The quality of doctoral-level chemistry (N=145), computer science (N=58), geoscience (N=91), mathematics (N=115), physics (N=123), and statistics/biostatistics (N=64) programs at United States universities was assessed, using 16 measures. These measures focused on variables related to: program size; characteristics of graduates; reputational factors (scholarly quality of faculty, effectiveness of programs in educating research scholars/scientists, improvement in program quality during the last 5 years); university library size; research support; and publication records. Chapter I discusses prior attempts to assess quality in graduate (...) education, development of the study plans, and the selection of disciplines and programs to be evaluated. Chapter II discusses the methodology used, focusing on each of the assessment measures. Chapters III to VIII present, respectively, findings from the analyses of the chemistry, computer science, geoscience, mathematics, physics, and statistics/biostatistics programs. Chapter IX includes a summary of results, correlations among measures, several additional analyses, and suggestions for future studies. Among the findings reported are those indicating that mathematics programs had, on the average, the largest number of faculty (N=33) in December 1980 followed closely by physics (N=28) and chemistry (N=23), and that 80 percent of computer science students had job commitments by graduation. (Survey instruments and supporting documentation are included in appendices.) (JN). (shrink)

The quality of doctoral-level biochemistry (N=139), botany (N=83), cellular/molecular biology (N=89), microbiology (N=134), physiology (N=101), and zoology (N=70) programs at United States universities was assessed, using 16 measures. These measures focused on variables related to: (1) program size; (2) characteristics of graduates; (3) reputational factors (scholarly quality of faculty, effectiveness of programs in educating research scholars/scientists, improvement in program quality during the last 5 years); (4) university library size; (5) research support; and (6) publication records. Chapter I discusses prior attempts (...) to assess quality in graduate education, development of the study plans, and the selection of disciplines and programs to be evaluated. Chapter II discusses the methodology used, focusing on each of the assessment measures. Chapters III to VIII present, respectively, findings from the analyses of the biochemistry, botany, cellular/molecular biology, microbiology, physiology, and zoology programs. Chapter IX includes a summary of results, correlations among measures, several additional analyses, and suggestions for future studies. Among the findings reported are those indicating that cellular/molecular biology programs had, on the average, the largest number of faculty and that students in cellular/molecular biology, biology, biochemistry, microbiology, and physiology received a relatively high fraction of financial support. (Survey instruments and supporting documentation are included in appendices.) (JN). (shrink)

This volume addresses relations between macroscopic and microscopic description; essential roles of visualization and representation in chemical understanding; historical questions involving chemical concepts; the impacts of chemical ideas on wider cultural concerns; and relationships between contemporary chemistry and other sciences. The authors demonstrate, assert, or tacitly assume that chemical explanation is functionally autonomous. This volume should he of interest not only to professional chemists and philosophers, but also to workers in medicine, psychology, and other fields in which relationships between explanations (...) based on diverse levels of description and investigation are important. (Listed on Google books). (shrink)

This paper considers the question of whether the influential distinction between levels of explanation introduced by David Marr can be used as a general framework for contemplating levels of explanation in cognitive sciences. Marr introduced three levels at which we can explain cognitive processes: the computational, algorithmic, and implementational levels. Some argue that Marr’s levels of explanation can only be applied to modular cognitive systems. However, since many psychological processes are non-modular, it seems that Marr’s (...) levels of explanation cannot explain such psychological processes. To show that the latter claim is not convincing, the paper draws upon an influential paradigm from cognitive sciences that is based on the principle of free energy. Based on this paradigm, the paper argues that even non-modular psychological processes can be computationally analyzed and algorithmically implemented. The conclusion of the paper is that, at least under the assumption that the func- tion of the mind is to minimize free energy, Marr’s levels of explanation can be successfully used as a general framework for understanding psychological processes at different levels of description. (shrink)

The notion of levels has been widely used in discussions of cognitive science, especially in discussions of the relation of connectionism to symbolic modeling of cognition. I argue that many of the notions of levels employed are problematic for this purpose, and develop an alternative notion grounded in the framework of mechanistic explanation. By considering the source of the analogies underlying both symbolic modeling and connectionist modeling, I argue that neither is likely to provide an adequate analysis (...) of processes at the level at which cognitive theories attempt to function: One is drawn from too low a level, the other from too high a level. If there is a distinctly cognitive level, then we still need to determine what are the basic organizational principles at that level. (shrink)

It is the aim of this paper to develop and defend an interpretation of level of scientific discipline within the truth-maker framework. In particular, I exploit the mereological relation of proper parthood, which is integral to truth-maker semantics, in order to provide an account of scientific level.

