and separate from, ethics and values. This logic, which was embraced in the Academy of Management from the 1960s, casts management researchers as ethical agents who ought to know about a reality conceptualized as naturally existing in the image of statistics and probability (replete with ‘constructs’), while overlooking that S&P logic and practices, which researchers made for themselves, have an appreciable role in making the world appear this way. We introduce a different way to conceptualize reality and ethics, wherein the process of scientific inquiry itself requires an examination of its own practices and commitments. Instead of resorting to decontextualized notions of ‘rigor’ and its ‘best practices,’ quantitative researchers can adopt more purposeful ways to reason about the ethics and relevance of their methods and their science. We end by considering implications for addressing ‘post truth’ and ‘alternative facts’ problems as collective concerns, wherein it is actually the pluralistic nature of description that makes defending a collectively valuable version of reality so important and urgent. (shrink)

Combining information from two or possibly several blocks of data is gaining increased attention and importance in several areas of science and industry. Typical examples can be found in chemistry, spectroscopy, metabolomics, genomics, systems biology and sensory science. Many methods and procedures have been proposed and used in practice. The area goes under different names: data integration, data fusion, multiblock analyses, multiset analyses and a few more. This book is an attempt to give an up-to-date treatment of the most used (...) and important methods within an important branch of the area; namely methods based on so-called components or latent variables. These methods have already obtained an enormous attention in for instance chemometrics, bioinformatics, machine learning and sensometrics and have proved to be important both for prediction and interpretation. The book is primarily a description of methodologies, but most of the methods will be illustrated by examples from the above-mentioned areas. The book is written such that both users of the methods as well as method developers will hopefully find sections of interest. In the end of the book there is a description of a software package developed particularly for the book. This package is freely available in R and covers many of the methods discussed. To distinguish the different type of methods from each other, the book is divided into five parts. Part I is introduction and preliminary concepts. Part II is the core of the book containing the main unsupervised and supervised methods. Part III deals with more complex structures and, finally, Part IV discusses alternative unsupervised and supervised methods. The book ends with Part V discussing the available software. Our recommendation for reading the book are as follows. A minimum read of the book would involve chapters 1, 2, 3, 5 and 7. Chapters 4, 6 and 8 are more specialized and chapters 9 and 10 contain methods we think are more advanced or less obvious to use. We feel privileged to have so many friendly colleagues who were willing to spend their time on helping us to improve the book by reading separate chapters. We would like to express our thanks to: Rasmus Bro, Margriet Hendriks, Ulf Indahl, Henk Kiers, Ingrid MaÌ⁽ge, Federico Marini, AÌ⁽smund Rinnan, Rosaria Romano, Lars Erik Solberg, Marieke Timmerman, Oliver Tomic, Johan Westerhuis and Barry Wise. Of course, the correctness of the final text is fully our responsibility! (shrink)

There is widespread recognition at universities that a proper understanding of science is needed for all undergraduates. Good jobs are increasingly found in fields related to Science, Technology, Engineering, and Medicine, and science now enters almost all aspects of our daily lives. For these reasons, scientific literacy and an understanding of scientific methodology are a foundational part of any undergraduate education. Recipes for Science provides an accessible introduction to the main concepts and methods of scientific reasoning. With the help of (...) an array of contemporary and historical examples, definitions, visual aids, and exercises for active learning, the textbook helps to increase students’ scientific literacy. The first part of the book covers the definitive features of science: naturalism, experimentation, modeling, and the merits and shortcomings of both activities. The second part covers the main forms of inference in science: deductive, inductive, abductive, probabilistic, statistical, and causal. The book concludes with a discussion of explanation, theorizing and theory-change, and the relationship between science and society. The textbook is designed to be adaptable to a wide variety of different kinds of courses. In any of these different uses, the book helps students better navigate our scientific, 21st-century world, and it lays the foundation for more advanced undergraduate coursework in a wide variety of liberal arts and science courses. Selling Points Helps students develop scientific literacy—an essential aspect of _any_ undergraduate education in the 21 st century, including a broad understanding of scientific reasoning, methods, and concepts Written for all beginning college students: preparing science majors for more focused work in particular science; introducing the humanities’ investigations of science; and helping non-science majors become more sophisticated consumers of scientific information Provides an abundance of both contemporary and historical examples Covers reasoning strategies and norms applicable in all fields of physical, life, and social sciences, _as well as_ strategies and norms distinctive of specific sciences Includes visual aids to clarify and illustrate ideas Provides text boxes with related topics and helpful definitions of key terms, and includes a final Glossary with all key terms Includes Exercises for Active Learning at the end of each chapter, which will ensure full student engagement and mastery of the information include earlier in the chapter Provides annotated ‘For Further Reading’ sections at the end of each chapter, guiding students to the best primary and secondary sources available Offers a Companion Website, with: For Students: direct links to many of the primary sources discussed in the text, student self-check assessments, a bank of exam questions, and ideas for extended out-of-class projects For Instructors: a password-protected Teacher’s Manual, which provides student exam questions with answers, extensive lecture notes, classroom-ready Power Point presentations, and sample syllabi Extensive Curricular Development materials, helping any instructor who needs to create a Scientific Reasoning Course, ex nihilo. (shrink)

