Johannes Persson

Do forest owners’ levels of education or value profiles explain their responses to climate change? The cultural cognition thesis has cast serious doubt on the familiar and often criticized "knowledge deficit" model, which says that laypeople are less concerned about climate change because they lack scientific knowledge. Advocates of CCT maintain that citizens with the highest degrees of scientific literacy and numeracy are not the most concerned about climate change. Rather, this is the group in which cultural polarization is greatest, and thus individuals with more limited scientific literacy and numeracy are more concerned about climate change under certain circumstances than those with higher scientific literacy and numeracy. The CCT predicts that cultural and other values will trump the positive effects of education on some forest owners' attitudes to climate change. Here, using survey data collected in 2010 from 766 private forest owners in Sweden and Germany, we provide the first evidence that perceptions of climate change risk are uncorrelated with, or sometimes positively correlated with, education level and can be explained without reference to cultural or other values. We conclude that the recent claim that advanced scientific literacy and numeracy polarizes perceptions of climate change risk is unsupported by the forest owner data. In neither of the two countries was university education found to reduce the perception of risk from climate change. Indeed in most cases university education increased the perception of risk. Even more importantly, the effect of university education was not dependent on the individuals' value profile.

The overall aim of this paper is to examine the claim that explanation is asymmetrical because causation is asymmetrical. The link between causal and explanatory asymmetry is focussed on. It is argued that many theories of causation account for causal asymmetry in a way that stops a causal model from contributing to our understanding of explanatory asymmetry. What appears to be generally advantageous with causal approaches is normally true only of a few specific causal accounts. These remaining alternatives, however, may well have some less attractive features that would never be brought to mind in the familiar explanatory contexts of balloons, flag poles, and the like—and with a standard concept of causation.

Kimberly Chuang’s detailed and very helpful reply to my article concerns Jon Elster’s struggle to develop a mechanistic account that sheds light on explanation in social science. I argue that a problem exists with Elster’s current conception of mechanistic explanation in social contexts. Chuang defends Elster’s conception against my critique. I still believe I have identified a problem with Elster’s conception. In this reply I want to recapitulate briefly Elster’s idea, as I understand it, and then use some of Chuang’s critical points to advance the position I advocate.

The functional separation of risk assessment and risk management has long been at the heart of risk analysis structures. Equally long it has been criticized for creating technocratic risk management due to valuations being done in the risk assessment to which the stakeholders do not have access. The criticism has mostly been of an ethical nature. Arguably, in separating risk assessment and risk management, one hopes to fulfil two requirements: Social requirement: we want risk management to meet the goals and needs of society. Scientific requirement: we do not want political views to influence the assessment of facts. We ask in this paper whether it is, in principle, possible to separate risk assessment from risk management. The crucial distinction between risk assessment and risk management we take to be between what kinds of values are involved in them and that separation is meant to shield risk assessment from risk management values and vice versa. Risk assessment is judged to be a scientific activity that should only involve scientific values. We go through a paradigmatic example of good science to see what those scientific values are and whether they are the only ones influencing science. We also present an example of a risk assessment in order to compare it to science. We conclude that the values involved in both science and risk assessment are of the same kind and that they both involve extra-scientific values. The paper ends with a short discussion of whether the above requirements can be met even though risk assessment and risk management are interdependent.

Although contentious, the concept of resilience is common in sustainability research. Critique of the concept have often focused on the content of the concept. In this paper we focus on another feature of concepts, namely how they are defined. We distinguish between concepts that are ostensively defined, that aim to point to some phenomena, and stipulatively defined concepts, where the content of the concept is given in the definition itself. We argue that although definitions themselves are similar across many different disciplines where resilience is used?most notably psychology and ecology?they differ in how. This has interesting consequences for how different disciplines can be connected and integrated. Notably, integration on basis of ostensively defined concepts turn on sharing the extension of the concept, but not necessarily the intension, whereas integration on basis of stipulatively defined concepts work in the opposite way.

Proven experience can be shared. Given this, we cannot assume that the character of proven experience is always manifest as a physical token in each individual sharing it. But the token might still exist somewhere. Perhaps that is a condition of the proven experience’s existence. Something similar could have been accepted as true of scientific knowledge, especially if those who argued that scientific claims were only shorthand for more complicated claims about observations had been right. But it seems that they were not. Hence there might be an ontological difference explaining why there will always be a netto divergence between science and proven experience.

