An astonishing volume and diversity of evidence is available for many hypotheses in the biomedical and social sciences. Some of this evidence—usually from randomized controlled trials (RCTs)—is amalgamated by meta-analysis. Despite the ongoing debate regarding whether or not RCTs are the ‘gold-standard’ of evidence, it is usually meta-analysis which is considered the best source of evidence: meta-analysis is thought by many to be the platinum standard of evidence. However, I argue that meta-analysis falls far short of that standard. Different meta-analyses (...) of the same evidence can reach contradictory conclusions. Meta-analysis fails to provide objective grounds for intersubjective assessments of hypotheses because numerous decisions must be made when performing a meta-analysis which allow wide latitude for subjective idiosyncrasies to influence its outcome. I end by suggesting that an older tradition of evidence in medicine—the plurality of reasoning strategies appealed to by the epidemiologist Sir Bradford Hill—is a superior strategy for assessing a large volume and diversity of evidence. (shrink)

Largely unacknowledged by historians of the human sciences, late-19th-century psychical researchers were actively involved in the making of fledgling academic psychology. Moreover, with few exceptions historians have failed to discuss the wider implications of the fact that the founder of academic psychology in America, William James, considered himself a psychical researcher and sought to integrate the scientific study of mediumship, telepathy and other controversial topics into the nascent discipline. Analysing the celebrated exposure of the medium Eusapia Palladino by German-born Harvard (...) psychologist Hugo Münsterberg as a representative example, this article discusses strategies employed by psychologists in the United States to expel psychical research from the agenda of scientific psychology. It is argued that the traditional historiography of psychical research, dominated by accounts deeply averse to its very subject matter, has been part of an ongoing form of ‘boundary-work’ to bolster the scientific status of psychology. (shrink)

This article presents a new framework for the analysis of experimental control. The framework highlights different functions for experimental controls in the realization of an experiment: experimental controls that serve as tests and experimental controls that serve as probes. The approach to experimental control proposed here can illuminate the constitutive role of controls in knowledge production, and it sheds new light on the notion of exploratory experimentation. It also clarifies what can and what cannot be expected from reviewers of scientific (...) journal articles giving feedback on experimental controls. (shrink)

This paper discusses two methodological notions, the concepts Gegenprobe (countercheck) and Gegenversuch (counter-trial), which were widely applied, discussed, relied upon, and defended in German-language writings about empirical inquiry. In the decades around 1800, they were common in physiology; medicine; agriculture; chemistry; various technologies, such as printing, metallurgy, and mining; accounting; and legal and political argumentation. The ubiquity of those concepts signals a broad concern with securing empirical findings and empirical knowledge. Gegenproben and Gegenversuche – the terms as well as the (...) practices – are evidence for the close connection among explicitly knowledge-seeking endeavors and crafts and technologies. Physiological experiments, chemical analyses, agricultural or vaccination trials were indebted to applied and practical procedures of making and assaying. What united these different fields was the fact that the problems that had to be solved were very complex yet at the same time of immediate relevance to everyday lives (like diseases or crops) or highly controversial (like vital forces or spontaneous generation). We know that late eighteenth-century and early nineteenth-century practices of inquiry were firmly embedded in applied, technical contexts; this essay shows that methodological notions were anchored in applied, technical contexts as well. (shrink)

During the last third of the 19th century, the ‘new’ French psychology developed within ‘the hypnotic context’ opened up by Charcot. In spite of their claims to the scientific nature of their hypnotic experiments, Charcot and his followers were unable to avoid the miracles that had accompanied mesmerism, the forerunner of hypnosis. The hysterics hypnotized in the Salpêtrière Hospital were expected to have supernormal faculties and these experiments opened the door to psychical research. In 1885 the first French psychology society (...) was founded. The research carried out by this society may seem surprising: its members – Charles Richet in particular – were interested in strange phenomena, like magnetic lucidity, ‘mental suggestion’, thought-reading, etc. Very quickly, psychologists applied themselves to finding rational explanations for these supposedly miraculous gifts. Generally, they ascribed them to unconscious or subconscious perceptual mechanisms. Finally, after a few years, studies of psychical phenomena were excluded from the field of psychology. However, during the 4th International Congress of Psychology, which took place in Paris in 1900, the foundation of an institute devoted to the study of psychical phenomena was announced, but Pierre Janet and Georges Dumas founded within it the Société Française de Psychologie, from which psychical research was excluded. As for Charles Richet, disappointed by the psychologists, he devoted himself to the development of a new ‘science’ which he called ‘Métapsychique’. Several hypotheses have been put forward to account for this early research undertaken by the French psychologists, pertaining as much to parapsychology as to scientific psychology. (shrink)