My aim in this paper is to explain how universal statements, as they occur in scientific theories, are actually tested by observational evidence, and to draw certain conclusions, on that basis, about the way in which scientific theories are tested in general. 1 But I am pursuing that aim, ambitious enough in and of itself, in the service of even more ambitious projects, and in the first place: (a) to say what is distinctive about modern science, and especially modern physical (...) science, as a human intellectual activity; and (b) to show how this distinctiveness explains the unique status of modern science in human intellectual life. So I will begin by saying a few words about that larger project. One might doubt, first, whether that project is legitimate. Although everything is different from everything else, the question “What is distinctive about X?” is not necessarily well put, because X may not be anything—that is, anything distinct. And there are indeed many philosophers, otherwise of the most diverse intellectual backgrounds and tendencies, who would deny, in various ways, that modern science is a distinct thing, or that its status is unique. It seems to me that they deny something terrifyingly obvious— a fact which confronts us far more urgently than the fact that, say, ravens are black. I will put off further remarks about this until the end of the paper, however, because the discussion of my more limited present aim will focus precisely on the ways to tell when a question is well put, and whether there is such a (distinct) thing as X. That one’s methodological problems are also the subject of one’s investigation is a sign that that investigation is philosophical, although (or because) also a threat to its coherence. Second, some points about methodology. I am not a sociologist, or even a historian, nor (unlike some recent philosophers of science) will I pretend to be.. (shrink)

These essays critically reassess the widely accepted view that statistical methods of analysis can, and do, yield causal understanding of social phenomena. They emphasize the historical, philosophical and conceptual perspectives that underlie and inform current methodological controversies.

Scientific literacy is an essential aspect of an undergraduate education. Recipes for Science responds to this need by providing an accessible introduction to the nature of science and scientific methods appropriate for any beginning college student. The book is adaptable to a wide variety of different courses, such as introductions to scientific reasoning, methods courses in scientific disciplines, science education, and philosophy of science. -/- Recipes for Science ​​was first published in 2018, and a thoroughly revised second edition was published (...) in 2024. Special features include contemporary and historical case studies from many fields of physical, life, and social sciences; visual aids to clarify and illustrate ideas; text boxes to explore related topics; plenty of exercises to support student recall and application of concepts; suggestions for further readings at the end of each chapter; a glossary with helpful definitions of key terms; and a companion website with course syllabi, PowerPoint presentations, additional exercises, and original short videos on key topics. (shrink)

This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and (...) made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

We owe most scientific knowledge to methods of inquiry that are never formally analyzed. The analysis of behavior does not call for hypothetico-deductive methods. Statistics, taught in lieu of scientific method, is incompatible with major features of much laboratory research. Squeezing significance out of ambiguous data discourages the more promising step of scrapping the experiment and starting again. As a consequence, psychologists have taken flight from the laboratory. They have fled to Real People and the human interest of “real (...) class='Hi'>life,” to Mathematical Models and the elegance of symbolic treatments, to the Inner Man and the explanatory preoccupation with inferred internal mechanisms, and to Laymanship and its appeal to “common sense.” An experimental analysis provides an alternative to these divertissements.The “theories” to which objection is raised here are not the basic assumptions essential to any scientific activity or statements that are not yet facts, but rather explanations which appeal to events taking place somewhere else, at some other level of observation, described in different terms, and measured, if at all, in different dimensions. Three types of learning theories satisfy this definition: physiological theories attempting to reduce behavior to events in the nervous system; mentalistic theories appealing to inferred inner events; and theories of the Conceptual Nervous System offered as explanatory models of behavior. It would be foolhardy to deny the achievements of such theories in the history of science. The question of whether they are necessary, however, has other implications.Experimental material in three areas illustrates the function of theory more concretely. Alternatives to behavior ratios, excitatory potentials, and so on demonstrate the utility of rate or probability of response as the basic datum in learning. Functional relations between behavior and environmental variables provide an account of why learning occurs. Activities such as preferring, choosing, discriminating, and matching can be dealt with solely in terms of behavior, without referring to processes in another dimensional system. The experiments are not offered as demonstrating that theories are not necessary but to suggest an alternative. Theory is possible in another sense. Beyond the collection of uniform relationships lies the need for a formal representation of the data reduced to a minimal number of terms. A theoretical construction may yield greater generality than any assemblage of facts; such a construction will not refer to another dimensional system. (shrink)