In Swedish law, the notion of ‘science and proven experience’ defines the gold standard for public decision-making and practice, especially in medicine. The notion is notoriously vague but nevertheless plays an important role in the distribution of rights and duties of patients and healthcare workers. For example, failure to provide care in accordance with this standard can lead to penal responsibility. The notion also helps to define Swedish patients’ right to reimbursement for cross-border healthcare. From a legal point of view, the notion is especially intriguing because it appears to import medical standards into the legal conceptual apparatus. The purpose of this article is to explore the mechanisms of this andkindred ‘importing notions’ by investigating the role that the notion of science and proven experience plays in Swedish law and in the transfer of information between the legal and medical fields.

A key question for evidence-based medicine is how best to model the way in which EBM should‘[integrate] individual clinical expertise and the best external evidence’. We argue that the formulations and models available in the literature today are modest variations on a common theme and face very similar problems when it comes to risk analysis, which is here understood as a decision procedure comprising a factual assessment of risk, the risk assessment, and the decision what to do based on this assessment, the risk management. Both the early and updated models of evidence-based clinical decisions presented in the writings of Haynes, Devereaux and Guyatt assume that EBM consists of, among other things, evidence from clinical research together with information about patients’ values and clinical expertise. On this A-view, EBM describes all that goes on in a specific justifiable medical decision. There is, however, an alternative interpretation of EBM, the B-view, in which EBM describes just one component of the decision situation and in which, together with other types of evidence, EBM leads to a justifiable clincial decision but does not describe the decision itself. This B-view is inspired by a 100-years older version of EBM, a Swedish standard requiring medical decision-making, professional risk-taking and practice to be in accordance with‘science and proven experience’. In the paper, we outline how the Swedish concept leads to an improved understanding of the way in which scientific evidence and clinical experience can and cannot be integrated in light of EBM. How scientific evidence and clinical experience is integrated influences both the way we do risk assessment and risk management. In addition, the paper sketches the as yet unexplored historical background to VBE and EBM.

in Undetermined Table d’Hôte Ingar Brinck: Investigating the development of creativity: The Sahlin hypothesis 7 Linus Broström: Known unknowns and proto-second-personal address in photographic art 25 Johan Brännmark: Critical moral thinking without moral theory 33 Martin Edman: Vad är ett missförhållande? 43 Pascal Engel: Rambling on the value of truth 51 Peter Gärdenfors: Ambiguity in decision making and the fear of being fooled 75 Göran Hermerén: NIPT: Ethical aspects 89 Mats Johansson: Roboethics: What problems should be addressed and why? 103 Johan Laserna: Ambivalenta bilder 113 Anna-Sofia Maurin: Metaphysical explanation 161 Kevin Mulligan: Is preference primitive? 169 John D. Norton: How does your garden grow? 181 Johannes Persson & Annika Wallin: The distinction between internal and external validity 187 Johanna Seibt: Becoming our selves 197 Paul Slovic, Robin Gregory, David Frank, and Daniel Vastfjall: Confronting the collapse of humanitarian values in foreignpolicy decision making 209 Peter Sylwan: Det eviga livet 215 Claudine Tiercelin: Chance, love and logic: Ramsey and Peirce on norms, rationality and the conduct of life 221 Epilog 257 Frank Ramsey.

A key question for evidence-based medicine is how best to model the way in which EBM should “[integrate] individual clinical expertise and the best external evidence”. We argue that the formulations and models available in the literature today are modest variations on a common theme and face very similar problems. For example, both the early and updated models of evidence-based clinical decisions presented in Haynes, Devereaux and Guyatt assume that EBM consists of, among other things, evidence from clinical research and clinical expertise. On this A-view, EBM describes all that goes on in a specific justifiable medical decision. There is, however, an alternative interpretation of EBM, the B-view, in which EBM describes just one component of the decision situation and in which, together with other types of evidence, EBM leads to a justifiable clincial decision but does not describe the decision itself. This B-view is inspired by a 100-years older version of EBM, a Swedish standard requiring medical decision-making and practice to be in accordance with ‘science and proven experience’. In the paper we outline how the Swedish concept leads to an improved understanding of the way in which scientific evidence and clinical experience can and cannot be integrated in light of EBM. In addition the paper sketches the as yet unexplored historical background to EBM.