This paper proposes to recover the topic of the philosophy of scientific method from its late nineteenth-century roots. The subject matter of scientific method sprouted from key inferential ingredients identified by Charles Peirce. In this paper, the historical path is traversed from the viewpoint of contemporary Cognitive Structural Realism (CSR). Peirce’s semiotic theory of methods and practices of scientific inquiry prefigured CSR’s reliance on embodied informational structures and experimentation upon forms of relations that model generic scientific domains. Three results are (...) shown to follow from this convocation: (i) a naturalization of Peirce’s interconnected abductive, deductive and inductive stages of the logic of science, here characterized de novo in terms of CSR. (ii) a perspective to scientific modeling that incorporates processes of abstraction and generalization as originated from Peirce’s logic of science, and (iii) diagrammatic reasoning as a pivotal method in analyzing scientific reasoning in experimental practices. (shrink)

Peter Urbach has argued, on Bayesian grounds, that experimental randomization serves no useful purpose in testing causal hypothesis. I maintain that he fails to distinguish general issues of statistical inference from specific problems involved in identifying causes. I concede the general Bayesian thesis that random sampling is inessential to sound statistical inference. But experimental randomization is a different matter, and often plays an essential role in our route to causal conclusions.

The value-free ideal in science has been criticised as both unattainable and undesirable. We argue that it can be defended as a practical principle guiding scientific research even if the unattainability and undesirability of a value-free end-state are granted. If a goal is unattainable, then one can separate the desirability of accomplishing the goal from the desirability of pursuing it. We articulate a novel value-free ideal, which holds that scientists should act as if science should be value-free, and we argue (...) that even if a purely value-free science is undesirable, this value-free ideal is desirable to pursue. (shrink)

The history of contraceptives met the history of drugs long before the invention of the contraceptive pill. In the first half of the twentieth century, numerous pharmaceutical laboratories, including major ones, manufactured and marketed chemical contraceptives: jellies, suppositories, creams, powders and foams applied locally to prevent conception. Efforts to put an end to the marginal status of these products and to transform them into ‘ethical’ drugs played an important role in the development of standardized laboratory tests of efficacy of contraceptive (...) preparations; debates on the validity of such tests; evaluation of the long-term toxicity of chemical compounds; and the rise of collaborations between activists, non-profit organizations and the pharmaceutical industry. Chemical contraceptives were initially associated with quack medicine, shady commercial practices and doubtful morality. Striving to change the status of contraceptives and to promote safe and efficient products that reduced fertility in humans shaped some of the key features of the present-day production and regulation of pharmaceuticals. (shrink)

Semmelweis’s work predates the discovery of the power of randomization in medicine by almost a century. Although Semmelweis would not have consciously used a randomized controlled trial (RCT), some features of his material—the allocation of patients to the first and second clinics—did involve what was in fact a randomization, though this was not realised at the time. This article begins by explaining why Semmelweis’s methodology, nevertheless, did not amount to the use of a RCT. It then shows why it is (...) descriptively and normatively interesting to compare what he did with the modern approach using RCTs. The argumentation centres on causal inferences and the contrast between Semmelweis’s causal concept and that deployed by many advocates of RCTs. It is argued that Semmelweis’s approach has implications for matters of explanation and medical practice. (shrink)

