Sarah Waterlow
- Published in print:
- 1982
- Published Online:
- October 2011
- ISBN:
- 9780198246565
- eISBN:
- 9780191681011
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198246565.003.0002
- Subject:
- Philosophy, Ancient Philosophy, Metaphysics/Epistemology
In Prior Analytics I.13, 32a18–20, Aristotle notes: ‘I say that the possible is that which is not necessary, but which, if we suppose it the case, has no impossible consequences’. Later he speaks as ...
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In Prior Analytics I.13, 32a18–20, Aristotle notes: ‘I say that the possible is that which is not necessary, but which, if we suppose it the case, has no impossible consequences’. Later he speaks as if he has given a definition of possibility, and the reference might be to the passage. Many have complained of circularity on the ground that the quoted statement spells out one modal concept in terms of the others. In connecting the modal and temporal concepts in the definition of possibility in the Analytics, the discussion takes the De Caello I.12 as the basis for a detailed exposition of Aristotelian modality. It traces the internal structure of Aristotle's concept of possibility relative to an actual state of things.Less
In Prior Analytics I.13, 32a18–20, Aristotle notes: ‘I say that the possible is that which is not necessary, but which, if we suppose it the case, has no impossible consequences’. Later he speaks as if he has given a definition of possibility, and the reference might be to the passage. Many have complained of circularity on the ground that the quoted statement spells out one modal concept in terms of the others. In connecting the modal and temporal concepts in the definition of possibility in the Analytics, the discussion takes the De Caello I.12 as the basis for a detailed exposition of Aristotelian modality. It traces the internal structure of Aristotle's concept of possibility relative to an actual state of things.
R. J. Hankinson
- Published in print:
- 2001
- Published Online:
- November 2003
- ISBN:
- 9780199246564
- eISBN:
- 9780191597572
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0199246564.003.0006
- Subject:
- Philosophy, Ancient Philosophy
In this chapter, Hankinson examines Aristotle's philosophy of science, or the logical structure of explanation as set out in the Posterior Analytics, and which is based on the theory of the syllogism ...
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In this chapter, Hankinson examines Aristotle's philosophy of science, or the logical structure of explanation as set out in the Posterior Analytics, and which is based on the theory of the syllogism worked out in the Prior Analytics. For Aristotle, definition is fundamental to the project of exhibiting science in its appropriate explanatory form, i.e. proceeding deductively from fundamental principles and axioms about the structure of things. Science and scientific explanation are for Aristotle construed realistically: science must mirror reality, and therefore theory always must cohere with observation and empirical investigation. Hankinson discusses Aristotle's qualitative physics of motion, on the basis of the doctrine of natural places, his account of chemical combination, and his cosmology, which is at once teleological in character, while being empirically adequate. Hankinson also discusses Aristotle's successors Theophrastus and Strato of Lampsacus: Theophrastus developed and refined Aristotle's methodology while bringing some scepticism to the ubiquitous application of teleology; Strato also tends more towards mechanistic explanations.Less
In this chapter, Hankinson examines Aristotle's philosophy of science, or the logical structure of explanation as set out in the Posterior Analytics, and which is based on the theory of the syllogism worked out in the Prior Analytics. For Aristotle, definition is fundamental to the project of exhibiting science in its appropriate explanatory form, i.e. proceeding deductively from fundamental principles and axioms about the structure of things. Science and scientific explanation are for Aristotle construed realistically: science must mirror reality, and therefore theory always must cohere with observation and empirical investigation. Hankinson discusses Aristotle's qualitative physics of motion, on the basis of the doctrine of natural places, his account of chemical combination, and his cosmology, which is at once teleological in character, while being empirically adequate. Hankinson also discusses Aristotle's successors Theophrastus and Strato of Lampsacus: Theophrastus developed and refined Aristotle's methodology while bringing some scepticism to the ubiquitous application of teleology; Strato also tends more towards mechanistic explanations.