Knowledge of factors that trigger human response to climate change is crucial for effective climate change policy communication. Climate change has been claimed to have low salience as a risk issue because it cannot be directly experienced. Still, personal factors such as strength of belief in local effects of climate change have been shown to correlate strongly with responses to climate change and there is a growing literature on the hypothesis that personal experience of climate change explains responses to climate change. Here we provide, using survey data from 845 private forest owners operating in a wide range of bio-climatic as well as economic-social-political structures in a latitudinal gradient across Europe, the first evidence that the personal strength of belief and perception of local effects of climate change, highly significantly explain human responses to climate change. A logistic regression model was fitted to the two variables, estimating expected probabilities ranging from 0.07 to 0.81 for self-reported adaptive measures taken. Adding socio-demographic variables improved the fit, estimating expected probabilities ranging from 0.022 to 0.91. We conclude that to explain and predict adaptation to climate change, the combination of personal experience and belief must be considered

Philosophers of science have often favoured reductive approaches to how-possibly explanation. This article identifies three alternative conceptions making how-possibly explanation an interesting phenomenon in its own right. The first variety approaches “how possibly X?” by showing that X is not epistemically impossible. This can sometimes be achieved by removing misunderstandings concerning the implications of one’s current belief system but involves characteristically a modification of this belief system so that acceptance of X does not result in contradiction. The second variety offers a potential how-explanation of X. It is usually followed by a range of further potential how-explanations of the same phenomenon. In recent literature the factual claims implied by the second variety have been downplayed whereas the heuristic role of mapping the space of conceptual possibilities has been emphasized. I will focus especially on this truth-bracketing sense of potentiality when looking closer at the second variety in the paper. The third variety has attracted less interest. It presents a partial how-explanation of X. Typically it aims to establish the existence of a mechanism by which X could be and was generated. The third conception stands out as the natural alternative for the advocate of ontic how-possibly explanations. This article transfers Salmon’s view that explanation-concepts can be broadly divided into epistemic, modal, and ontic to the context of how-possibly explanations. Moreover, it is argued that each of the three above-mentioned varieties of how-possibly explanation occurs in science. To recognize this may be especially relevant for philosophers. We are often misled by the promises of various why-explanation accounts, and seem to have forgotten nearly everything about the diversity of how-possibly explanations

Facts are once again put to work in philosophical enterprises. The discussion in this paper is conducted under the presumption that we for this reason need to examine the nature of facts anew. To some extent it has been taken for granted that the question of properties and particulars is the primary problem to solve, and that the question of facts is secondary. This approach naturally leads to many of the old problems of facts and complexes. By taking facts as truly basic, we should see how we can construct the particulars and universals we still have need for. In order to further this idea, I suggest that facts may be though of as tropes or once-for-all occurrent properties. However, this characterisation of facts is acceptable only if tropes manage without substances or "thin" particulars for their instantiation.

BACKGROUND: Representing is about theories and theory formation. Philosophy of science has a long-standing interest in representing. At least since Ian Hacking's modern classic Representing and Intervening analytical philosophers have struggled to combine that interest with a study of the roles of intervention studies. With few exceptions this focus of philosophy of science has been on physics and other natural sciences. In particular, there have been few attempts to analyse the use of the notion of intervention in other disciplines where intervention studies are important, such as in nursing research. One unintended consequence of this is that the relations between representing and intervening tend to be less understood outside the natural sciences. OBJECTIVES AND DESIGN: This article highlights a number of possible topics on which nursing science and analytic philosophy of science can fruitfully interact. The basic idea is simple. Building on a characterisation of interventions in terms of what is intervened on and with respect to what, we suggest that interventions in nursing research typically are a blend of varieties belonging to the three dimensions of agency, epistemology, and ontology. The details of the blend determine the relation of the particular intervention study to traditional representational categories such as inductivism and hypothetico-deductive method, and have a bearing on its explanatory power and other more theory independent features of research as well. The framework we suggest should be relevant for nurse researchers who want to adopt a more general and analytically entrenched perspective on representing and intervening than the methodological boundaries in nursing research typically allow