This second edition of Life Science Ethics includes four essays not found in the first edition: Richard Haynes on “Animals in Research” Stephen M. Gardiner on “Climate Change” Christopher Kelty on “Nanotechnology” Gary Comstock on “Genetically Modified Foods” and a revised and expanded version of the chapter on “Farms” in which Stephen Carpenter joins Charles Taliaferro as author. In addition, Part III has been thoroughly revised with the goal of focusing attention on salient examples. Three new case studies have (...) been added: Robert Streiffer and Sara Gavrell Ortiz on “Enviropigs” Donald F. Boesch, et al. on “Coastal Dead Zones” Deb Bennett-Woods on “Nanotechnology and Human Enhancement” The first edition was praised for providing instructors with a stimulating text that will help students hone their critical thinking skills. That text is here enhanced with treatments of critical new issues, including global warming, nanotechnology, and the possibility that bioengineering may be able to change human nature. The new edition includes classroom discussion questions for use in provoking and guiding in-class discussions. Part I introduces ethics, the relationship of religion to ethics, how we assess ethical arguments, and a method ethicists use to reason about ethical theories. Part II demonstrates the relevance of ethical reasoning to the environment, land, farms, food, biotechnology, genetically modified foods, animals in agriculture and research, climate change, and nanotechnology. Part III presents case studies for the topics found in Part II. Two appendices include exercises to help students learn systematic ways of thinking through ethical dilemmas and notes for instructors using the book as a text. (shrink)

Science and language; Axioms; Deduction and induction; Probability and statistics; The methodological structure of the natural sciences.

The author finds no support for the claim that J. M. Keynes had severe reservations, in general, as opposed to particular, concerning the application of mathematical, logical and statistical methods in economics. These misinterpretations rest on the omission of important source material as well as a severe misconstrual ofThe Treatise on Probability (1921).

In this paper, I examine William Whewell’s (1794–1866) ‘Discoverer’s Induction’, and argue that it 21 supplies a strikingly accurate characterization of the logic behind many statistical methods, exploratory 22 data analysis (EDA) in particular. Such methods are additionally well-suited as a point of evaluation of 23 Whewell’s philosophy since the central techniques of EDA were not invented until after Whewell’s death, 24 and so couldn’t have influenced his views. The fact that the quantitative details of some very general 25 (...) methods designed to suggest hypotheses would so closely resemble Whewell’s views of how theories 26 are formed is, I suggest, a strongly positive comment on these views. (shrink)

The application of statistical methods and models both in the natural and social sciences is nowadays a trivial fact which nobody would deny. Bold analogies even suggest the application of the same statistical models to fields as different as statistical mechanics and economics, among them the case of the young and controversial discipline of Econophysics . Less trivial, however, is the answer to the philosophical question, which has been raised ever since the possibility of “commuting” (...) class='Hi'>statistical thinking and models between natural and social sciences emerged: whether such a methodological kinship would imply some kind of more profound unity of the natural and the social domain. Starting with Adolphe Quetelet (1796-1874) and ending with the Vienna Circle (from the late 1920s until the 1940s), this paper offers a brief historical and philosophical reconstruction of some important stages in the development of statistics as “commuting” between the natural and the social sciences. This reconstruction is meant to highlight (with respect to the authors under consideration): (1) the existence of a significant correlation between the readiness to “transfer” statistical thinking from natural to social sciences and vice versa, on the one hand, and the standpoints on the issue of the unity/disunity of science, on the other; (2) the historical roots and the fortunes of the analogy between statistical models of society and statistical models of gases. (shrink)