The subject of this edited volume is the idea of levels of organization: roughly, the idea that the natural world is segregated into part-whole relationships of increasing spatiotemporal scale and complexity. The book comprises a collection of essays that raise the idea of levels into its own topic of analysis. Owing to the wide prominence of the idea of levels, the scope of the volume is aimed at theoreticians, philosophers, and practicing researchers of all stripes in the (...) life sciences. The volume’s contributions reflect this diversity, and draw from fields such as developmental biology, evolutionary biology, molecular biology, ecology, cell biology, and neuroscience. The book presents wide-ranging novel insights on causation and levels, the hierarchical structure of evolution, the role of levels in biological theory, and more. (shrink)

This article introduces a model of levels of analysis applied to statements found in philosophical, scientific, and religious discourses in order to facilitate a more accurate description of the relation between science and religion. The empirical levels prove to be the most crucial for the relation between science and religion, because they include statements that are important parts of both scientific and religious discourse, whereas statements from metaphysical levels are only important in terms of religion (...) and are neutral in relation to particular scientific theories. In particular, the rejection of certain ontological assumptions behind special divine action logically entails the rejection of the literal meaning of empirical statements describing special open expression of supernatural factors in nature. Such a rejection also entails an essential revision of many religious systems of beliefs, including traditional Christian theism. (shrink)

This book offers a unique perspective on one of the deepest questions about the world we live in: is reality multi-leveled, or can everything be reduced to some fundamental ‘flat’ level? This deep philosophical issue has widespread implications in philosophy, since it is fundamental to how we understand the world and the basic entities in it. Both the notion of ‘levels’ within science and their ontological implications are issues that are underexplored in the philosophical literature. The volume reconsiders (...) the view that reality contains many levels and opens new ways to understand the ontological status of the special sciences. The book focuses on major open questions that arise at the foundations of cognitive science, cognitive psychology, brain science and other special sciences, in particular with respect to the physical foundations of these sciences. For example: Is the mental computational? Do brains compute? How can the special sciences be autonomous from physics, grounded in, or based on, physics and at the same time irreducible to physics? The book is an important read for scientists and philosophers alike. It is of interest to philosophers of science, philosophers of mind and biology interested in the notion of levels, but also to psychologists, cognitive scientists and neuroscientists investigating such issues as the precise relation of the mental to the underlying neural structures and the appropriate approach to study it. (shrink)

David Marr provided an influential account of levels of description in classical cognitive science. In this paper we contrast Marr'ent with some alternatives that are suggested by the recent emergence of connectionism. Marr's account is interesting and important both because of the levels of description it distinguishes, and because of the way his presentation reflects some of the most basic, foundational, assumptions of classical AI-style cognitive science. Thus, by focusing on levels of description, one can (...) sharpen foundational differences between classicism and potential non-classical conceptions of mentality that might emerge under the rubric of connectionism. (shrink)

David Marr provided an influential account of levels of description in classical cognitive science. In this paper we contrast Marr'ent with some alternatives that are suggested by the recent emergence of connectionism. Marr's account is interesting and important both because of the levels of description it distinguishes, and because of the way his presentation reflects some of the most basic, foundational, assumptions of classical AI-style cognitive science . Thus, by focusing on levels of description, one (...) can sharpen foundational differences between classicism and potential non-classical conceptions of mentality that might emerge under the rubric of connectionism. (shrink)

Baumard proposes that life history slowing in populations over time is the principal driver of innovation rates. We show that this is only true of micro-innovation rates, which reflect cognitive and economic specialization as an adaptation to high population density, and not macro-innovation rates, which relate more to a population's level of general intelligence.

Scientific data are often subjected to two contradictory over-simplifications. People who have no personal experience in science often say that a certain idea has been scientifically established and feel that the question is therewith settled. They do not distinguish among methods, or generalizations in different fields. This implies that all science is infallible. The other oversimplification comes from the specialist; he may dismiss the work of men who study the problems approaching his own but who use methods different (...) from his. This view implies that only one type of scientific investigation is really sound. Both groups are wrong, for science is neither infallible nor wholly untrustworthy. In fact, science as an abstract whole is nothing; it is the name given collectively to all methods which men have used to explore natural processes and the results obtained by the use of such methods. Some problems are sufficiently simple and accessible to be explored in detail while others can be treated only after a set of postulates have been set as a starting point. A mechanism must be established within which it is possible to deal with the problems at hand. In other words, there are levels of scientific research which may be arranged in a series based on increasing assumptions. The more complex levels are formed by assuming the data and methods of those simpler and adding to them a new set of assumptions with the aid of which it is possible to treat the phenomena to be studied. Material cannot be carried directly from one level to another unless attention is given to the premises on which the conclusions have been drawn. Since such attention is not always given, entire fields of research have sometimes been brought into suspicion on the part of those working in what they themselves style “a more fundamental field.” Yet there may be data available at a different level which, when properly used, would be of value in their own work. (shrink)

