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Books on the topic 'Relation causale'

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Published: 4 June 2021
Last updated: 2 February 2022

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1

Kurki, Milja. Causation in international relations: Reclaiming causal analysis. Cambridge: Cambridge University Press, 2008.

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Kurki, Milja. Causation in international relations: Reclaiming causal analysis. Cambridge: Cambridge University Press, 2008.

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Kurki, Milja. Causation in international relations: Reclaiming causal analysis. Cambridge: Cambridge University Press, 2008.

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4

Vourkoutiotis, Vasilis. Making common cause: German-Soviet relations, 1919-22. Basingstoke [England]: Palgrave Macmillan, 2007.

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5

Shultz, George Pratt. Berlin and the cause of freedom. Washington, D.C: U.S. Dept. of State, Bureau of Public Affairs, 1985.

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6

Shultz, George Pratt. Berlin and the cause of freedom. Washington, D.C: U.S. Dept. of State, Bureau of Public Affairs, 1985.

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7

Shultz, George Pratt. Berlin and the cause of freedom. Washington, D.C: U.S. Dept. of State, Bureau of Public Affairs, 1985.

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8

American international oil policy: Causal factors and effect. London: F. Pinter, 1987.

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9

American international oil policy: Causal factors and effect. New York: St. Martin's Press, 1987.

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10

Riaux, Gilles. Ethnicité et nationalisme en Iran: La cause azerbaïdjanaise. Paris: Karthala, 2012.

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11

Ethnicité et nationalisme en Iran: La cause azerbaïdjanaise. Paris: Karthala, 2012.

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12

Paul, Ashton, ed. Unemployment: Cause and cure. 2nd ed. Oxford, UK: B. Blackwell, 1985.

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13

Margaret, Roth, and Baker Caleb, eds. Operation Just Cause: The storming of Panama. New York: Lexington Books, 1991.

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14

Donnelly, Thomas. Operation just cause: The invasion of Panama. Lexington, Mass: Lexington Books, 1991.

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15

Spadolini, Giovanni. Laurea "honoris causa" dell'Universita' (sic) di Coimbra al Professor Giovanni Spadolini =: Doutoramento "honoris causa" do Professor Giovanni Spadolini pela Universidade de Coimbra. Lisbona: Istituto italiano di cultura in Portogallo, 1992.

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16

Horiner-Levi, Eveline. Effects of group membership and intergroup stereotypes on causal attribution. [Israel: s.n., 1988.

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17

Grant, Rebecca L. Operation Just Cause and the U.S. policy process. Santa Monica, CA: Rand, 1991.

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18

Metzger, David. The lost cause of rhetoric: The relation of rhetoric and geometry in Aristotle and Lacan. Carbondale: Southern Illinois University Press, 1995.

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19

Anderson, Natalie. Rebel with a cause. Toronto: Harlequin, 2011.

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20

Lionel, Curtis. World war: Its cause and cure. London: Lothian Foundation Press, 1992.

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21

Sulla, Olga. Analysis of causal relations and long- and short-term correspondence between share indices in Israel and the United States. Jerusalem: Bank of Israel, Monetary Dept., 2000.

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22

El subdesarrollo social de España: Causas y consecuencias. Barcelona: Diario Público, 2009.

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23

Lecturer, Rashid Abdul, and Pakistan Institute of Development Economics., eds. A significant shift in causal relations of money, income, and prices in Pakistan: The price hikes in the early 1970s. Islamabad: Pakistan Institute of Development Economics, 2006.

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24

Husain, Fazal. A significant shift in causal relations of money, income, and prices in Pakistan: The price hikes in the early 1970s. Islamabad: Pakistan Institute of Development Economics, 2006.

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Husain, Fazal. A significant shift in causal relations of money, income, and prices in Pakistan: The price hikes in the early 1970s. Islamabad: Pakistan Institute of Development Economics, 2006.

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26

Lewis, Clayton. Causal Relations. Edited by Susan E. F. Chipman. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199842193.013.9.

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27

Dowe, Phil. Causal Process Theories. Edited by Helen Beebee, Christopher Hitchcock, and Peter Menzies. Oxford University Press, 2010. http://dx.doi.org/10.1093/oxfordhb/9780199279739.003.0011.

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If the core idea of process theories of causation is that causation can be understood in terms of causal processes and interactions, then the approach should be attributed primarily to Wesley Salmon (1925–2001). Salmon takes causal processes and interactions as more fundamental than causal relations between events. To express this Salmon liked to quote John Venn: ‘Substitute for the time honoured “chain of causation”, so often introduced into discussions upon this subject, the phrase a “rope of causation”, and see what a very different aspect the question will wear’. According to the process theory, any facts about causation as a relation between events obtain only on account of more basic facts about causal processes and interactions. Causal processes are the world-lines of objects, exhibiting some characteristic essential for causation.
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28

Bennett, Karen. Causing. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199682683.003.0004.