In science and technology studies today, there is a troubling tendency to portray actors in the biosciences as “cultural dopes” and technology as having monolithic qualities with predetermined outcomes. To remedy this analytical impasse, this article introduces the concept styles of valuation to analyze how actors struggle with valuing technology in practice. Empirically, this article examines how actors in a bioscientific laboratory struggle with valuing the properties and qualities of algorithms in a high-throughput setting and identifies the copresence of several (...) different styles. The question that the actors struggle with is what different configurations of algorithms, devices, and humans are “good bioscience,” that is, what do the actors perform as a good distribution of agency between algorithms and humans? A key finding is that algorithms, robots, and humans are valued in multiple ways in the same setting. For the actors, it is not apparent which configuration of agency and devices is more authoritative nor is it obvious which skills and functions should be redistributed to the algorithms. Thus, rather than tying algorithms to one set of values, such as “speed,” “precision,” or “automation,” this article demonstrates the broad utility of attending to the multivalence of algorithms and technology in practice. (shrink)

The requirement of randomization in experimental design was first stated by R. A. Fisher, statistician and geneticist, in 1925 in his book Statistical Methods for Research Workers. Earlier designs were systematic and involved the judgment of the experimenter; this led to possible bias and inaccurate interpretation of the data. Fisher's dictum was that randomization eliminates bias and permits a valid test of significance. Randomization in experimenting had been used by Charles Sanders Peirce in 1885 but the practice was not continued. (...) Fisher developed his concepts of randomizing as he considered the mathematics of small samples, in discussions with "Student," William Sealy Gosset. Fisher published extensively. His principles of experimental design were spread worldwide by the many "voluntary workers" who came from other institutions to Rothamsted Agricultural Station in England to learn Fisher's methods. (shrink)

Stephen Braude, a philosopher, believes that scientists, scholars and intellectuals ignore the wide range of evidence for psychic phenomena. They dismiss what is known and refuse to inquire further. He uses strong words such as “intellectual dishonesty and cowardice.” He means me and probably you. He made these allegations in his second book on parapsychology, The Limits of Influence, which is subtitled Psychokinesis and the Philosophy of Science. It was published in 1986. The editor of Dialogue thought that the charges (...) had not been adequately discussed, and that the appearance of a paperbound edition would be a good occasion to treat them seriously. (shrink)

Scientific methods are heuristic in nature. Heuristics are simplifying, incomplete, underdetermined and fallible problem-solving rules that can nevertheless serve certain goals in certain contexts better than truth-preserving algorithms. Because of their goal- and context-dependence, a framework is needed for systematic choosing between them. This is the domain of scientific methodology. Such a methodology, I argue, relies on a form of instrumental rationality. Three challenges to such an instrumentalist account are addressed. First, some authors have argued that the rational choice of (...) at least some methods, namely those supporting belief formation, is not goal-dependent. Second, some authors have observed that some method choices seem intuitively rational, even though relevant goals are lacking. Thirdly, some authors have argued that instrumental rationality itself depends on a goal-independent form of rationality. It is the heuristic nature of scientific methods that affords me the arguments against these challenges. This heuristic-instrumentalist account provides the means-ends analysis needed to evaluate heuristic method choice. The paper thus offers the conceptual basis for a scientific methodology that is both compatible with the heuristic nature of actual scientific practice and also normatively relevant for assessing method choice. (shrink)

Randomized experiments, as developed by Esther Duflo and Abhijit Banerjee at the Abdul Latif Jameel Poverty Action Lab, offer a novel, evidence-based approach to fighting poverty. This approach is original, in that it imports the methodology of clinical trials for application in development economics. This paper examines the analogy between J-PAL’s field experiments in development economics and randomized controlled trials in medicine. RCTs and randomized field experiments are commonly treated as identical, but such treatment neglects some of the major distinguishing (...) features that make each experiment specifically apt for use in its respective field. The central claim of this paper is that the analogy between medicine and development economics is incomplete because the central dimensions of RCTs are not simply different but altogether lacking in J-PAL’s approach. This weakens both the political and the theoretical power of such experiments in development economics. (shrink)