Food safety risk is becoming a vital issue for public health, and improving public awareness of FSR through social media is necessary. This study aims to explore specific mechanisms of FSR perception; it first categorizes 19 risk characteristics into two variables, dread and efficacy, and then examines how social media use affects perceived FSR through both variables. Additionally, the study explores the moderating effects of source credibility and science literacy on the mechanisms of FSR perception. Based on a nationwide (...) online survey of more than six salient food safety issues in China, the study found that exposure to food safety risk information on social media can help improve perceived FSR based on the proposed “dread–efficacy processing model”, where dread stimulates perceived risk, while efficacy suppresses risk perception. Moreover, source credibility intensifies the effect of social media use on efficacy appraisal, whereas science literacy exerts a “double-weakening” influence on dread appraisal. Theoretical and practical implications of the findings are discussed. (shrink)

Burkart et al. present a paradox – general factors of intelligence exist among individual differences (g) in performance in several species, and also at the aggregate level (G); however, there is ambiguous evidence for the existence of g when analyzing data using a mixed approach, that is, when comparing individuals of different species using the same cognitive ability battery. Here, we present an empirical solution to this paradox.

Cognitive science began as a multidisciplinary endeavor to understand how the mind works. Since the beginning, cognitive scientists have been asking questions about the right methodologies and levels of explanation to pursue this goal, and make cognitive science a coherent science of the mind. Key questions include: Is there a privileged level of explanation in cognitive science? How do different levels of explanation fit together, or relate to one another? How should explanations at one (...) level inform or constrain explanations at some other level? Can the different approaches to the mind, brain, and culture be unified? The aim of this issue of topiCS is to provide a platform for discussing different answers to such questions and to facilitate a better understanding between the different strands of thinking about the right levels of explanation in cognitive science. (shrink)

Over the past century or more, cognitive neuropsychologists have discussed many of the issues raised in this volume. On the basis of this literature, we argue that autism is not a single homogeneous condition, and so can have no single cause. Instead, each of its symptoms has a cause, and the proper study of autism is the separate study of each of these symptoms and its cause. We also offer evidence to support the radical view advanced by Stoljar and Gold (...) in this volume, namely, that in explaining such syndromes the cognitive level of explanation has priority over the neuroscientific. (shrink)

Philosophers and scientists often describe theories, laws, and explanations as applying to the world at different 'levels'. The idea of a 'level of application' is often used to demarcate disciplinary or sub-disciplinary boundaries in the sciences. For instance, stoichiometric laws and quantum mechanical laws might be said to describe chemical phenomena at different levels. More generally, the idea of levels is used to distinguish more fundamental laws or theories from less fundamental ones: more fundamental theories are those (...) that apply at more fundamental levels. (shrink)

In this study, we aimed to investigate how prospective science teachers, who participated in a series of explicit-reflective activities for NOS teaching, understood "science in a social and cultural context" in the context of a biographical documentary film. We adopted a phenomenological approach. The data were analyzed descriptively by considering the aspects of nature of science and the levels of understanding as defined in Dilthey's hermeneutic approach. In this way, we determined participants’ levels of hermeneutic (...) understanding regarding the nature of science. The findings show that the participants regarded science within the framework of aspects of the consensus view blended with somewhat authentic interpretations and at a basic level of understanding from the point of view of hermeneutics. This finding highlights the importance of integrating the hermeneutic approach into the teaching process in understanding science. (shrink)

