Applying the Psychology of Science to the Science of Psychology: Can Psychologists Use Psychological Science to Enhance Psychology as a Science?

ABSTRACT— Added to the already tremendous diversity of subdisciplines of psychological science is the psychology of science. Although research on the psychology of science began in 1874, the field has seen a substantial expansion of activity in recent years. One particular subset of this research literature has special importance: namely, inquiries into the psychology of doing great science. These investigations may be assigned into four groups: cognitive, differential, developmental, and social. Each of these deal with critical questions that can, if answered, contribute directly to the improvement of psychology as a science. Potential applications include (a) the identification of scientific talent in psychology, (b) the education of future investigators in psychological science, and (c) the evaluation of psychology's progress as a scientific endeavor.     

And the Winner is… Awards for the Integration of Science and Practice in Psychology

Psychotherapists from all fields perform difficult and challenging work, trying to help their clients gain insight into their problems and make lasting changes in their thoughts and behaviors. Unfortunately, too often the work of a psychotherapist is minimized, neglected, or disregarded. Where departmental or conference awards may be presented regularly, public recognition for evidence-based and clinically-relevant published work is lacking. The present paper aims to acknowledge the most valuable recent accomplishments in the field of mental health assessment and treatment. Nominations were accepted for works published during 2017, papers of enduring value, and most valuable psychologist, and votes were cast by a panel of judges. These valuable contributions are recommended for all psychotherapists who hope to improve their work with clients.     

What is the Thematic Structure of Science?

The paper justifies the concept of “thematic structure” or “order of knowledge” over the traditional “classification of sciences” due to the uncertainty of many classification criteria. The thematic structure of science has, of course, various levels and various dimensions. Arguments against any forms of separating the humanities from sciences in the traditional sense of the term are presented and discussed. Equally unacceptable are attempts at sharp separation of technical disciplines and humanities. The thematic structure of humanities is not created by some material aspects but rather through the interest — or problem-oriented aspects. In addition to the natural sciences and the humanities there exists an important sphere of sciences on artefacts or, using the term by H. Simon, the sciences of the artificial. For the contemporary research activities is typical what could be denoted as “interdisciplinary or multidisciplinary complex.” The paper traces a set of epistemological criteria for the justification of the relative independence of a scientific discipline. This revised version was published online in August 2006 with corrections to the Cover Date.     

The Regression Trap and Other Pitfalls of Replication Science—Illustrated by the Report of the Open Science Collaboration

The Open Science Collaboration’s 2015 Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349, aac4716. doi:10.1126/science.aac4716[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] report suggests that replication effect sizes in psychology are modest. However, closer inspection reveals serious problems. When plotting replication effects are against original effects, the regression trap is lurking: Expecting replication effects to be equally strong as original effects is logically unwarranted; they are inevitably subject to regressive shrinkage. To control for regression, the reliability of original and replication studies must be taken into account. Further problems arise from missing manipulation checks and sampling biases. Our critical comment highlights the need for replication science to live up to the same methodological scrutiny as other research.     

From the Characterization of ‘European Philosophy of Science’ to the Case of Philosophy of the Social Sciences

How distinct is European philosophy of science? The first step is to characterize what is or might be considered as ‘European philosophy of science’. The second is to analyse philosophy of the social sciences as a relevant case in the European contribution to philosophy of science. (1) ‘European perspective’ requires some clarification, which can be done from two main angles: the historical approach and the thematic view. Thus, there are several structural and dynamic things to be considered in European philosophy of science and compare with other conceptions: (i) the topics discussed; (ii) the contents proposed; and (iii) the style of thought used. (2) The case of philosophy of the social sciences is relevant for the historical approach and for the thematic view. Historically, the Erklären–Verstehen methodological controversy arose in this continent, where the main authors and most of the influential approaches are located. Thematically, we can consider the contributions made by these European approaches to philosophy of the social sciences. They give us some distinctive features of European philosophy of science.     

Science as a Vocation in the Era of Big Data: the Philosophy of Science behind Big Data and humanity’s Continued Part in Science

We now live in the era of big data, and according to its proponents, big data is poised to change science as we know it. Claims of having no theory and no ideology are made, and there is an assumption that the results of big data are trustworthy because it is considered free from human judgement, which is often considered inextricably linked with human error. These two claims lead to the idea that big data is the source of better scientific knowledge, through more objectivity, more data, and better analysis. In this paper I analyse the philosophy of science behind big data and make the claim that the death of many traditional sciences, and the human scientist, is much exaggerated. The philosophy of science of big data means that there are certain things big data does very well, and some things that it cannot do. I argue that humans will still be needed for mediating and creating theory, and for providing the legitimacy and values science needs as a normative social enterprise.     