Metapsychy, or metapsychics, is the French science known in English-speaking countries as parapsychology or psychical research. As Régine Plas has shown, the ‘psychic’ phenomena were among the first subjects of psychological inquiry. Like many of his colleagues, Henri Piéron began his career researching apparent telepathic phenomena, and in collaboration with Nicolae Vaschide explained them in terms of an ‘intellectual parallelism’. From 1913 onward, Piéron developed the ‘Métapsychie’ section of L’année psychologique, where he used his critical skills to sometimes foster and (...) sometimes discourage this field of research. In the background to these events was the issue of metapsychy's place within the field of psychology, a field on which Piéron had himself helped to confer institutional and professional status. The growing disparity between metapsychy and psychology suggested a distinct demarcation between the two disciplines, with Piéron zealously fulfilling a missionary role as one of several gatekeepers. While open to what were presented as new examples of physiologically objectified psychic activity, he never really seems to have observed anything he considered convincing and so generally suspected fraud. His interventions played a role in the emancipation/expulsion of metapsychy from the nascent field of psychology, with the advantage of increasing recognition of the epistemic authority of the latter. (shrink)

Charles Sanders Peirce was acknowledged by William James as the founder of pragmatism; however, while James’ appreciation for psychology is well taken into account in his philosophy, the role that psychological inquiry played in Peirce’s thought remains largely unexplored. Few excellent studies indicate Peirce as the first American experimental psychologist (Cadwallader 1974, 1975; Fisch 1986) and as the first to perform a truly modern experiment in psycho-physics (Hacking 1988). Nonetheless, Peirce’s commitment to psycho-physics fails to be fully integrated with the (...) broader project of his philosophy. This integration is crucial to gain a better understanding of the complexity of Peirce’s system of thought and of his position in the psychologistic-antipsychologistic divide. On the logical side, making Peirce’s position on psychology explicit leads to investigating his material logic; on the psychological side, Peirce’s scientific approach to psychology has its theoretical foundation in Kant and further marks the distinction between Peirce’s pragmatism and James’. (shrink)

The most conspicuous form of agricultural experiment is the field trial, and within the history of such trials, the arrival of the randomised control trial is considered revolutionary. Originating with R.A. Fisher within British agricultural science in the 1920s and 30s, the RCT has since become one of the most prodigiously used experimental techniques throughout the natural and social sciences. Philosophers of science have already scrutinised the epistemological uniqueness of RCTs, undermining their status as the ‘gold standard’ in experimental design. (...) The present paper introduces a historical case study from the origins of the RCT, uncovering the initially cool reception given to this method by agricultural scientists at the University of Cambridge and the National Institute of Agricultural Botany. Rather than giving further attention to the RCT, the paper focuses instead on a competitor method – the half-drill strip – which both predated the RCT and remained in wide use for at least a decade beyond the latter’s arrival. In telling this history, John Pickstone’s Ways of Knowing is adopted, as the most flexible, and productive way to write the history of science, particularly when sciences and scientists have to work across a number of different kinds of place. It is shown that those who resisted the RCT did so in order to preserve epistemic and social goals that randomisation would have otherwise run a tractor through. (shrink)

A key role in inference is played by randomization, which has been extensively used in clinical trials designs. Randomization is primarily intended to prevent the source of bias in treatment allocation by producing comparable groups. In the frequentist framework of inference, randomization allows also for the use of probability theory to express the likelihood of chance as a source for the difference of end outcome. In the Bayesian framework, its role is more nuanced. The Bayesian analysis of clinical trials can (...) afford a valid rationale for selective controls, pointing out a more limited role for randomization than it is generally accorded. This paper is aimed to offer a view of randomization from the perspective of both frequentist and Bayesian statistics and discussing the role of randomization also in theoretical decision models. (shrink)

There is something very appealing about the idea that we are epistemic agents. One reason—if not the main reason—is that, while we are undoubtedly fallible creatures, us being epistemic agents that do things means that it might just be within our power to improve and thereby do better. One important way in which we would want to improve is in relation to our well-established tendency for cognitive bias. Still, the proper role of epistemic agency in us avoiding or correcting for (...) cognitive bias is highly limited. In fact, what we know from empirical psychology—particularly with respect to our tendencies for overconfidence—suggests that we cannot rely on ourselves for epistemic improvement, and have good reason to impose significant constraints on our ability to exercise such agency in ameliorative contexts. (shrink)