Scientists have always attempted to explain the world in terms of a few unifying principles. In the fifth century B.C. Democritus boldly claimed that reality is simply a collection of indivisible and eternal parts or atoms. Over the centuries his doctrine has remained a landmark, and much progress in physics is due to its distinction between subjective perception and objective reality. This book discusses theory reduction in physics, which states that the whole is nothing more than the sum of its (...) parts: the properties of things are directly determined by their constituent parts. Reductionism deals with the relation between different theories that address different levels of reality, and uses extrapolations to apply that relation in different sciences. Reality shows a complex structure of connections, and the dream of a unified interpretation of all phenomena in several simple laws continues to attract anyone with genuine philosophical and scientific interests. If the most radical reductionist point of view is correct, the relationship between disciplines is strictly inclusive: chemistry becomes physics, biology becomes chemistry, and so on. Eventually, only one science, indeed just a single theory, would survive, with all others merging in the Theory of Everything. Is the current coexistence of different sciences a mere historical venture which will end when the Theory of Everything has been established? Can there be a unified description of nature? Rather than an analysis of full reductionism, this book focuses on aspects of theory reduction in physics and stimulates reflection on related questions: is there any evidence of actual reduction? Are the examples used in the philosophy of science too simplistic? What has been endangered by the search for (the) ultimate truth? Has the dream of reductionist reason created any monsters? Is big science one such monster? What is the point of embedding science Y within science X, if predictions cannot be made on that basis? (shrink)

In the last two centuries, our world would have been a safer place if philosophers such as Rousseau, Marx, and Nietzsche had not given intellectual encouragement to the radical ideologies of Jacobins, Stalinists, and fascists. Maybe the world would have been better off, from the standpoint of sound practice, if philosophers had engaged in only modest, decent theory, as did John Stuart Mill. Yet, as Ronald Beiner contends, the point of theory is not to think safe thoughts; the point is (...) to open intellectual horizons. In Philosophy in a Time of Lost Spirit, Beiner reflects on the dualism of theory and practice. The purpose of the theorist is not to offer sensible guidance on the conduct of social life but to test the boundaries of our vision of social order. Whereas the liberal citizen should embody the practical virtues of prudence and moderation, the theorist should be radical, probing, and immoderate. Looking back at the liberal-communitarian debate of the 1980s, Beiner recognizes that the antidote to our spiritless times lies neither in the embrace of community over individualism nor of individualism over community: both individual and community need to be submitted to radical questioning. It is by exposing ourselves to the challenge of fearless thinking encountered at the philosophical extremities that we are most likely to understand our own world at a deeper level. In this collection of essays and reviews, Ronald Beiner helps us to think critically about the thought-worlds of our foremost contemporary thinkers, including Hannah Arendt, Allan Bloom, Michel Foucault, Hans-Georg Gadamer, J¦rgen Habermas, Will Kymlicka, Christopher Lasch, Richard Rorty, Judith Shklar, Leo Strauss, Charles Taylor, and Michael Walzer. (shrink)

The idea of levels of organization plays a central role in the philosophy of the life sciences. In this article, I first examine the explanatory goals that have motivated accounts of levels of organization. I then show that the most state-of-the-art and scientifically plausible account of levels of organization, the account of levels of mechanism proposed by Bechtel and Craver, is fundamentally problematic. Finally, I argue that the explanatory goals can be reached by adopting a deflationary (...) approach, where levels of organization give way to more well-defined and fundamental notions, such as scale and composition. (shrink)

Over the past century or more, cognitive neuropsychologists have discussed many of the issues raised in this volume. On the basis of this literature, we argue that autism is not a single homogeneous condition, and so can have no single cause. Instead, each of its symptoms has a cause, and the proper study of autism is the separate study of each of these symptoms and its cause. We also offer evidence to support the radical view advanced by Stoljar and Gold (...) in this volume, namely, that in explaining such syndromes the cognitive level of explanation has priority over the neuroscientific. (shrink)

A common argument against explanatory reductionism is that higher‐level explanations are sometimes or always preferable because they are more general than reductive explanations. Here I challenge two basic assumptions that are needed for that argument to succeed. It cannot be assumed that higher‐level explanations are more general than their lower‐level alternatives or that higher‐level explanations are general in the right way to be explanatory. I suggest a novel form of pluralism regarding levels of explanation, according to which explanations at (...) different levels are preferable in different circumstances because they offer different types of generality, which are appropriate in different circumstances of explanation. (shrink)

Unity of science was once a very popular idea among both philosophers and scientists. But it has fallen out of fashion, largely because of its association with reductionism and the challenge from multiple realisation. Pluralism and the disunity of science are the new norm, and higher-level natural kinds and special science laws are considered to have an important role in scientific practice. What kind of reductionism does multiple realisability challenge? What does it take to reduce one phenomenon (...) to another? How do we determine which kinds are natural? What is the ontological basis of unity? In this Element, Tuomas Tahko examines these questions from a contemporary perspective, after a historical overview. The upshot is that there is still value in the idea of a unity of science. We can combine a modest sense of unity with pluralism and give an ontological analysis of unity in terms of natural kind monism. This title is available as Open Access on Cambridge Core. (shrink)

Indeed, this is the first serious book-length study of the subject by a philosopher of science.

