The claims of randomized controlled trials to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This article describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. (...) It argues that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The article reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

In their rich and intricate paper ‘Independence, Invariance, and the Causal Markov Condition’, Daniel Hausman and James Woodward ([1999]) put forward two independent theses, which they label ‘level invariance’ and ‘manipulability’, and they claim that, given a specific set of assumptions, manipulability implies the causal Markov condition. These claims are interesting and important, and this paper is devoted to commenting on them. With respect to level invariance, I argue that Hausman and Woodward's discussion is confusing because, as I point out, (...) they use different senses of ‘intervention’ and ‘invariance’ without saying so. I shall remark on these various uses and point out that the thesis is true in at least two versions. The second thesis, however, is not true. I argue that in their formulation, the manipulability thesis is patently false and that a modified version does not fare better. Furthermore, I think their proof that manipulability implies the causal Markov condition is not conclusive. In the deterministic case it is valid but vacuous, whereas it is invalid in the probabilistic case. 1 Introduction 2 Intervention, invariance and modularity 3 The causal Markov condition: CM1 and CM2 4 From MOD to the causal Markov condition and back 5 A second argument for CM2 6 The proof of the causal Markov condition for probabilistic causes 7 ‘Cartwright's objection’ defended 8 Metaphysical defenses of the causal Markov condition 9 Conclusion. (shrink)

There is a takeover movement fast gaining influence in development economics, a movement that demands that predictions about development outcomes be based on randomized controlled trials. The problem it takes up—of using evidence of efficacy from good studies to predict whether a policy will be effective if we implement it—is a general one, and affects us all. My discussion is the result of a long struggle to develop the right concepts to deal with the problem of warranting effectiveness predictions. Whether (...) I have it right or not, these are questions of vast social importance that philosophers of science can, and should, help answer. (shrink)

WE AIM HERE to outline a theory of evidence for use. More specifically we lay foundations for a guide for the use of evidence in predicting policy effectiveness in situ, a more comprehensive guide than current standard offerings, such as the Maryland rules in criminology, the weight of evidence scheme of the International Agency for Research on Cancer (IARC), or the US ‘What Works Clearinghouse’. The guide itself is meant to be well-grounded but at the same time to give practicable (...) advice, that is, advice that can be used by policy-makers not expert in the natural and social sciences, assuming they are well-intentioned and have a reasonable but limited amount of time and resources available for searching out evidence and deliberating. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

<I>Conducting Hermeneutic Research: From Philosophy to Practice is the only textbook that teaches the reader ways to conduct research from a philosophical hermeneutic perspective. It is an invaluable resource for graduate students about to embark in hermeneutic research and for academics or other researchers who are novice to this research method or who wish to extend their knowledge. In 2009, the lead author of this proposed text was one of three co-founders of the Canadian Hermeneutic Institute. The institute was created (...) as a means of bringing together scholars of hermeneutics and hermeneutic research across disciplines in creative dialogue and conversations of philosophy, research, and practice. An outcome of this was the launch of the <I>Journal of Applied Hermeneutics, with Nancy J. Moules serving as Editor. The work of the institute and the journal make clear that people (both students and professors) seek practical guidance on how to conduct hermeneutic research. This book is a must read for this audience. (shrink)

This book presents a radical new picture of natural order. The Newtonian idea of a cosmos ruled by universal and exceptionless laws has been superseded; replaced by a conception of nature as a realm of diverse powers, potencies, and dispositions, a 'dappled world'. There is order in nature, but it is more local, diverse, piecemeal, open, and emergent than Newton imagined. In each chapter expert authors expound the historical context of the idea of laws of nature, and explore the diverse (...) sorts of order actually presupposed by work in physics, biology, and the social sciences. They consider how human freedom might be understood, and explore how Newton's idea of a 'universal designer' might be revised, in this new context. They argue that there is not one unified totalizing program of science, aiming at the completion of one closed causal system. We live in an ordered universe, but we need to rethink the classical idea of the 'laws of nature' in a more dynamic and creatively diverse way. (shrink)

Four distinguished authors have been brought together to produce this elegant study of a much-neglected figure. The book is divided into three sections: Neurath's biographical background and the economic and social context of his ideas; his theory of science; and the development of his role in debates on Marxist concepts of history and his own conception of science. Coinciding with the emerging serious interest in logical positivism, this timely publication will redress a current imbalance in the history and philosophy of (...) science. (shrink)

This book on the philosophy of science argues for an empiricism, opposed to the tradition of David Hume, in which singular rather than general causal claims are primary; causal laws express facts about singular causes whereas the general causal claims of science are ascriptions of capacities or causal powers, capacities to make things happen. Taking science as measurement, Cartwright argues that capacities are necessary for science and that these can be measured, provided suitable conditions are met. There are case studies (...) from both econometrics and quantum mechanics. (shrink)