Benjamin Alamar
- Published in print:
- 2013
- Published Online:
- November 2015
- ISBN:
- 9780231162920
- eISBN:
- 9780231535250
- Item type:
- book
- Publisher:
- Columbia University Press
- DOI:
- 10.7312/columbia/9780231162920.001.0001
- Subject:
- Sociology, Sport and Leisure
This book shows diverse organizations how to implement analytics into their decision-making strategies, especially as analytic tools grow increasingly complex. It provides a clear, easily digestible ...
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This book shows diverse organizations how to implement analytics into their decision-making strategies, especially as analytic tools grow increasingly complex. It provides a clear, easily digestible survey of the practice and a detailed understanding of analytics' vast possibilities. It explains how to evaluate different programs and put them to use. Using concrete examples from professional sports teams and case studies demonstrating the use and value of analytics in the field, the book designs a roadmap for managers, general managers, and other professionals as they build their own programs and teach their approach to others.Less
This book shows diverse organizations how to implement analytics into their decision-making strategies, especially as analytic tools grow increasingly complex. It provides a clear, easily digestible survey of the practice and a detailed understanding of analytics' vast possibilities. It explains how to evaluate different programs and put them to use. Using concrete examples from professional sports teams and case studies demonstrating the use and value of analytics in the field, the book designs a roadmap for managers, general managers, and other professionals as they build their own programs and teach their approach to others.
Jonathan Barnes
- Published in print:
- 2009
- Published Online:
- October 2011
- ISBN:
- 9780199568178
- eISBN:
- 9780191702037
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199568178.003.0005
- Subject:
- Philosophy, Ancient Philosophy, Logic/Philosophy of Mathematics
In his Elements, Euclid first sets down certain primary truths or axioms and then deduces from them a number of secondary truths or theorems. Before ever Euclid wrote, Aristotle had described and ...
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In his Elements, Euclid first sets down certain primary truths or axioms and then deduces from them a number of secondary truths or theorems. Before ever Euclid wrote, Aristotle had described and commended that rigorous conception of a science for which the Elements was to provide a perennial paradigm. All sciences, in Aristotle's view, ought to be presented as axiomatic deductive systems — that is one of the main messages of the Posterior Analytics. And the deductions which derive the theorems of any science from its axioms must be syllogisms — that is a main message of the Prior Analytics. He never says in so many words that logic is a science. Indeed, he never uses the formula ‘syllogistic science’, nor any near equivalent.Less
In his Elements, Euclid first sets down certain primary truths or axioms and then deduces from them a number of secondary truths or theorems. Before ever Euclid wrote, Aristotle had described and commended that rigorous conception of a science for which the Elements was to provide a perennial paradigm. All sciences, in Aristotle's view, ought to be presented as axiomatic deductive systems — that is one of the main messages of the Posterior Analytics. And the deductions which derive the theorems of any science from its axioms must be syllogisms — that is a main message of the Prior Analytics. He never says in so many words that logic is a science. Indeed, he never uses the formula ‘syllogistic science’, nor any near equivalent.
Ifan Shepherd and Gary Hearne
- Published in print:
- 2019
- Published Online:
- May 2020
- ISBN:
- 9781447348214
- eISBN:
- 9781447348269
- Item type:
- chapter
- Publisher:
- Policy Press
- DOI:
- 10.1332/policypress/9781447348214.003.0004
- Subject:
- Sociology, Social Research and Statistics
Data analytics have emerged in recent years as a family of overlapping, competing and hybridising products and practices. They have been championed by technology companies, academics, business users ...