The hypothesis that human reasoning and decision-making can be roughly modeled by Expected Utility Theory has been at the core of decision science. Accumulating evidence has led researchers to modify the hypothesis. One of the latest additions to the field is Dual Process theory, which attempts to explain variance between participants and tasks when it comes to deviations from Expected Utility Theory. It is argued that Dual Process theories at this point cannot replace previous theories, since they, among other things, lack a firm conceptual framework, and have no means of producing independent evidence for their case.

Polygenic effects have more than one cause. They testify to the fact that several causal contributors are sometimes simultaneously involved in causation. The importance of polygenic causation was noticed early on by Mill (1893). It has since been shown to be a problem for causal-law approaches to causation and accounts of causation cast in terms of capacities. However, polygenic causation needs to be examined more thoroughly in the emerging literature on causal mechanisms. In this paper I examine whether an influential theory of mechanisms proposed by Peter Machamer, Lindley Darden and Carl Craver can accommodate polygenic effects and other forms of causal interaction. This theory is problematic, I will argue, because it ascribes a central role to activities. In it, activities are needed not only to constitute mechanisms but also to perform the causal role of mechanisms. Any such mechanism-as-activity will be incompatible with causal situations where either no or merely another kind of activity occurs. But, as I will try to illustrate in this paper, both kinds of situation may be frequent. If I am right, the view that Machamer and colleagues suggest leads to an impoverished conception of mechanism.

Researchers often aim to make correct inferences both about that which is actually studied and about what the results generalize to. The language of internal and external validity is not used by everyone, but many of us would agree that intuitively the distinction makes a lot of sense. Two claims are commonly made with respect to internal and external validity. The first is that internal validity is prior to external validity since there is nothing to generalize if the findings obtained in, for instance, the experimental setting do not hold. The first claim is explicit in many writings. See for instance Francisco Guala’s influential book The methodology of experimental economics. And it is often implicitly relied on. The second claim is that researchers have to make a trade-off between internal and external validity. When one is increased, the other will decrease. The second claim was made already from the start by D.T Campbell in his classic Factors relevant to the validity of experiments in social settings. There is a certain tension between the first and the second claim. It has been argued before that it might be difficult to combine them. We intend to make the stronger point that both claims are misconstrued. Our hypothesis is that the relationship between internal and external validity has to be re-conceptualized, and we will briefly indicate how

This paper is an attempt to further our understanding of mechanisms conceived of as ontologically separable from laws. What opportunities are there for a mechanistic perspective to be independent of, or even more fundamental than, a law perspective? Advocates of the mechanistic view often play with the possibility of internal and external reliability, or with the paralleling possibilities of enforcing, counteracting, redirecting, etc., the mechanisms’ power to produce To further this discussion I adopt a trope ontology. It is independent of the notion of law, and can easily be adapted to account for such characteristics of mechanisms. The idea of tropes as mechanisms is worked out in some detail. According to the resulting picture, there is still an opportunity to link mechanisms and laws. But while the predominant law view conceives of mechanistic approaches as special kinds of law accounts, this study indicates that the converse may be true. Law accounts are special cases of mechanistic accounts, and they work only in those worlds where the mechanisms are of the right kind.

Jon Elster worries about the explanatory power of the social sciences. His main concern is that they have so few well-established laws. Elster develops an interesting substitute: a special kind of mechanism designed to fill the explanatory gap between laws and mere description. However, his mechanisms suffer from a characteristic problem that I will explore in this article. As our causal knowledge of a specific problem grows we might come to know too much to make use of an Elsterian mechanism but still lack a law. We might then find ourselves in the paradoxical position of knowing more relevant causal truths about the phenomenon we are interested in than we did before, but being able to explain less. If this possibility is realized in social science settings, as I argue it might well be, Elster?s mechanistic account is threatened. Moreover, even if the possibility is rarely realized in that way, it raises, simply as a possibility, a conceptual problem with Elster?s mechanistic framework