This Research Topic aimed at deepening our understanding of the levels and explanations that are of interest for cognitive sci- entists, neuroscientists, psychologists, behavioral scientists, and philosophers of science. Indeed, contemporary developments in neuroscience and psy- chology suggest that scientists are likely to deal with a multiplicity of levels, where each of the different levels entails laws of behavior appropriate to that level (Berntson et al., 2012). Also, gathering and modeling data at the different levels (...) of analysis is not suffi- cient: the integration of information across levels of analysis is a crucial issue. Given such state of affairs, a number of interesting questions arise. How can the autonomy of explanatory levels be properly understood in behavioral explanation? Is reductionism a satis- factory strategy? How can high-level and low-level models be constrained in order to be actually explanatory of both behav- ioral and neurological or molecular evidence? What is the kind of relationship between those models? (shrink)

Levels of organization are structures in nature, usually defined by part-whole relationships, with things at higher levels being composed of things at the next lower level. Typical levels of organization that one finds in the literature include the atomic, molecular, cellular, tissue, organ, organismal, group, population, community, ecosystem, landscape, and biosphere levels. References to levels of organization and related hierarchical depictions of nature are prominent in the life sciences and their philosophical study, and appear not (...) only in introductory textbooks and lectures, but also in cutting-edge research articles and reviews. In philosophy, perennial debates such as reduction, emergence, mechanistic explanation, interdisciplinary relations, natural selection, and many other topics, also rely substantially on the notion. -/- Yet, in spite of the ubiquity of the notion, levels of organization have received little explicit attention in biology or its philosophy. Usually they appear in the background as an implicit conceptual framework that is associated with vague intuitions. Attempts at providing general and broadly applicable definitions of levels of organization have not met wide acceptance. In recent years, several authors have put forward localized and minimalistic accounts of levels, and others have raised doubts about the usefulness of the notion as a whole. -/- There are many kinds of ‘levels’ that one may find in philosophy, science, and everyday life—the term is notoriously ambiguous. Besides levels of organization, there are levels of abstraction, realization, being, analysis, processing, theory, science, complexity, and many others. In this article, the focus will be on levels of organization and debates associated with them, and other kinds of levels will only be discussed when they are relevant to this main topic. (shrink)

Open peer commentary on the article “Second-Order Science of Interdisciplinary Research: A Polyocular Framework for Wicked Problems” by Hugo F. Alrøe & Egon Noe. Upshot: I critically assess Alrøe and Noe’s plea for a “second-order science of interdisciplinary research” from the perspective of a consistently naturalized philosophy of science, arguing that the latter precludes the “levels view” of science implied by the former. I also suggest we avoid the term “polyocularity” as it perpetuates the persistent (...) bias toward vision in our scientific and philosophical understanding of human perception. (shrink)

In this paper Wimsatt's analysis of units of selection is taken as defining the units of selection question. A definition of levels of selection is offered and it is shown that the levels of selection question is quite different from the units of selection question. Some of the relations between units and levels are briefly explored. It is argued that the levels of selection question is the question relevant to explanatory concerns, and it is suggested that (...) it is the question relevant to ontological concerns. (shrink)

This book describes the framework of a new theory of science. Over the last hundred years, philosophy of science has developed its theory based on what philosophers perceived what science is and what scientists do. It does not address the basic questions that scientists care about. Thus, this book examines the conventional theories of philosophy of science from a completely different point of view and describes the most difficult problems that scientists are concerned about and how (...) science is conducted. This book is based on the lecture notes under the same title in Honors College at the junior level in UMASS Lowell. It is qualified as a required course in Art and Humanity for science and engineering majors. (shrink)

Some controversies in cognitive science, such as arguments about whether classical or distributed connectionist architectures best model the human cognitive system, reenact long‐standing debates in the philosophy of science. For millennia, philosophers have pondered whether mentality can submit to scientific explanation generally and to physical explanation particularly. Recently, positive answers have gained popularity. The question remains, though, as to the analytical level at which mentality is best explained. Is there a level of analysis that is peculiarly appropriate to (...) the explanation of either consciousness or mental contents? Are human consciousness, cognition, and conduct best understood in terms of talk about neurons and networks or schemas and scripts or intentions and inferences? If our best accounts make no appeal to our hopes or beliefs or desires, how do we square those views with our conception of ourselves as rational beings? Moreover, can models of physical processes explain our mental lives? Does mentality require a special level of rational or cognitive explanation, or is it best understood in terms of overall brain functioning or neuronal or molecular or even quantum activities – or any of a dozen levels of physical explanation in between? Also, regardless of how they compare with explanations cast at physical levels, what is the status of psychological explanations that appeal fundamentally to mental contents? (shrink)