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Data analytics have emerged in recent years as a family of overlapping, competing and hybridising products and practices. They have been championed by technology companies, academics, business users and governments alike, and in a short period of time have earned business developers and adopters billions of pounds in revenue and unprecedented levels of market domination. Data analytics have also provided distinct benefits in terms of an increasing democratisation of digital tools, but at the same time are giving rise to increasing levels of societal and governmental concern. This chapter has four aims: to help intelligent outsiders and old school data analysts make sense of the many competing methodologies and technologies that inhabit the data analytics ecosystem; to assist readers understand which of the many techniques and methodologies represent genuine additions to the state of the art rather than simply old wine in new bottles; to provide a brief overview of the software tools currently available for data analytics; and to identify societal issues and concerns that attend this family of technical and social practices, and the extent to which they are being adequately addressed by developers, users and society at large.Less
Data analytics have emerged in recent years as a family of overlapping, competing and hybridising products and practices. They have been championed by technology companies, academics, business users and governments alike, and in a short period of time have earned business developers and adopters billions of pounds in revenue and unprecedented levels of market domination. Data analytics have also provided distinct benefits in terms of an increasing democratisation of digital tools, but at the same time are giving rise to increasing levels of societal and governmental concern. This chapter has four aims: to help intelligent outsiders and old school data analysts make sense of the many competing methodologies and technologies that inhabit the data analytics ecosystem; to assist readers understand which of the many techniques and methodologies represent genuine additions to the state of the art rather than simply old wine in new bottles; to provide a brief overview of the software tools currently available for data analytics; and to identify societal issues and concerns that attend this family of technical and social practices, and the extent to which they are being adequately addressed by developers, users and society at large.
Andrew Piper
- Published in print:
- 2018
- Published Online:
- January 2019
- ISBN:
- 9780226568614
- eISBN:
- 9780226568898
- Item type:
- book
- Publisher:
- University of Chicago Press
- DOI:
- 10.7208/chicago/9780226568898.001.0001
- Subject:
- Literature, Criticism/Theory
For well over a century, academic disciplines have studied human behavior using quantitative information. Until recently, however, the humanities have remained largely immune to the use of data—or ...
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For well over a century, academic disciplines have studied human behavior using quantitative information. Until recently, however, the humanities have remained largely immune to the use of data—or vigorously resisted it. Thanks to new developments in computer science and natural language processing, literary scholars have embraced the quantitative study of literary works and have helped make Digital Humanities a rapidly growing field. But these developments raise a fundamental and as yet unanswered question: what is the meaning of literary quantity? This book answers that question across a variety of domains fundamental to the study of literature. It focuses on the elementary particles of literature, from the role of punctuation in poetry and the matter of plot in novels, to the study of topoi and the behavior of characters, to the nature of fictional language and the shape of a poet’s career. How does quantity affect our understanding of these categories? What happens when we look at 3,388,230 punctuation marks, 1.4 billion words, or 650,000 fictional characters? Does this change how we think about poetry, the novel, fictionality, character, the commonplace, or the writer’s career? In the course of answering these questions the book introduces readers to the analytical building blocks of computational text analysis and brings them to bear on fundamental concerns of literary scholarship.Less
For well over a century, academic disciplines have studied human behavior using quantitative information. Until recently, however, the humanities have remained largely immune to the use of data—or vigorously resisted it. Thanks to new developments in computer science and natural language processing, literary scholars have embraced the quantitative study of literary works and have helped make Digital Humanities a rapidly growing field. But these developments raise a fundamental and as yet unanswered question: what is the meaning of literary quantity? This book answers that question across a variety of domains fundamental to the study of literature. It focuses on the elementary particles of literature, from the role of punctuation in poetry and the matter of plot in novels, to the study of topoi and the behavior of characters, to the nature of fictional language and the shape of a poet’s career. How does quantity affect our understanding of these categories? What happens when we look at 3,388,230 punctuation marks, 1.4 billion words, or 650,000 fictional characters? Does this change how we think about poetry, the novel, fictionality, character, the commonplace, or the writer’s career? In the course of answering these questions the book introduces readers to the analytical building blocks of computational text analysis and brings them to bear on fundamental concerns of literary scholarship.