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It is common to sharply distinguish between causal and noncausal determination, and to assume that building or grounding only involves the latter. That is a mistake; the line between causal and noncausal determination is not nearly as clear as it is usually taken to be. This chapter defends the claim that building is causally tainted in two quite distinct senses. First, it is useful to count causation itself as a building relation. That is, the class that includes both causation and other putatively noncausal building relations is reasonably natural and philosophically important. Second, some particular building relations other than causation hold in virtue of causal facts.
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29

Bernstein, Sara. Causal Idealism. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198746973.003.0013.

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This chapter argues that causal idealism, the view that causation is a product of mental activity, is at least as attractive as several contemporary views of causation that incorporate human thought and agency into the causal relation. The chapter discusses three such views: contextualism, which holds that truth conditions for causal judgments are contextual; contrastivism, which holds that the causal relation is a quaternary relation between a cause, an effect, and contextually specified contrast classes for the cause and the effect; and pragmatism, which holds that causal claims are sensitive to pragmatic factors. This chapter suggests that causal idealism has at least as much explanatory strength as these three theories, and is more parsimonious and internally stable.
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30

Holyoak, Keith J., and Hee Seung Lee. Inferring Causal Relations by Analogy. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.25.

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When two situations share a common pattern of relationships among their constituent elements, people often draw an analogy between a familiar source analog and a novel target analog. This chapter reviews major subprocesses of analogical reasoning and discusses how analogical inference is guided by causal relations. Psychological evidence suggests that analogical inference often involves constructing and then running a causal model. It also provides some examples of analogies and models that have been used as tools in science education to foster understanding of critical causal relations. A Bayesian theory of causal inference by analogy illuminates how causal knowledge, represented as causal models, can be integrated with analogical reasoning to yield inductive inferences.
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31

Buehner, Marc J. Space, Time, and Causality. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.29.

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This chapter explores how the understanding of causality relates to the understanding of space and time. Traditionally, spatiotemporal contiguity is regarded as a cue toward causality. While concurring with this view, this chapter also reviews some boundary conditions of this approach. Moreover, temporal information goes beyond merely helping to identify causal relations; it also shapes the types of causal inferences that reasoners draw. Recent developments further show that the relation between time and causality is bi-directional: not only does temporal information shape and guide causal inferences, but once one holds a causal belief, one’s perception of time and space is distorted such that cause and effect appear closer in space-time. Spatiotemporal contiguity thus supports causal beliefs, which in turn foster impressions of contiguity.
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32

Ehring, Douglas. Causal Relata. Edited by Helen Beebee, Christopher Hitchcock, and Peter Menzies. Oxford University Press, 2010. http://dx.doi.org/10.1093/oxfordhb/9780199279739.003.0020.

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This article argues that the intrinsicness of the causal relation undermines the main case for facts as the causal relata, which is based on causation by and of absences. Furthermore, it argues that since causes and effects are generally temporally and spatially related to each other, facts could not be causes and effects. It also argues that the transitivity of causation rules out at least one major candidate for causal relata, coarse-grained events. And, finally, it argues that since the best theory of causation employs the notion of qualitative or property persistence, the best candidate for causal relata must be based around tropes or particularized properties.
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33

Godfrey‐Smith, Peter. Causal Pluralism. Edited by Helen Beebee, Christopher Hitchcock, and Peter Menzies. Oxford University Press, 2010. http://dx.doi.org/10.1093/oxfordhb/9780199279739.003.0017.

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Causal pluralism is the view that causation is not a single kind of relation or connection between things in the world. Instead, the apparently simple and univocal term ‘cause’ is seen as masking an underlying diversity. Assessing such a claim requires making sense of a difficult counting operation. How do we tell whether a theory of causation is identifying causation with a ‘single’ kind of connection? In practice, there tends not to be much disagreement about how to do the counting, because most philosophical work on causation has sought a view with an obvious kind of unity. The literature often works with a standard range of candidate connections that seem to have an important link to the idea of causation.
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34

Hitchcock, Christopher. Probabilistic Causation. Edited by Alan Hájek and Christopher Hitchcock. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199607617.013.41.

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This chapter will explore a variety of projects that aim to characterize causal concepts using probability. These are, somewhat arbitrarily, divided into four categories. First, a tradition within philosophy that has aimed to define, or at least constrain, causation in terms of conditional probability is discussed. Secondly, the use of causal Bayes nets to represent causal relations, to facilitate inferences from probabilities to causal relations, and to ‘identify’ causal quantities in probabilistic terms is discussed. Thirdly, efforts to measure causal strength in probabilistic terms are reviewed, with particular attention to the significance of these measures in the context of epidemiology. Finally, attempts are discussed to analyze the relation of ‘actual causation’ (sometimes called ‘singular causation’) using probability.
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35

Kurki, Milja. Causation in International Relations: Reclaiming Causal Analysis (Cambridge Studies in International Relations). Cambridge University Press, 2008.

