The budding notion of sustainability is analyzed using the notions of an interdisciplinary versus a multidisciplinary field by Lindley Darden and Nancy Maul.

In this paper I provide a frequentist philosophical-methodological solution for the stopping rule problem presented by Lindley & Phillips in 1976, which is settled in the ecological realm of testing koalas’ sex ratio. I deliver criteria for discerning a stopping rule, an evidence and a model that are epistemically more appropriate for testing the hypothesis of the case studied, by appealing to physical notion of probability and by analyzing the content of possible formulations of evidence, assumptions of models and (...) meaning of the ecological hypothesis. First, I show the difference in the evidence taken into account in different frequentist sampling procedures presented in the problem. Next, I discuss the inapplicability of the Carnapian principle of total evidence in deciding which formulation of evidence associated with a given sampling procedure and statistical model is epistemically more appropriate for testing the hypothesis in question. Then I propose a double-perspective (evidence and model) frequentist solution based on the choice of evidence which better corresponds to the investigated ecological hypothesis, as well as on the choice of a model that embraces less unrealistic ontological assumptions. Finally, I discuss two perspectives of the stopping rule dependence. (shrink)

This is the text of The Lindley Lecture for 1987, given by John McDowell, a South African philosopher.

The concept of mechanism in biology has three distinct meanings. It may refer to a philosophical thesis about the nature of life and biology (‘mechanicism’), to the internal workings of a machine-like structure (‘machine mechanism’), or to the causal explanation of a particular phenomenon (‘causal mechanism’). In this paper I trace the conceptual evolution of ‘mechanism’ in the history of biology, and I examine how the three meanings of this term have come to be featured in the philosophy of biology, (...) situating the new ‘mechanismic program’ in this context. I argue that the leading advocates of the mechanismic program (i.e., Craver, Darden, Bechtel, etc.) inadvertently conflate the different senses of ‘mechanism’. Specifically, they all inappropriately endow causal mechanisms with the ontic status of machine mechanisms, and this invariably results in problematic accounts of the role played by mechanism-talk in scientific practice. I suggest that for effective analyses of the concept of mechanism, causal mechanisms need to be distinguished from machine mechanisms, and the new mechanismic program in the philosophy of biology needs to be demarcated from the traditional concerns of mechanistic biology. (shrink)

Leuridan (2011) questions whether mechanisms can really replace laws at the heart of our thinking about science. In doing so, he enters a long-standing discussion about the relationship between the mech-anistic structures evident in the theories of contemporary biology and the laws of nature privileged especially in traditional empiricist traditions of the philosophy of science (see e.g. Wimsatt 1974; Bechtel and Abrahamsen 2005; Bogen 2005; Darden 2006; Glennan 1996; MDC 2000; Schaffner 1993; Tabery 2003; Weber 2005). In our view, (...) Leuridan misconstrues this discussion. His weak positive claim that mechanistic sciences appeal to generalizations is true but uninteresting. His stronger claim, that all causal claims require laws, is unsupported by his arguments. Though we proceed by criticizing Leuridan’s arguments, our greater purpose is to embellish his arguments in order to show how thinking about mechanisms enriches and transforms old philosophical debates about laws in biology and provides new insights into how generalizations afford prediction, explanation and control. (shrink)

The Morris water maze has been put forward in the philosophy of neuroscience as an example of an experimental arrangement that may be used to delineate the cognitive faculty of spatial memory (e.g., Craver and Darden, Theory and method in the neurosciences, University of Pittsburgh Press, Pittsburgh, 2001; Craver, Explaining the brain: Mechanisms and the mosaic unity of neuroscience, Oxford University Press, Oxford, 2007). However, in the experimental and review literature on the water maze throughout the history of its (...) use, we encounter numerous responses to the question of “what” phenomenon it circumscribes ranging from cognitive functions (e.g., “spatial learning”, “spatial navigation”), to representational changes (e.g., “cognitive map formation”) to terms that appear to refer exclusively to observable changes in behavior (e.g., “water maze performance”). To date philosophical analyses of the water maze have not been directed at sorting out what phenomenon the device delineates nor the sources of the different answers to the question of what. I undertake both of these tasks in this paper. I begin with an analysis of Morris’s first published research study using the water maze and demonstrate that he emerged from it with an experimental learning paradigm that at best circumscribed a discrete set of observable changes in behavior. However, it delineated neither a discrete set of representational changes nor a discrete cognitive function. I cite this in combination with a reductionist-oriented research agenda in cellular and molecular neurobiology dating back to the 1980s as two sources of the lack of consistency across the history of the experimental and review literature as to what is under study in the water maze. (shrink)