W.F.R. Hardie
- Published in print:
- 1980
- Published Online:
- October 2011
- ISBN:
- 9780198246329
- eISBN:
- 9780191680953
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198246329.003.0012
- Subject:
- Philosophy, Ancient Philosophy, Moral Philosophy
The expression ‘practical syllogism’ is used by commentators on Aristotle as a name for a process in which a rule is applied to a concrete situation, the application consisting in the thinker's doing ...
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The expression ‘practical syllogism’ is used by commentators on Aristotle as a name for a process in which a rule is applied to a concrete situation, the application consisting in the thinker's doing something, actually performing as an agent or producer. The rule prescribes things which should be done in specified types of situation; its verbal expression requires the use of an evaluative word like ‘good’ or ‘useful’ or of a prescriptive word like ‘should’ or ‘ought’. In terms of Aristotle's doctrine of the theoretical syllogism, as expounded in the Prior and Posterior Analytics, the thinking which precedes, or accompanies, practical rule-keeping can be expressed in the verbal form of a first-figure syllogism of the minor.Less
The expression ‘practical syllogism’ is used by commentators on Aristotle as a name for a process in which a rule is applied to a concrete situation, the application consisting in the thinker's doing something, actually performing as an agent or producer. The rule prescribes things which should be done in specified types of situation; its verbal expression requires the use of an evaluative word like ‘good’ or ‘useful’ or of a prescriptive word like ‘should’ or ‘ought’. In terms of Aristotle's doctrine of the theoretical syllogism, as expounded in the Prior and Posterior Analytics, the thinking which precedes, or accompanies, practical rule-keeping can be expressed in the verbal form of a first-figure syllogism of the minor.
William B. Rouse
- Published in print:
- 2019
- Published Online:
- September 2019
- ISBN:
- 9780198846420
- eISBN:
- 9780191881589
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198846420.001.0001
- Subject:
- Mathematics, Logic / Computer Science / Mathematical Philosophy
This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers ...
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This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what “data analytics” can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a “shared mental model” of computational modeling in the process, which will greatly enhance their chances of success.Less
This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what “data analytics” can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a “shared mental model” of computational modeling in the process, which will greatly enhance their chances of success.
David Charles
- Published in print:
- 2002
- Published Online:
- November 2003
- ISBN:
- 9780199256730
- eISBN:
- 9780191597183
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/019925673X.003.0003
- Subject:
- Philosophy, Ancient Philosophy
Aristotle, in Posterior Analytics B.10, separates three stages in scientific enquiry: (1) knowledge of the signification of the relevant terms, (2) knowledge of the existence of the kind, and (3) ...
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Aristotle, in Posterior Analytics B.10, separates three stages in scientific enquiry: (1) knowledge of the signification of the relevant terms, (2) knowledge of the existence of the kind, and (3) knowledge of the essence of the kind. One can, in all relevant cases, achieve the first stage of enquiry without (as yet) achieving the second or third stages. So, knowledge of the signification of the relevant terms does not essentially involve knowledge of the existence of the kind in question.Less
Aristotle, in Posterior Analytics B.10, separates three stages in scientific enquiry: (1) knowledge of the signification of the relevant terms, (2) knowledge of the existence of the kind, and (3) knowledge of the essence of the kind. One can, in all relevant cases, achieve the first stage of enquiry without (as yet) achieving the second or third stages. So, knowledge of the signification of the relevant terms does not essentially involve knowledge of the existence of the kind in question.
David Charles
- Published in print:
- 2002
- Published Online:
- November 2003
- ISBN:
- 9780199256730
- eISBN:
- 9780191597183
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/019925673X.003.0004
- Subject:
- Philosophy, Ancient Philosophy
Aristotle, in Posterior Analytics B.3–7, prepares for the three‐stage view by arguing that no one account can tell us both the essence of a kind and the signification of the term that names that ...