As with much contemporary philosophical and scientific research, the predominant metaphysics of situatedness is monism, particularly, physicalism. Here, we claim that while monism is the proper metaphysical thesis, empirically-supported theories of situated phenomena require ontological pluralism as well. We defend this position via the example of bird flocks, which are situated systems that exhibit ontologically plural features, namely, component dominance and interaction dominance. The description of these features will illustrate that understanding these phenomena requires a coevolution of conceptual and methodological (...) development. Specifically, ontological features are partially identified and evaluated by way of the analyses applied to them. Both descriptive and normative lessons are drawn. Descriptively, research on bird flocks demonstrate that natural phenomena may not be readily cast via a monistic ontology (e.g., component dominant), even at the same scale of investigation. The normative consequence is that while research on situated systems need not reject metaphysical monism, it ought to begin from a pluralistic position concerning ontology. (shrink)

Certain characteristics make machine learning a powerful tool for processing large amounts of data, and also particularly unsuitable for explanatory purposes. There are worries that its increasing use in science may sideline the explanatory goals of research. We analyze the key characteristics of ML that might have implications for the future directions in scientific research: epistemic opacity and the ‘theory-agnostic’ modeling. These characteristics are further analyzed in a comparison of ML with the traditional statistical methods, in order to demonstrate (...) what it is specifically that makes ML methodology substantially unsuitable for reaching explanations. The analysis is given broader philosophical context by connecting it with the views on the role of prediction and explanation in science, their relationship, and the value of explanation. We proceed to show, first, that ML disrupts the relationship between prediction and explanation commonly understood as a functional relationship. Then we show that the value of explanation is not exhausted in purely predictive functions, but rather has a ubiquitously recognized value for both science and everyday life. We then invoke two hypothetical scenarios with different degrees of automatization of science, which help test our intuitions on the role of explanation in science. The main question we address is whether ML will reorient or otherwise impact our standard explanatory practice. We conclude with a prognosis that ML would diversify science into purely predictively oriented research based on ML-like techniques and, on the other hand, remaining faithful to anthropocentric research focused on the search for explanation. (shrink)

BackgroundThe experience sampling method is an increasingly popular data collection method to assess interpersonal dynamics in everyday life and emotions contextualized in real-world settings. As primary advantages of ESM sampling strategies include minimization of memory biases, maximization of ecological validity, and hypothesis testing at the between- and within-person levels, ESM is suggested to be appropriate for studying the daily lives of educational actors. However, ESM appears to be underutilized in education research. We, thus, aimed to systematically evaluate the methodological (...) characteristics and quality of published ESM studies of social interactions among children and adolescents in school settings, as well as to explore how much variance in social interaction variables could be attributed to the within-person level.MethodUsing Academic Search Complete, APA PsycINFO, APA PsycArticles, ProQuest, Web of Science, Wiley Online Library, and SAGE Journals, and in accordance with PRISMA guidelines and pre-defined eligibility criteria, we conducted a systematic literature search of experience sampling studies up to November 2020. To assess methodological quality, we used a modified checklist for reporting of ESM studies.ResultsOf the originally 2 413 identified studies, a final 52 experience sampling studies were included in the present review. Findings on sample and study design characteristics generally revealed wide variability. Even if high-quality studies were associated with higher scores on the training of participants in using the ESM procedure, and use of incentives, these design strategies did not reveal a statistically significant impact on compliance. The intraclass correlation coefficient was reported in nine studies and on average 58% of the variance in social interaction variables could be attributed to within-person fluctuation between timepoints.ConclusionThe current study is the first to systematically review ESM-based studies on social interactions among children and adolescents in the school context. These observations suggest that ESM is a potentially favorable technique for extracting complex social phenomena in real-world settings. We hope that this review will contribute to improving the quality assessment of ESM studies as well as to inform and guide future experience sampling studies, particularly regarding social phenomena with children and adolescents in educational settings. (shrink)

BackgroundEthics is the science of moral and ethical rules recognised in human life and attempts to verify what is morally right and wrong. Healthcare ethics is seen as an integrated part of the daily activities of health facilities. Healthcare professionals’ standardisation and uniformity in healthcare ethics are urgent and basic requirements. Therefore, this study aimed to assess the practice of the code of ethics and associated factors among health professionals in Central Gondar Zone public hospitals, Northwest Ethiopia, 2021.MethodsA facility-based (...) cross-sectional study design with a mixed method was conducted on 631 health professionals from Central Gondar Zone public hospitals. For the quantitative part, pre-tested self-administered questionnaires were used, and for the qualitative part, key informant interviews with a semi-structured questionnaire were used. Variables with a p value of < 0.2 in binary logistic regression entered into a multivariable logistic regression, then p value < 0.05 and AOR were used to declare statistically significant variables in quantitative data. A thematic content analysis was used for qualitative data analysis.ResultsThis study revealed that only 286 health professionals had good practice of the code of ethics. Good ethical knowledge, favourable attitude, and satisfaction of health professionals with their jobs were significantly associated with the practice of health care ethics.ConclusionsHealth professionals' overall level of practice of health care ethics in the Central Gondar Zone public hospitals was poor. This necessitates practical training, ongoing follow-up, availing of necessary medical equipment, a smooth working environment, and modification of the recognition system for health professionals. (shrink)