Taking as starting point Kuhn’s analysis of science textbooks and its application to Sinnott and Dunn’s (1925), it will be discussed the problem of the existence of laws in biology. In particular, it will be showed, in accordance with the proposals of Darden (1991) and Schaffner (1980, 1986, 1993), the relevance of the exemplars, diagrammatically or graphically represented, in the way in which is carried out the teaching and learning process of classical genetics, inasmuch as the information contained in (...) them, indispensable for the right development of that process, exceeds the information contained in the “laws” linguistically articulated and presented in the textbooks. However, it will be maintained that the information is implicit in the law that according to the structuralist concept of fundamental law and the reconstruction of genetics presented by Balzer & Dawe (1990), and later developed by Balzer & Lorenzano (1997) and Lorenzano (1995, 2000, 2002a) could be considered the fundamental law of classical genetics,the law of matching, clearly identified in this paper. (shrink)

This is the text of The Lindley Lecture for 1983, given by Hilary Putnam, an American philosopher.

This paper generalises an argument for probabilism due to Lindley [9]. I extend the argument to a number of non-classical logical settings whose truth-values, seen here as ideal aims for belief, are in the set $\{0,1\}$, and where logical consequence $\models $ is given the “no-drop” characterization. First I will show that, in each of these settings, an agent’s credence can only avoid accuracy-domination if its canonical transform is a (possibly non-classical) probability function. In other words, if an agent (...) values accuracy as the fundamental epistemic virtue, it is a necessary requirement for rationality that her credence have some probabilistic structure. Then I show that for a certain class of reasonable measures of inaccuracy, having such a probabilistic structure is sufficient to avoid accuracy-domination in these non-classical settings. (shrink)

According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of (...) scientific explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)

One is occasionally reminded of Foucault's proclamation in a 1970 interview that "perhaps, one day this century will be known as Deleuzian." Less often is one compelled to update and restart with a supplementary counter-proclamation of the mathematician, David Lindley: "the twenty-first century would be a Bayesian era..." The verb tenses of both are conspicuous. // To critically attend to what is today often feared and demonized, but also revered, deployed, and commonly referred to as algorithm(s), one cannot avoid (...) the mathematical and philosophical legacies of probability. // But attending to these probabilistic or Bayesian legacies must include an undeniable theological legacy in which they remain entangled. // We are not, today, discovering quirky theological metaphors in contemporary technics. It's the other way around. The technologies are mere metaphors of past theologies. (shrink)

Truths will be defined as an agreement on uncertainties, the consensus over matters of empirical and social nature such as mathematics, physics or economics. As illustrated by Dennis Lindley , ‘individuals tend to know things to be true and false but the extent of this truth and falsity would always remain unknown’. Leading individuals to a permanent state of stress, uncertainty becomes a risk for the social community. Problems could not be presumed to be solvable as any kind of (...) solution would be perceived as uncertain. The struggle for solutions would develop into a state of insecurity and conflict where no individual could trust the answers given by any other member of the community. To prevent a ‘war of all against all’ that would cause anxiety and permanent conflict, it will become an essential duty for the social community to diminish uncertainty by imposing truths. With those, individuals can be reassured about the certainty of their knowledge and use truths as a resolution tool for any dispute that might occur within the social space. For the purpose of social peace, truths will therefore be every outcome of the process through which uncertainty is transformed into an agreed form of knowledge. “Gravity”, “Death” and “God” will all be considered truths as they represent a form of agreement over different domains of the human and social life. It is not the intention of this essay to examine each of the truths separately but rather, to analyse them all together in order to formulate a hypothesis for all empirical and social matters. (shrink)

This essay articulates a conception of responsibility and excuse in terms of the fair opportunity to avoid wrongdoing and explores its implications for insanity, incompetence, and psychopathy. The fair opportunity conception factors responsibility into conditions of normative competence and situational control and factors normative competence into cognitive and volitional capacities. This supports a conception of incompetence that recognizes substantial impairment of either cognitive or volitional capacities as excusing, provided the agent is not substantially responsible for her own incompetence. This conception (...) helps frame the question whether psychopathy is excusing. The most common rationale for excusing psychopathy appeals to claims about cognitive incompetence. However, there are good philosophical and empirical reasons to be skeptical that psychopaths lack the relevant cognitive capacities. There is more to be said for a volitional rationale for excuse. The crucial question here is whether the problems psychopaths have with impulse control and conforming their behavior to the relevant moral and criminal norms are systematic enough to demonstrate genuine volitional incompetence. The available empirical evidence should leave us skeptical about the merits of this volitional rationale for excuse. (shrink)