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Aristotle, in Posterior Analytics B.3–7, prepares for the three‐stage view by arguing that no one account can tell us both the essence of a kind and the signification of the term that names that kind. Here, he lays the foundation for the separation of two questions, which we would represent as follows: ‘What does “triangle” signify?’ and ‘What is the triangle?’ This distinction provides him with a way to address and resolve Meno's paradox of enquiry.Less
Aristotle, in Posterior Analytics B.3–7, prepares for the three‐stage view by arguing that no one account can tell us both the essence of a kind and the signification of the term that names that kind. Here, he lays the foundation for the separation of two questions, which we would represent as follows: ‘What does “triangle” signify?’ and ‘What is the triangle?’ This distinction provides him with a way to address and resolve Meno's paradox of enquiry.
David Charles
- Published in print:
- 2002
- Published Online:
- November 2003
- ISBN:
- 9780199256730
- eISBN:
- 9780191597183
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/019925673X.003.0008
- Subject:
- Philosophy, Ancient Philosophy
Aristotle argues in Posterior Analytics B.3–7 that accounts of definition unsupported by understanding of the explanatory structure of kinds are incapable of giving us knowledge of the nature of ...
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Aristotle argues in Posterior Analytics B.3–7 that accounts of definition unsupported by understanding of the explanatory structure of kinds are incapable of giving us knowledge of the nature of kinds. The formal or logical level of analysis needs to be supplemented by considerations drawn from a study of causes.Less
Aristotle argues in Posterior Analytics B.3–7 that accounts of definition unsupported by understanding of the explanatory structure of kinds are incapable of giving us knowledge of the nature of kinds. The formal or logical level of analysis needs to be supplemented by considerations drawn from a study of causes.
David Charles
- Published in print:
- 2002
- Published Online:
- November 2003
- ISBN:
- 9780199256730
- eISBN:
- 9780191597183
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/019925673X.003.0009
- Subject:
- Philosophy, Ancient Philosophy
Aristotle seeks to resolve the problems raised in Posterior Analytics B.3–7 by arguing that our practices of definition and explanation are interdependent. It is not possible to define kinds without ...
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Aristotle seeks to resolve the problems raised in Posterior Analytics B.3–7 by arguing that our practices of definition and explanation are interdependent. It is not possible to define kinds without appeal to their causal structure, nor is it possible to single out the relevant causal structure without appeal to what is required for good definition. This is why Aristotle holds that the answer to the questions, ‘What is F?’ and ‘Why is F as it is?’ are the same. Neither definition nor explanation can be completed without assistance from the other.Less
Aristotle seeks to resolve the problems raised in Posterior Analytics B.3–7 by arguing that our practices of definition and explanation are interdependent. It is not possible to define kinds without appeal to their causal structure, nor is it possible to single out the relevant causal structure without appeal to what is required for good definition. This is why Aristotle holds that the answer to the questions, ‘What is F?’ and ‘Why is F as it is?’ are the same. Neither definition nor explanation can be completed without assistance from the other.
Ted Underwood
- Published in print:
- 2019
- Published Online:
- September 2019
- ISBN:
- 9780226612669
- eISBN:
- 9780226612973
- Item type:
- book
- Publisher:
- University of Chicago Press
- DOI:
- 10.7208/chicago/9780226612973.001.0001
- Subject:
- Literature, Criticism/Theory
As literary historians have learned to compare thousands of volumes at a time, they have stumbled onto century-spanning trends that are not yet fully understood. This book explores some of those ...