In 1884 French physiologist Charles Richet published an article on ‘‘mental suggestion’’ in the Revue philosophique de la France et de l’etrangere that is an early classic of experimental parapsychology. This work is generally remembered for the use of statistical evaluation of ESP experiments. Nonetheless, Richet discussed other issues as well that are generally neglected. This included reanalyses of previously published thought-transference studies, and discussions of topics such as the place of mental suggestion in science, study participants, and the relationship (...) of mediumship to the unconscious mind. Furthermore, in this paper Richet wrote about a variety of issues related to ESP such as its various features, targets, motor automatisms, its unconscious nature, and theoretical issues. Keywords: Charles Richet—mental suggestion—ESP—French psychical research—mediumship. (shrink)

The thesis consists of an introduction and two papers. In the introduction a brief historical survey of empirical investigations into the effectiveness of medicinal interventions is given. Also, the main ideas of the EBM movement are presented. Both included papers can be viewed as investigations into the reasonableness of EBM and its hierarchies of evidence. Paper I: Typically, in a clinical trial patients with specified symptoms are given either of two or more predetermined treatments. Health endpoints in these groups are (...) then compared using statistical methods. Concerns have been raised, not least from adherents of so-called alternative medicine, that clinical trials do not offer reliable evidence for some types of treatment, in particular for highly individualized treatments, for example traditional homeopathy. It is argued that such concerns are unfounded. There are two minimal conditions related to the nature of the treatments that must be fulfilled for evaluability in a clinical trial, namely the proper distinction of the two treatment groups and the elimination of confounding variables or variations. These are delineated, and a few misunderstandings are corrected. It is concluded that the conditions do not preclude the testing of alternative medicine, whether individualized or not. Paper II: Traditionally, mechanistic reasoning has been assigned a negligible role in standard EBM literature, although some recent authors have argued for an upgrading. Even so, mechanistic reasoning that has received attention has almost exclusively been positive -- both in an epistemic sense of claiming that there is a mechanistic chain and in a health-related sense of there being claimed benefits for the patient. Negative mechanistic reasoning has been neglected, both in the epistemic and in the health-related sense. I distinguish three main types of negative mechanistic reasoning and subsume them under a new definition of mechanistic reasoning in the context of assessing medical interventions. Although this definition is wider than a previous suggestion in the literature, there are still other instances of reasoning that concern mechanisms but do not count as mechanistic reasoning. One of the three distinguished types, which is negative only in the health-related sense, has a corresponding positive counterpart, whereas the other two, which are epistemically negative, do not have such counterparts, at least not that are particularly interesting as evidence. Accounting for negative mechanistic reasoning in EBM is therefore partly different from accounting for positive mechanistic reasoning. Each negative type corresponds to a range of evidential strengths, and it is argued that there are differences with respect to the typical strengths. The variety of negative mechanistic reasoning should be acknowledged in EBM, and presents a serious challenge to proponents of so-called medical hierarchies of evidence. (shrink)

Intentional sampling methods are non-probabilistic procedures that select a group of individuals for a sample with the purpose of meeting specific prescribed criteria. Intentional sampling methods are intended for exploratory research or pilot studies where tight budget constraints preclude the use of traditional randomized representative sampling. The possibility of subsequently generalize statistically from such deterministic samples to the general population has been the issue of long standing arguments and debates. Nevertheless, the intentional sampling techniques developed in this paper explore pragmatic (...) strategies for overcoming some of the real or perceived shortcomings and limitations of intentional sampling in practical applications. (shrink)

Decoupling is a general principle that allows us to separate simple components in a complex system. In statistics, decoupling is often expressed as independence, no association, or zero covariance relations. These relations are sharp statistical hypotheses, that can be tested using the FBST - Full Bayesian Significance Test. Decoupling relations can also be introduced by some techniques of Design of Statistical Experiments, DSEs, like randomization. This article discusses the concepts of decoupling, randomization and sparsely connected statistical models in the epistemological (...) framework of cognitive constructivism. (shrink)