Any serious attempt to give an account of the cognitive aspect of science – as contrasted with e.g. its social or cultural aspects – cannot ignore the automation revolution. In the conception presented in this paper the results of computer science are taken seriously and integrated with many of the ideas concerning what constitutes scientific inquiry that have been proposed at least since the early Middle Ages. The central idea is that of reliable inquiry. Science makes explicit and elaborates on (...) the methods of acquiring beliefs in our daily life. The central question a scientific method applied to inquiry needs to face is if it is reliable in getting to the truth. On the reliabilist criteria presented here, if a method is logically warranted to get to the right answer – given data and background knowledge available – and to stick to it afterwards, then it is reliable. This is a normative theory, but the standard of reliability is adjusted to the domain of the inquiry at hand. This paper presents the central tenets of the reliabilist conception of science and briefly outlines the main results underlying it. Roughly, the aim of science is interesting truth about the world around us (scientific realism) and reliabilist epistemology affords us precise answers as to how far science can succeed in this task – given the methods, goals and background assumptions available. The philosophical task to deliver an adequate understanding of science is taken to be continuous with scientific research itself (naturalism), a major part of which is concerned with delivering causal explanations (causality) and can only be carried out with limited resources (computability). Many of the ideas integrated into the reliabilist conception of science and precisely articulated therewith have appeared earlier in both philosophy and science (history of ideas). I conclude the exposition of the ideas integrated into the reliabilist conception of science with discussions of sample case studies where the reliabilist conception of science has been applied to actual scientific research. For obvious reasons none of the grand conceptions of science from the distant past is adequate. Towards the end of this paper I give some substance to the claim that among the few contemporary conceptions of science reliabilist epistemology is the the most comprehensive account. For only it systematically elaborates the ideas of reliability and computability accompanying science from its inception. None of the past or contemporary alternatives to a thoroughly revised understanding of science offered by the reliabilist approach can embrace the recent outburst of new sciences such as computer science, Bayesian statistics and cognitive science. An outline of open problems and directions for future research concludes the paper. (shrink)

Empirical bioethics is commonly understood as integrating empirical research with normative-ethical research in order to address an ethical issue. Methodological analyses in empirical bioethics mainly focus on the integration of socio-empirical sciences and normative ethics. But while there are numerous multidisciplinary research projects combining life sciences and normative ethics, there is few explicit methodological reflection on how to integrate both fields, or about the goals and rationales of such interdisciplinary cooperation. In this paper we will review some (...) drivers for the tendency of empirical bioethics methodologies to focus on the collaboration of normative ethics with particularly social sciences. Subsequently, we argue that the ends of empirical bioethics, not the empirical methods, are decisive for the question of which empirical disciplines can contribute to empirical bioethics in a meaningful way. Using already existing types of research integration as a springboard, five possible types of research which encompass life sciences and normative analysis will illustrate how such cooperation can be conceptualized from a methodological perspective within empirical bioethics. We will conclude with a reflection on the limitations and challenges of empirical bioethics research that integrates life sciences. (shrink)

In the contemporary life sciences more and more researchers emphasize the “limits of reductionism” (e.g. Ahn et al. 2006a, 709; Mazzocchi 2008, 10) or they call for a move “beyond reductionism” (Gallagher/Appenzeller 1999, 79). However, it is far from clear what exactly they argue for and what the envisioned limits of reductionism are. In this paper I claim that the current discussions about reductionism in the life sciences, which focus on methodological and explanatory issues, leave the (...) concepts of a reductive method and a reductive explanation too unspecified. In order to fill this gap and to clarify what the limits of reductionism are I identify three reductive methods that are crucial in the current practice of the life sciences: decomposition, focusing on internal factors, and studying parts in isolation. Furthermore, I argue that reductive explanations in the life sciences exhibit three characteristics: first, they refer only to factors at a lower level than the phenomenon at issue, second, they focus on internal factors and thus ignore or simplify the environment of a system, and, third, they cite only the parts of a system in isolation. (shrink)