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As literary historians have learned to compare thousands of volumes at a time, they have stumbled onto century-spanning trends that are not yet fully understood. This book explores some of those trends in English-language literature. It shows, for instance, that patterns of literary judgment are very durable: a model trained on reviewing patterns in the nineteenth century can also predict the choices of twentieth-century reviewers. Chapter 2 traces the consolidation of detective fiction and science fiction; Chapter 4 measures the gradual blurring of boundaries between grammatically masculine and feminine characters. Throughout the argument, emphasis falls on the gradual emergence of a specialized literary language that continues to shape our assumptions about the purpose of poetry and fiction even today. The book also explains the new modes of quantitative analysis that are making these patterns visible. Instead of framing a debate about “digital humanities,” or a conflict between “close” and “distant" reading, the book presents statistical models as interpretive strategies akin to humanistic interpretation. The argument relies especially on the premise that machine learning can be trained on different subsets of evidence, in order to help scholars reason about the differences between historical perspectives.Less
As literary historians have learned to compare thousands of volumes at a time, they have stumbled onto century-spanning trends that are not yet fully understood. This book explores some of those trends in English-language literature. It shows, for instance, that patterns of literary judgment are very durable: a model trained on reviewing patterns in the nineteenth century can also predict the choices of twentieth-century reviewers. Chapter 2 traces the consolidation of detective fiction and science fiction; Chapter 4 measures the gradual blurring of boundaries between grammatically masculine and feminine characters. Throughout the argument, emphasis falls on the gradual emergence of a specialized literary language that continues to shape our assumptions about the purpose of poetry and fiction even today. The book also explains the new modes of quantitative analysis that are making these patterns visible. Instead of framing a debate about “digital humanities,” or a conflict between “close” and “distant" reading, the book presents statistical models as interpretive strategies akin to humanistic interpretation. The argument relies especially on the premise that machine learning can be trained on different subsets of evidence, in order to help scholars reason about the differences between historical perspectives.
David Charles
- Published in print:
- 2002
- Published Online:
- November 2003
- ISBN:
- 9780199256730
- eISBN:
- 9780191597183
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/019925673X.003.0010
- Subject:
- Philosophy, Ancient Philosophy
Aristotle, in the Posterior Analytics, connects his account of definition and explanation with the theory of division. The features that figure in the relevant explanation include those that ...
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Aristotle, in the Posterior Analytics, connects his account of definition and explanation with the theory of division. The features that figure in the relevant explanation include those that distinguish the kind in its relevant genus. His account of differentiation into genera and species is strongly interconnected with his explanation‐involving account of definition.Less
Aristotle, in the Posterior Analytics, connects his account of definition and explanation with the theory of division. The features that figure in the relevant explanation include those that distinguish the kind in its relevant genus. His account of differentiation into genera and species is strongly interconnected with his explanation‐involving account of definition.
Stephen Everson
- Published in print:
- 1999
- Published Online:
- November 2003
- ISBN:
- 9780198238638
- eISBN:
- 9780191597374
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198238630.003.0006
- Subject:
- Philosophy, Ancient Philosophy
Everson examines Aristotle's use of the term empeiria, particularly as it appears in Metaphysics I.1 and Posterior Analytics II.19. Empeiria is usually translated as ‘experience’, but Everson argues ...
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Everson examines Aristotle's use of the term empeiria, particularly as it appears in Metaphysics I.1 and Posterior Analytics II.19. Empeiria is usually translated as ‘experience’, but Everson argues that it ought to be interpreted as ‘an acquired perceptual concept’. Such concepts are involved in determining the content of perceptual experience. On this account, perceptual awareness is a combination of phantasia and the presence or absence of a certain empeiria, i.e. of the acquired perceptual concept appropriate for the perceptual awareness in question.Less
Everson examines Aristotle's use of the term empeiria, particularly as it appears in Metaphysics I.1 and Posterior Analytics II.19. Empeiria is usually translated as ‘experience’, but Everson argues that it ought to be interpreted as ‘an acquired perceptual concept’. Such concepts are involved in determining the content of perceptual experience. On this account, perceptual awareness is a combination of phantasia and the presence or absence of a certain empeiria, i.e. of the acquired perceptual concept appropriate for the perceptual awareness in question.
Terence Irwin
- Published in print:
- 1990
- Published Online:
- November 2003
- ISBN:
- 9780198242901
- eISBN:
- 9780191597770
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/0198242905.003.0006
- Subject:
- Philosophy, Ancient Philosophy
The Posterior Analytics describes the structure of a science and of the content of scientific propositions. Aristotle sees the weaknesses observed in his methods, and his views on justification ...