Philosophers of science have had little to say about ‘middle-range theory’ although much of what is done in science and of what drives its successes falls under that label. These lectures aim to spark an interest in the topic and to lay groundwork for further research on it. ‘Middle’ in ‘middle range’ is with respect to the level both of abstraction and generality. Much middle-range theory is about things that come under the label ‘mechanism’. The lectures explore three different kinds (...) of mechanism: struc tural mechanisms or underlying systems that afford causal pathways; causal-chain mechanisms that are represented in what in policy contexts are called ‘theories of change’ and for which I give an extended account following the causal process theory of Wesley Salmon; and middle-range-law mechanisms like those discussed by Jon Elster, which I claim are —and rightly are— rampant throughout the social sciences. The theory of the democratic peace, that democracies do not go to war with democracies, serves as a running example. The discussions build up to the start of, first, an argument that reliability in social (and natural) science depends not so much on evidence as it does on the support of a virtuous tangle of practices (without which there couldn’t even be evidence), and second, a defence of a community-practice centred instrumentalist understanding of many of the central basic principles that we use (often successfully) in social (and in natural) science for explanation, prediction and evaluation. (shrink)

In this paper, the authors describe an aspect of a program of research around grief and clinical practice. The first phase of the study involves examination of experiences of grief with attention to troublesome or problematic beliefs that fuel the extent of suffering in the bereaved. The data, obtained from a review of videotaped clinical interviews with families seen in the Family Nursing Unit at the University of Calgary, were analyzed according to philosophical hermeneutic tradition. Findings suggest that grief is (...) an experience that is ongoing, that changes in nature over time, but that involves a continuing relationship with the deceased; it is a graceful, periodic, deliberate walk backwards while keeping a sure foot in living forward. (shrink)

In this paper, the authors address the perceived recent trend of funding and publishing bodies that seem to have taken a regard of qualitative research as a subordinate to, or even a subset of, quantitative research. In this reflection, they pull on insights that Hans-Georg Gadamer offered around the history of the natural and human science bifurcation, ending with a plea that qualitative research needs to be received, appraised, judged, and promoted by different lenses and criteria of value.

Knowledge of causal laws is expensive and hard to come by. But we work hard to get it because we believe that it will reduce contingency in planning policies and in building new technologies: knowledge of causal laws allows us to predict reliably what the outcomes will be when we manipulate the factors cited as causes in those laws. Or do they? This paper will argue that causal laws have no special role here. As economists from JS Mill to Robert (...) Lucas and David Hendry stress, along recently with philosophers like James Woodward and Sandra Mitchell, they can do the job only if they are invariant under the manipulations proposed. But then, I shall argue, anything that is invariant under the proposed manipulations will do this job equally well. There seems to be nothing special about causal-law knowledge in and of itself that makes it particularly valuable for policy and technology prediction. What seems to matter is invariance alone, not causality. But what guarantees invariance and how do we know when it will obtain? Here certain kinds of causal laws do have a special place – those underwritten either by what I have called ‘nomological machines’ or by what I have called ‘capacities’. Capacities and nomological machines have a double virtue that makes them invaluable for policy planning. First, the causal laws they give rise to will be invariant so long as they obtain; and second, they typically have visible markers we can come to recognize that tell us when they obtain. The markers for nomological machines are shakier than those for capacities, though, since capacities are often tied to markers by well-established empirical laws. Capacities have their own drawback however, which is the final topic of this paper: the causal laws that are guaranteed by a capacity connect the obtaining of a capacity with its exercise. But Hume argued that no distinction can be made between the obtaining of a power and its exercise. (shrink)

Pluralism is usually opposed to realism. This paper argues that the two come naturally into conflict only given a third assumption-imperialism, i.e., the doctrine that some one, or some handful, of our favourite theories are universal. This paper attempts to show why that assumption is implausible, even in the case of fundamental theories in physics. It argues first that physics theories are true only in their models: for the most part the successes of a theory are confined to situations that (...) resemble the models. Second it argues specifically for the possibility of peaceful co-existence between quantum and classical physics. (shrink)

A good many models used in physics and economics offer descriptions of imaginary situations, using a combination of mathematics and natural language. The descriptions are both thin - not much about the situation is filled in - and unrealistic - what is filled in is not true of many real situations. Yet we want to use the results of these models to inform our conclusions about a range of actually occurring situations. I propose we interpret many of these models as (...) fables. The actual happenings in the model are only one concrete instantiation of a lesson that is more widely applicable ‘when expressed in more abstract language.' A fable generally comes with the abstract lesson attached; parables, by contrast, usually require an interpretation from outside. Models, then, tend to be more like parables than fables. The right abstract interpretation is not supplied by the model itself. The central problem, then, is where shall it come from? (shrink)