Kierkegaard and Psychology as the Science of the “Multifarious Life”

The aim of this paper is to demonstrate the actuality of some considerations around psychology made by the Danish philosopher Søren Kierkegaard (1813–1855). According to him psychology is about the “multifarious” life, which is a term that pinpoints the challenges psychology still have when it comes to including changes and genetic perspectives on its understanding of actual living. Yet Kierkegaard discusses psychology in relationship to metaphysics, which is an almost forgotten perspective. His understanding opens up for narrowing the definition of psychology down to the science of subjectivity, which at the same time elevates psychology to being the only science that focuses on the actual human life. Yet Kierkegaard’s most important contribution to psychology is to maintain a radical distinction between subjectivity and objectivity, and in this respect the psychology of today is challenged.     

A Critical Assessment of the Programmes of Producing ‘Islamic Science’ and ‘Islamisation of Science/Knowledge’

In the present article, working from within the framework of critical rationalism and focusing mostly on the views developed by some Iranian writers, I argue that the programmes of producing ‘Islamic Science’ (cIS) and ‘Islamisation of Science/Knowledge’ (IoK) are doomed to failure. I develop my arguments in three parts. I start by explaining that the advocates of the programmes of producing cIS or IoK subscribe to mistaken images of science that are shaped by either a positivist or outmoded culturalist/interpretivist theories of science. I shall then focus on the similarities and differences of ‘science’ and ‘technology’, arguing that despite close interconnection between the two it is of utmost importance, for analytical purposes, to keep these two socially constructed entities apart. Drawing on the above distinction, I argue that while creating ‘Islamic’ or ‘indigenous’ sciences is impossible, constructing ‘Islamic’ or ‘indigenous’ technologies is, in principle, feasible. Lastly, I turn to some of the more recent works on creating/constructing cIS and/or IoK. I shall try to show that none of the arguments introduced by the advocates of the projects of cIS/IoK is tenable.     

Ethics and Science: Is Plausibility in the Eye of the Beholder?

This paper argues that morality is objective in a specific sense that accords with a broadly expressivist stance in metaethics. The paper also explains that although there is a kind of subjectivity in moral inquiry, the same holds for other kinds of normative inquiry, including epistemic and even scientific inquiry, and moreover that this kind of subjectivity is no threat to morality’s objectivity. The argument for the objectivity of morality draws strong parallels between ethics, epistemology, and science, but does not depend on equally strong parallels between ethics and mathematics. I argue that there is more to learn from a comparison between ethics and mathematics than I used to think, but the difference between the issues that come up in thinking about objectivity in ethics and those that come up in thinking about objectivity in mathematics is substantial, and we cannot carry over results from the philosophy of mathematics to the case of morality.     

Still Fighting the “War for Talent”? Bridging the Science Versus Practice Gap

The purpose of this article is to identify some the most critical outstanding issues faced by practitioners in undertaking effective talent management. In spite of the global financial crisis, talent management will continue being one of the most important challenges faced by organizations in the coming decade. Workforce demographics and skills shortages are likely to make the “war for talent” fiercer than ever before making effective talent management a competitive necessity. While talent management is rapidly developing as a research field, there are many areas and questions that need to be explored. These questions are likely to have a particularly important applied benefit as they represent some of the key challenges organizations are grappling with in effectively managing their talent. The article asks researchers in the field to consider the questions proposed in developing future research agendas.     

Polytomous Latent Scales for the Investigation of the Ordering of Items

We propose three latent scales within the framework of nonparametric item response theory for polytomously scored items. Latent scales are models that imply an invariant item ordering, meaning that the order of the items is the same for each measurement value on the latent scale. This ordering property may be important in, for example, intelligence testing and person-fit analysis. We derive observable properties of the three latent scales that can each be used to investigate in real data whether the particular model adequately describes the data. We also propose a methodology for analyzing test data in an effort to find support for a latent scale, and we use two real-data examples to illustrate the practical use of this methodology.     

That’s Not Science! The Role of Moral Philosophy in the Science/Non-science Divide

The science/non-science distinction has become increasingly blurred. This paper investigates whether recent cases of fraud in science can shed light on the distinction. First, it investigates whether there is an absolute distinction between science and non-science with respect to fraud, and in particular with regards to manipulation and fabrication of data. Finding that it is very hard to make such a distinction leads to the second step: scrutinizing whether there is a normative distinction between science and non-science. This is done by investigating one of the recent internationally famous frauds in science, the Sudbø case. This case demonstrates that moral norms are not only needed to regulate science because of its special characteristics, such as its potential for harm, but moral norms give science its special characteristics. Hence, moral norms are crucial in differentiating science from non-science. Although this does not mean that ethics can save the life of science, it can play a significant role in its resuscitation.