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The Posterior Analytics describes the structure of a science and of the content of scientific propositions. Aristotle sees the weaknesses observed in his methods, and his views on justification support and explain some of his demands on scientific knowledge. However, these same views seem to imply demands that he cannot meet within any plausible conception of justification.Less
The Posterior Analytics describes the structure of a science and of the content of scientific propositions. Aristotle sees the weaknesses observed in his methods, and his views on justification support and explain some of his demands on scientific knowledge. However, these same views seem to imply demands that he cannot meet within any plausible conception of justification.
Peter Grindrod
- Published in print:
- 2014
- Published Online:
- March 2015
- ISBN:
- 9780198725091
- eISBN:
- 9780191792526
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198725091.001.0001
- Subject:
- Mathematics, Analysis, Probability / Statistics
This book presents analytics within a framework of mathematical theory and concepts, building upon firm theory and foundations of probability theory, graphs, and networks, random matrices, linear ...
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This book presents analytics within a framework of mathematical theory and concepts, building upon firm theory and foundations of probability theory, graphs, and networks, random matrices, linear algebra, optimization, forecasting, discrete dynamical systems, and more. Following on from the theoretical considerations, applications are given to data from commercially relevant interests: supermarket baskets; loyalty cards; mobile phone call records; smart meters; ‘omic‘ data; sales promotions; social media; and microblogging. Each chapter tackles a topic in analytics: social networks and digital marketing; forecasting; clustering and segmentation; inverse problems; Markov models of behavioural changes; multiple hypothesis testing and decision-making; and so on. Chapters start with background mathematical theory explained with a strong narrative and then give way to practical considerations and then to exemplar applications.Less
This book presents analytics within a framework of mathematical theory and concepts, building upon firm theory and foundations of probability theory, graphs, and networks, random matrices, linear algebra, optimization, forecasting, discrete dynamical systems, and more. Following on from the theoretical considerations, applications are given to data from commercially relevant interests: supermarket baskets; loyalty cards; mobile phone call records; smart meters; ‘omic‘ data; sales promotions; social media; and microblogging. Each chapter tackles a topic in analytics: social networks and digital marketing; forecasting; clustering and segmentation; inverse problems; Markov models of behavioural changes; multiple hypothesis testing and decision-making; and so on. Chapters start with background mathematical theory explained with a strong narrative and then give way to practical considerations and then to exemplar applications.
José van Dijck
- Published in print:
- 2013
- Published Online:
- January 2013
- ISBN:
- 9780199970773
- eISBN:
- 9780199307425
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199970773.003.0004
- Subject:
- Sociology, Culture
The fourth chapter traces the transformation of Twitter, the microblogging platform that started in 2006. The platform aimed to be an autonomous utility service promoting user connectedness, but ...
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The fourth chapter traces the transformation of Twitter, the microblogging platform that started in 2006. The platform aimed to be an autonomous utility service promoting user connectedness, but gradually transmuted into an information network exploiting user connectivity. Twitter’s history revolves around a double paradox: first, the functions of following and trending presume a neutral technological infrastructure where all users are equal and all content is carried indiscriminately. In practice, Twitter’s filtering mechanisms inscribe more weight to some twitterers and tweets, thus promoting the creation of big followings and popular trends. Second, Twitter presents its network as an online “town hall” for networked communication, but the platform has manifested itself as a potent instrument for manipulating opinions. In light of this paradox, we need to interpret how Twitter changed its initial ambitions from wanting to be a “utility” to becoming an “information networking company.” Using instruments like predictive analytics, the site increasingly aims at capitalizing the flow of tweets rushing though its veinsLess
The fourth chapter traces the transformation of Twitter, the microblogging platform that started in 2006. The platform aimed to be an autonomous utility service promoting user connectedness, but gradually transmuted into an information network exploiting user connectivity. Twitter’s history revolves around a double paradox: first, the functions of following and trending presume a neutral technological infrastructure where all users are equal and all content is carried indiscriminately. In practice, Twitter’s filtering mechanisms inscribe more weight to some twitterers and tweets, thus promoting the creation of big followings and popular trends. Second, Twitter presents its network as an online “town hall” for networked communication, but the platform has manifested itself as a potent instrument for manipulating opinions. In light of this paradox, we need to interpret how Twitter changed its initial ambitions from wanting to be a “utility” to becoming an “information networking company.” Using instruments like predictive analytics, the site increasingly aims at capitalizing the flow of tweets rushing though its veins
Anders Drachen, Pejman Mirza-Babaei, and Lennart Nacke (eds)
- Published in print:
- 2018
- Published Online:
- March 2018
- ISBN:
- 9780198794844
- eISBN:
- 9780191836336
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198794844.001.0001
- Subject:
- Mathematics, Logic / Computer Science / Mathematical Philosophy, Computational Mathematics / Optimization
Today, Games User Research forms an integral component of the development of any kind of interactive entertainment. User research stands as the primary source of business intelligence in the ...