Cet article défend l’idée que l’on peut distinguer quatre niveaux d’analyse au sein des sciences sociales (y compris l’économie) – à savoir, a) un niveau descriptif statistique, b) un niveau explicatif causal, c) un niveau explicatif téléologique, et d) un niveau téléologique prescriptif. Généralement, les sciences sociales ne considèrent que les niveaux a) et b). L’exclusion du niveau c) peut conduire à considérer comme des « anomalies » certains comportements qui ne sont pas compatibles avec des théories comme celle du (...) choix rationnel ou celle de l’utilité espérée – à savoir, des théories qui adoptent une attitude dite de « rationalité instrumentale ». Inclure le niveau c) dans la réflexion implique de considérer la « rationalité pratique » et cela rend ces anomalies « raisonnables ». L’article prend pour cadre théorique la notion de causalité et la téléologie d’Aristote. La première section introduit ces notions, tandis que la deuxième section explore les points de vue contemporains sur la causalité et la téléologie. La troisième section introduit des arguments pour établir la légitimité de l’usage des valeurs en sciences sociales. Cette étape est nécessaire, car les causes finales des explications téléologiques dans le domaine des choses humaines sont bien, en définitive, des valeurs. Ces discussions ouvrent la voie à l’introduction, dans la quatrième et dernière section, des quatre niveaux analytiques susmentionnés. Plus précisément, dans le cas de l’économie, cette discussion se fonde sur la classification des disciplines économiques chez Carl Menger. (shrink)

I begin by tracing some of the confusions regarding levels and reduction to a failure to distinguish two different principles according to which theories can be viewed as hierarchically arranged — epistemic authority and ontological constitution. I then argue that the notion of levels relevant to the debate between symbolic and connectionist paradigms of mental activity answers to neither of these models, but is rather correlative to the hierarchy of functional decompositions of cognitive tasks characteristic of homuncular functionalism. (...) Finally, I suggest that the incommensurability of the intentional and extensional vocabularies constitutes a strongprima facie reason to conclude that there is little likelihood of filling in the story of Bechtel''s missing level in such a way as to bridge the gap between such homuncular functionalism and his own model of mechanistic explanation. (shrink)

Philosophers and non-philosophers have been attracted to the idea that the world incorporates levels of being: higher-level items – ordinary objects, artifacts, human beings – depend on, but are not in any sense reducible to, items at lower levels. I argue that the motivation for levels stems from an implicit acceptance of a Picture Theory of language according to which we can ‘read off’ features of the world from ways we describe the world. Abandonment of the Picture (...) Theory opens the way to a ‘no levels’ conception of reality, a conception that honors anti-reductionist sentiments and preserves the status of the special sciences without the ontological baggage. (shrink)

An important lesson that philosophy can learn from the Turing Test and computer science more generally concerns the careful use of the method of Levels of Abstraction (LoA). In this paper, the method is first briefly summarised. The constituents of the method are “observables”, collected together and moderated by predicates restraining their “behaviour”. The resulting collection of sets of observables is called a “gradient of abstractions” and it formalises the minimum consistency conditions that the chosen abstractions must satisfy. (...) Two useful kinds of gradient of abstraction – disjoint and nested – are identified. It is then argued that in any discrete (as distinct from analogue) domain of discourse, a complex phenomenon may be explicated in terms of simple approximations organised together in a gradient of abstractions. Thus, the method replaces, for discrete disciplines, the differential and integral calculus, which form the basis for understanding the complex analogue phenomena of science and engineering. The result formalises an approach that is rather common in computer science but has hitherto found little application in philosophy. So the philosophical value of the method is demonstrated by showing how making the LoA of discourse explicit can be fruitful for phenomenological and conceptual analysis. To this end, the method is applied to the Turing Test, the concept of agenthood, the definition of emergence, the notion of artificial life, quantum observation and decidable observation. It is hoped that this treatment will promote the use of the method in certain areas of the humanities and especially in philosophy. (shrink)