The role of Alfred Kinsey, America's most influential sexologist, in the cultural revolution of sex and gender during the past fifty years remains as unquestionable as it has been controversial. This admiring biography argues that Kinsey also qualifies as an authentic great man of science in the tradition of Darwin. Kinsey's expert authority was recently challenged by James Jones, who claimed in his 1997 biography that Kinsey's terrible personal secrets—homosexuality and masochism—plagued his life and ruined his science. Jonathan Gathorne‐Hardy (...) sets out to repair Kinsey's reputation by defending him against this “Kenneth Starr school of biography” . The author seeks to rescue Kinsey's achievement from the stigmatizing charge that it was flawed because it subordinated science to subjectivity.Gathorne‐Hardy emphasizes Kinsey's methodological creativity and his interviewing genius. During his early career, when he worked on gall wasps, Kinsey's science developed as a practice of scrupulous collection, observation, and documentation. Even in graduate school, he was dubbed “get a million Kinsey,” and his belief in sheer quantity—as well as quantification—was just as apparent when he turned his attention to human sexuality. In 1938 Kinsey taught a course on marriage at Indiana University, where he spent his entire working life. Limited to married or engaged students and faculty, the course covered reproductive physiology, contraception, and a host of other sexual topics in explicit detail. Kinsey also used the course to gather data about his students' sex lives. The thousands of sexual histories collected at the Institute for Sex Research in later years—7,985 by Kinsey alone—attest to his scientific commitment to behavior as the only legitimate basis for a science of sex.The behavioral unit of analysis chosen by Kinsey was the orgasm—or “outlet,” as Kinsey called it. Because it was countable, the theory went, it was objective. Kinsey's ethic of measurement resulted in interviews involving at least 350 standard questions, whose answers were recorded in a custom code designed to fit on a single sheet of paper divided into 287 squares. Among the ironies of Kinsey's method was the fact that his sex histories measured linguistic rather than sexual behavior. What Kinsey actually compiled was a huge cache of stories, not direct observations of sexual behavior. Kinsey, who gathered more sexual stories than any other person alive, systematically aimed to eradicate all quirks and complexities in order to produce a statistical portrait of population‐wide behavior. Meanings might be historically important, but numbers, not narratives, would yield truth. The easy use of “human males” and “human females” in the titles of Kinsey's famous reports suggests how universal his scientific claims were—and also how devoid of temporal and cultural particularity.The resulting conception of human sexual nature is probably best represented in Kinsey's six‐point scale, where behavioral possibilities ranged from exclusively homosexual at one pole to exclusively heterosexual at the other. Diversity emerged as the premier fact about sexual behavior. While this placed men and women uncomfortably close to their primate cousins on an evolutionary map, making human sexual exceptionalism objectively unsustainable, it also produced a reformist sensibility that rooted its demand for toleration in the powerful evidence of natural facts. It is difficult to overstate how shocking Kinsey's picture of polymorphous sexuality was in a culture devoted to either/or binaries and prone to harsh judgments about deviation from norms. Kinsey's contribution was to point out the gap between ideology and behavior . That lots of people did lots of things at odds with professed sexual morality was, for some, a welcome relief and call to revolution. For others, it was a reason to hate Kinsey and blame him for changes in the realm of gender and sexuality already well under way by midcentury.No biographies can save scientific heroes from the fatal charge that their methods and findings were bound up in their lives, or they would not be biographies worth reading. This attests to the stubborn endurance of the psychoanalytic paradigm. Kinsey despised Freud for passing off philosophy as science. Yet because of the conventions of post‐Freudian biography, Gathorne‐Hardy must explore exactly those dimensions of Kinsey's life and character that Freud embraced but that Kinsey himself would never have admitted into the precincts of science. His childhood illnesses and struggles with an overbearing father, his rage against religion, fondness for music, charismatic yet autocratic style, and his own anguished sexuality are keys to puzzling out not only a life in science, but a life.Gathorne‐Hardy can hardly ignore evidence that Kinsey's own sexual appetites were diverse—“bisexual” is this author's preferred designation—or that his enterprise in sex research involved experimentation: the mostly married male members of Kinsey's team were expected to engage in sexual activities with one another and one another's wives. Kinsey's wife Clara was a confidant and supporter from the start. Their loving marriage was also an open marriage. Mac was a participant‐observer in the world of sex research. She had a series of affairs with Kinsey's colleagues and even changed the bedsheets during energetic sessions of sexual cinematography that took place in the attic of their home. Yet the Kinseys also shielded their children from their own unorthodox sexual practices.This biography concludes by suggesting that Kinsey died tragically in 1957, convinced that his enemies had the upper hand. Kinsey was wrong. The diversity he championed has become a theoretical staple in the human and life sciences as well as a practical goal in social policies related to gender, race, and sexuality. However unfinished it may be, it is difficult to imagine Kinsey's revolution being reversed in either science or society. (shrink)