This chapter provides an introduction to the study of the philosophical notions of mechanisms and causality in biology and economics. This chapter sets the stage for this volume, Mechanism and Causality in Biology and Economics, in three ways. First, it gives a broad review of the recent changes and current state of the study of mechanisms and causality in the philosophy of science. Second, consistent with a recent trend in the philosophy of science to focus on scientific practices, it in (...) turn implies the importance of studying the scientific methods employed by researchers. Finally, by way of providing an overview of each chapter in the volume, this chapter demonstrates that biology and economics are two fertile fields for the philosophy of science and shows how biological and economic mechanisms and causality can be synthesized. (shrink)

The thesis consists of an introduction and five papers. The introduction gives a brief historical survey of empirical investigations into the effectiveness of medicinal interventions, as well as surveys of the concept of evidence and of the history and philosophy of experiments. The main ideas of the EBM movement are also presented. Paper I: Concerns have been raised that clinical trials do not offer reliable evidence for some types of treatment, in particular for highly individualised treatments, for example traditional homeopathy. (...) With respect to individualised treatments, it is argued that such concerns are unfounded. There are two minimal conditions related to the nature of the treatments that must be fulfilled for evaluability in a clinical trial, namely the proper distinction of treatment groups and the elimination of confounding variables or variations. These conditions do not preclude the testing of individualised medicine. Paper II: Traditionally, mechanistic reasoning has been assigned a negligible role in the EBM literature. When discussed, mechanistic reasoning has almost exclusively been positive – both in an epistemic sense of claiming that there is a mechanistic chain and in a health-related sense of there being claimed benefits for the patient. Negative mechanistic reasoning has been neglected. I distinguish three main types of negative mechanistic reasoning and subsume them under a new definition. One of the three distinguished types, which is negative only in the health-related sense, has a corresponding positive counterpart, whereas the other two, which are epistemically negative, do not have such counterparts, at least not that are particularly interesting as evidence. Accounting for negative mechanistic reasoning in EBM is therefore partly different from accounting for positive mechanistic reasoning. Paper III: Evidence hierarchies are lists of investigative strategies ordered with regard to the claimed strength of evidence. They have been used for a couple of decades within EBM, particularly for the assessment of evidence for treatment recommendations, but they remain controversial. An under-investigated question is what the order in the hierarchy means. Four interpretations of the order are distinguished and discussed. The two most credible ones are, in rough terms, “typically stronger” and “ideally stronger”. The GRADE framework seems to be based on the “typically stronger” reading. Even if the interpretation of an evidence hierarchy were established, hierarchies appear to be rather unhelpful for the task of evidence aggregation. However, specifying the intended order relation may help sort out disagreements. Paper IV: There are three main arguments for randomisation that connect inseparably to theoretical concepts: Randomisation is useful for performing null hypothesis testing. Randomisation is needed for plausible causal inferences from treatment to effect. Randomisation is acceptable and computationally convenient in a Bayesian setting. A critical scrutiny of these arguments shows that is acceptable in the context of clinical trials. As for, it is argued that randomisation only provides weak reasons for drawing causal inferences in the context of real clinical trials. Argument is weak because it is controversial among Bayesians, and because formally Bayesian analyses of trial results are rarely asked for. Paper V: Practical arguments for randomisation are arguments with no necessary connections to theoretical frameworks like null hypothesis testing or causal inferences. Four common practical arguments in the context of clinical trials are distinguished and assessed: Randomisation contributes to allocation concealment. Randomisation contributes to the baseline balance of treatment groups. Randomisation decreases self-selection bias. Randomisation removes allocation bias. Argument is rejected. Arguments and are approved. Argument is rejected if it is formulated so as to be independent from and, but it is true that randomisation contributes to balance through the mechanisms mentioned in and. It is judged that may be the strongest single argument. (shrink)