Problem: Medical student mistreatment, as well as patient and staff mistreatment by all levels of medical trainees and faculty, is still prevalent in U.S. clinical training. Largely missing in interventions to reduce mistreatment is acknowledgement of the abuse of power produced by the hierarchical structure in which medicine is practiced. Approach: Beginning in 2001, Yale School of Medicine has held annual “Power Day” workshops for third year medical students and advanced practice nursing students, to define and analyse power dynamics within (...) the medical hierarchy and hidden curriculum using literature, guest speakers, and small groups. During rotations, medical students write narratives about the use of power witnessed in the wards. In response to student and small group leader feedback, workshop organizers have developed additional activities related to examining and changing the use of power in clinical teams. Outcome: Emerging narrative themes included the potential impact of small acts and students feeling “mute” and “complicit” in morally distressing situations. Small groups provided safe spaces for advice, support, and professional identity formation. By 2005, students recognized residents that used power positively with Power Day awards and alumni served as keynote speakers on the use of power in medicine. By 2010, departments including OB/GYN, surgery, psychiatry, and paediatrics, had added weekly team Power Hour discussions. Next Steps: The authors highlight barriers, benefits, and lessons learned. Barriers include the notion of clinical irrelevance and resistance to the word “power” due to perceived accusation of abuse. Benefits include promoting open dialogue about power, fostering inter-professional collaboration, rewarding positive role modelling by residents and faculty, and creating a network of trainee empowerment and leadership. Furthermore, faculty have started to ask that issues of power be addressed in a more transparent way at their level of the hierarchy as well. (shrink)

Many, if not most, of our highly prized ‘laws’ of physics cannot be adequately rendered as statements of regular association among the values of ‘categorical’ quantities, I have argued.63 This is true even if we do not balk at the concept of natural necessity and are willing to add that the associations hold ‘by law’. They are rather ascriptions of capacities. They tell us what capacities a system will have by virtue of having a given property. The law of gravity (...) is one example. A system of mass M has the capacity of strength GMm/r2 to move another object of mass m a distance r away towards itself. I call this the gravitational capacity. My second thesis is a commonly shared one. Ascriptions of capacities do not reduce to conditionals involving only categorical properties. I shall here discuss two questions about these theses: 1) Why think of capacities as akin to dispositions or powers; and 2) Why allow them in science? Before tackling the first question, I shall first try to figure out what features we expect to be characteristic of dispositions and powers themselves. (shrink)

Knowledge of causal laws is expensive and hard to come by. But we work hard to get it because we believe that it will reduce contingency in planning policies and in building new technologies: knowledge of causal laws allows us to predict reliably what the outcomes will be when we manipulate the factors cited as causes in those laws. Or do they? This paper will argue that causal laws have no special role here. As economists from JS Mill to Robert (...) Lucas and David Hendry stress, along recently with philosophers like James Woodward and Sandra Mitchell, they can do the job only if they are invariant under the manipulations proposed. But then, I shall argue, anything that is invariant under the proposed manipulations will do this job equally well. There seems to be nothing special about causal-law knowledge in and of itself that makes it particularly valuable for policy and technology prediction. What seems to matter is invariance alone, not causality. But what guarantees invariance and how do we know when it will obtain? Here certain kinds of causal laws do have a special place – those underwritten either by what I have called ‘nomological machines’ or by what I have called ‘capacities’. Capacities and nomological machines have a double virtue that makes them invaluable for policy planning. First, the causal laws they give rise to will be invariant so long as they obtain; and second, they typically have visible markers we can come to recognize that tell us when they obtain. The markers for nomological machines are shakier than those for capacities, though, since capacities are often tied to markers by well-established empirical laws. Capacities have their own drawback however, which is the final topic of this paper: the causal laws that are guaranteed by a capacity connect the obtaining (or triggering) of a capacity with its exercise. But Hume argued (mistakenly I suggest) that no distinction can be made between the obtaining of a power and its exercise. (shrink)

Nursing on paper: therapeutic letters in nursing practice This paper offers a selected piece of interpretive research extracted from the context of a larger research study. The hermeneutic research inquiry described in this paper involved the examination of the nursing and family therapy intervention of therapeutic letters. It incorporated the textual interpretation of 11 therapeutic letters, clinical sessions with three families, clinical team discussions, and research interviews with four family members and three nurse clinicians who participated in the writing of (...) the letters. This particular paper extracts segments of the research related to the letters received by two participants, as well as some general findings, with a focus on the possibilities and influences of therapeutic letters in nursing practice. The findings of this research offer suggestions, not as a template, but as an inspiration and evocation to write therapeutic letters that address the obligation of meeting people experiencing illness at the point of their suffering, with words and questions that invite relationship, reflection, and are large enough to sustain a meeting. (shrink)

This is a much-needed new introduction to a field that has been transformed in recent years by exciting new subjects, ideas, and methods. It is designed for students in both philosophy and the social sciences. Topics include ontology, objectivity, method, measurement, and causal inference, and such issues as well-being and climate change.