Newton’s impact on Enlightenment natural philosophy has been studied at great length, in its experimental, methodological and ideological ramifications. One aspect that has received fairly little attention is the role Newtonian “analogies” played in the formulation of new conceptual schemes in physiology, medicine, and life science as a whole. So-called ‘medical Newtonians’ like Pitcairne and Keill have been studied; but they were engaged in a more literal project of directly transposing, or seeking to transpose, Newtonian laws into quantitative models (...) of the body. I am interested here in something different: neither the metaphysical reading of Newton, nor direct empirical transpositions, but rather, a more heuristic, empiricist construction of Newtonian analogies. Figures such as Haller, Barthez, and Blumenbach constructed analogies between the method of celestial mechanics and the method of physiology. In celestial mechanics, they held, an unknown entity such as gravity is posited and used to mathematically link sets of determinate physical phenomena (e.g., the phases of the moon and tides). This process allows one to remain agnostic about the ontological status of the unknown entity, as long as the two linked sets of phenomena are represented adequately. Haller et. al. held that the Newtonian physician and physiologist can similarly posit an unknown called ‘life’ and use it to link various other phenomena, from digestion to sensation and the functioning of the glands. These phenomena consequently appear as interconnected, goal-oriented processes which do not exist either in an inanimate mechanism or in a corpse. In keeping with the empiricist roots of the analogy, however, no ontological claims are made about the nature of this vital principle, and no attempts are made to directly causally connect such a principle and observable phenomena. The role of the “Newtonian analogy” thus brings together diverse schools of thought, and cuts across a surprising variety of programs, models and practices in natural philosophy. (shrink)

This paper challenges the common assumption that some phenotypic traits are quantitative while others are qualitative. The distinction between these two kinds of traits is widely influential in biological and biomedical research as well as in scientific education and communication. This is probably due to both historical and epistemological reasons. However, the quantitative/qualitative distinction involves a variety of simplifications on the genetic causes of phenotypic variability and on the development of complex traits. Here, I examine three cases from the (...) class='Hi'>life sciences that show inconsistencies in the distinction: Mendelian traits, Mendelian diseases, and polygenic mental disorders. I show that these traits can be framed both quantitatively and qualitatively depending, for instance, on the methods through which they are investigated and on specific epistemic purposes. This suggests that the received view of quantitative and qualitative traits has a limited heuristic power—limited to some local contexts or to the specific methodologies adopted. Throughout the paper, I provide directions for framing phenotypes beyond the quantitative/qualitative distinction. I conclude by pointing at the necessity of developing a principled characterisation of what phenotypic traits, in general, are. (shrink)

Over the course of the last three decades, computer simulations have become a major tool of doing science and engaging with the world, not least in an effort to predict and intervene in a future to come. Born in the context of the Second World War and the discipline of physics, simulations have long spread into most diverse fields of enquiry and technological application. This paper introduces a topical collection focussing on simulations in the life sciences. Echoing the (...) current state of tinkering, fast developments, segmentation of knowledge and interdisciplinary collaboration, and in an effort to bridge the science-humanities divide, the contributors to this collection come from multiple disciplinary backgrounds, including information studies, cognitive sciences, philosophy and biology. The ambiguous character of simulations, their cutting across scientific disciplines, analysis and prediction, understanding and doing, gave rise to their success in contemporary life sciences and has been the object of much scientific debate. One of the main aims of this topical collection, by contrast, is to call into question the assumption of an obvious use and easy transfer of methods between fields of knowledge as diverse as, e.g. physics and biology. The collection presents historical case studies from various biological sub-fields. The articles study how simulations are used and the ways they contribute specifically to our understanding of life. Taking up Sergio Sismondo’s description of simulations as “compromises” and “glue”, they also critically engage with the question of what exactly the life sciences have been gluing together over the last two decades. (shrink)