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Today, Games User Research forms an integral component of the development of any kind of interactive entertainment. User research stands as the primary source of business intelligence in the incredibly competitive game industry. This book aims to provide the foundational, accessible, go-to resource for people interested in GUR. It is a community-driven effort—it is written by passionate professionals and researchers in the GUR community as a handbook and guide for everyone interested in user research and games. The book bridges the current gaps of knowledge in Game User Research, building the go-to volume for everyone working with games, with an emphasis on those new to the field.Less
Today, Games User Research forms an integral component of the development of any kind of interactive entertainment. User research stands as the primary source of business intelligence in the incredibly competitive game industry. This book aims to provide the foundational, accessible, go-to resource for people interested in GUR. It is a community-driven effort—it is written by passionate professionals and researchers in the GUR community as a handbook and guide for everyone interested in user research and games. The book bridges the current gaps of knowledge in Game User Research, building the go-to volume for everyone working with games, with an emphasis on those new to the field.
Justin Longo and Kathleen McNutt
- Published in print:
- 2018
- Published Online:
- January 2019
- ISBN:
- 9781447334910
- eISBN:
- 9781447334934
- Item type:
- chapter
- Publisher:
- Policy Press
- DOI:
- 10.1332/policypress/9781447334910.003.0018
- Subject:
- Political Science, Comparative Politics
Policy analysis relies on data collected at discrete intervals along the policy cycle, from problem identification through evaluation. Policy analytics, in contrast, represents the combination of ...
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Policy analysis relies on data collected at discrete intervals along the policy cycle, from problem identification through evaluation. Policy analytics, in contrast, represents the combination of new, ubiquitous, and continuous data sources—from Internet search and social media to mobile smartphones, Internet of Everything (IoE) devices, and electronic transaction cards—with new data analytics techniques for informing and directing policy choices. New technology platforms also offer the possibility of small-scale policy experiments that can be piloted with their effects precisely observed in real-time. This big data + analytics + real-time experiments approach offers a significant change to the traditional practice of policy analysis. This chapter describes the movement from policy analysis to policy analytics, discusses emergent examples and potential applications, and concludes with questions that can guide the appropriate adoption of policy analytics for supporting policymaking.Less
Policy analysis relies on data collected at discrete intervals along the policy cycle, from problem identification through evaluation. Policy analytics, in contrast, represents the combination of new, ubiquitous, and continuous data sources—from Internet search and social media to mobile smartphones, Internet of Everything (IoE) devices, and electronic transaction cards—with new data analytics techniques for informing and directing policy choices. New technology platforms also offer the possibility of small-scale policy experiments that can be piloted with their effects precisely observed in real-time. This big data + analytics + real-time experiments approach offers a significant change to the traditional practice of policy analysis. This chapter describes the movement from policy analysis to policy analytics, discusses emergent examples and potential applications, and concludes with questions that can guide the appropriate adoption of policy analytics for supporting policymaking.