The autobiography of one of the most versatile of American scientists of his generation, the first to be trained largely in his own country. A scientific generalist, Morse has made significant contributions to atomic physics, quantum mechanics, plasma physics, astrophysics, acoustics, machine computation, and operations research. Philip Morse has surely been one of the most versatile of American scientists of his generation, the first to be trained largely in his own country. A scientific generalist, he has made significant contributions to (...) atomic physics, quantum mechanics, plasma physics, astrophysics, acoustics, machine computation, and operations research. His life-long commitment to teaching, through his authorship of a series if standard-setting textbooks and through his personal guidance of unnumbered individual students, has extended this scope to include thermodynamics, statistical mechanics, and the methods of theoretical physics as well. Moreover, as this autobiography relates at a fast-moving pace, Morse has also been involved in the high-pressure concerns of war research, scientific administration and consultation, policy formation, the education of key groups and wider publics beyond the classroom, and the real-world utilization of scientific techniques and discoveries. For all these accomplishments, Morse writes that his experience as a scientist and as a participant in the affairs of his time "has been at the second, rather than at the top, level." It may be that this circumstance of being neat, rather than at, the top makes this autobiography more, rather than less, relevant to other and younger scientists, to those considering a life in science, and to general readers curious as to what such a life is really like. Only a miniscule few reach, say. Einsteinian levels, and their lives and work tend to be unique unto themselves; what Morse reports is truer to the experience of the great majority of the members of the scientific community. While his actual accomplishments, his range, and his eminence certainly far exceed those of a "typical" scientist, they do so more in degree than in kind. Morse's style is straightforward and nontechnical, direct, and personal. Some of the lighter moments and revealingly human incidents of his experience are recorded along with the problems and breakthroughs in the near-private world of pure science and the public worlds of policy, high-level consultation, and practical applications. (shrink)

Background Biomedicine, i.e. the application of basic sciences to medicine, has become the cornerstone for the study of etiopathogenesis and treatment of diseases. Biomedicine has enormously contributed to the progress of medicine and healthcare and has become the preferred approach to medical problems in the West. The developments in statistical inference and machine learning techniques have provided the foundation for personalised medicine where clinical management can be fully informed by biomedicine. The deployment of precision medicine may impact the (...) autonomy and self-normativity of the patients. Understanding the relationship between biomedicine and medical practice can help navigate the benefits and challenges offered by precision medicine. Methods Conventional content analysis was applied to “Le Normal and le Pathologique” (Canguilhem G. The Normal and the Pathological. Princeton: Princeton University Press; 1991) and further investigated with respect to its relationship with techne and precision medicine using PubMed and Google Scholar and the Standford Encyclopedia of Philosophy to search for the following keywords singularly or in combination: “Canguilhem”, “techne”, “episteme”, “precision medicine”, “machine learning AND medicine”. Results The Hippocratic concept of techne accounts for many characteristics of medical knowledge and practice. The advances of biomedicine, experimental medicine and, more recently, machine learning offer, in contrast, the model of a medicine based purely on episteme. I argue that Canguilhem medical epistemology establishes a framework where episteme and data-driven medicine is compatible with the promotion of patient’s autonomy and self-normativity. Conclusions Canguilhem’s medical epistemology orders the relationship of applied medicine with experimental sciences, ethics and social sciences. It provides guidance to define the scope of medicine and the boundaries of medicalization of healthy life. Finally, it sets an agenda for a safe implementation of machine learning in medicine. (shrink)

Individuals’ beliefs, as well as their spiritual orientations (SOs), can affect the quality of their work life cycle. Given that a large portion of people’s lives are spent in organisations, it is crucial to consider the factors affecting quality of work life (QWL) among employees. Against this background, the present study investigated the effects of the Islam-based SOs on the QWL in Muslim employees working for Iraqi municipalities in 2022. For this purpose, an applied research design was adopted, (...) using field studies of the correlational type for data collection. In total, 1345 staff of Iraqi municipalities were selected by simple random sampling in 2022, and two standardised questionnaires were utilised to collect the data. The content validity method was further recruited to determine the validity of the questionnaires, and the Cronbach’s alpha coefficient was used to measure the reliability. To analyse the data, descriptive tests, including frequency, mean and standard deviation (SD), along with inferential statistics, namely one-sample t-test, one-way analysis of variance (ANOVA) and independent-samples t-test, were implemented using the Statistical Package for the Social Sciences (SPSS) software package. The correlation coefficients accordingly showed a rising trend in the QWL among these employees following the growth in their SOs. Moreover, there was a significant relationship between the components of SOs, namely spiritual beliefs, sense of spirituality, spiritual self-actualisation and spiritual practices, and the QWL of the Muslim employees.Contribution: This study revealed that the increase in the Islam-based SOs and its components led to an increase in the QWL of Iraqi Muslim employees. (shrink)