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36

Causation in International Relations: Reclaiming Causal Analysis (Cambridge Studies in International Relations). Cambridge University Press, 2008.

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37

Lebow, Richard Ned. Constructing Cause in International Relations. University of Cambridge ESOL Examinations, 2015.

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38

Constructing Cause In International Relations. Cambridge University Press, 2014.

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39

Rehder, Bob. Concepts as Causal Models. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.39.

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This chapter evaluates the case for treating concepts as causal models, the view that people conceive of a categories as consisting of not only features but also the causal relations that link those features. In particular, it reviews the role of causal models in categorization, the process of inferring an object’s category membership by observing its features. Reviewed studies include those testing categories that are either real world or artificial (made up of the experimenters) and subjects that are either adults or children. The chapter concludes that causal models provide accounts of causal-based categorization judgments that are superior to alternative accounts.
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40

Hoefer, Carl. Causation in Spacetime Theories. Edited by Helen Beebee, Christopher Hitchcock, and Peter Menzies. Oxford University Press, 2010. http://dx.doi.org/10.1093/oxfordhb/9780199279739.003.0035.

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Although Russell maintained that causation was not to be found in advanced physical theories (which is described in this article), even he would have admitted that, if one must talk of cause–effect relations between events, then spacetime theories may well place constraints on what sorts of causal relations may exist and how they may be arranged in time. They may also imply the possibility of surprising and unexpected causal relations, and even serious causal anomalies. This article looks at what the three most important spacetime theories imply about causation. It starts with a brief look at Newtonian physics, looks at how important changes are introduced by Special Relativity theory, and finally turns to the rich causal fields of General Relativity models.
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41

Bernstein, Sara. Causal Proportions and Moral Responsibility. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198805601.003.0009.

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Both causation and moral responsibility seem to come in degrees, but explaining the metaphysical relationship between them is more complex than theorists have realized. This paper poses an original puzzle about this relationship and uses it to reach three important conclusions. First, certain natural resolutions of the puzzle reveal the existence of a new sort of moral luck called proportionality luck. Second, there is indeterminacy in the type of causal relation deployed in assessments of moral responsibility. Finally—and most importantly—leading theories of causation do not have the ability to capture the sorts of causal differences that matter for moral evaluation of agents’ causal contributions to outcomes.
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42

Cheng, Patricia W., and Hongjing Lu. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.9.

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This chapter illustrates the representational nature of causal understanding of the world and examines its implications for causal learning. The vastness of the search space of causal relations, given the representational aspect of the problem, implies that powerful constraints are essential for arriving at adaptive causal relations. The chapter reviews (1) why causal invariance—the sameness of how a causal mechanism operates across contexts—is an essential constraint for causal learning in intuitive reasoning, (2) a psychological causal-learning theory that assumes causal invariance as a defeasible default, (3) some ways in which the computational role of causal invariance in causal learning can become obscured, and (4) the roles of causal invariance as a general aspiration, a default assumption, a criterion for hypothesis revision, and a domain-specific description. The chapter also reviews a puzzling discrepancy in the human and non-human causal and associative learning literatures and offers a potential explanation.
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43

The germ theory in relation to therapeutics. [Canada?: s.n., 1994.

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44

Tooley, Michael. Causes, Laws, and Ontology. Edited by Helen Beebee, Christopher Hitchcock, and Peter Menzies. Oxford University Press, 2010. http://dx.doi.org/10.1093/oxfordhb/9780199279739.003.0019.

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Different approaches to causation often diverge very significantly on ontological issues, in the case of both causal laws, and causal relations between states of affairs. This article sets out the main alternatives with regard to each. Causal concepts have surely been present from the time that language began, since the vast majority of action verbs involve the idea of causally affecting something. Thus, in the case of transitive verbs describing physical actions, there is the idea of causally affecting something external to one — one finds food, builds a shelter, sows seed, catches fish, and so on — while in the case of intransitive verbs describing physical actions, it is very plausible that they involve the idea of causally affecting one's own body — as one walks, runs, jumps, hunts, and so on.
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45

Brown, Thomas. Inquiry into the Relation of Cause and Effect. University of Cambridge ESOL Examinations, 2012.

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46

Rehder, Bob. Concepts as Causal Models. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.21.

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This chapter evaluates the case for treating concepts as causal models, the view that people conceive of a categories as consisting of not only features but also the causal relations that link those features. In particular, it reviews the role of causal models in category-based induction. Category-based induction consists of drawing inferences about either objects or categories; in the latter case one generalizes a feature to a category (and thus its members). How causal knowledge influences how categories are formed in the first place—causal-based category discovery—is also examined. Whereas the causal model approach provides a generally compelling account of a large variety of inductive inferences, certain key discrepancies between the theory and empirical findings are highlighted. The chapter concludes with a discussion of the new sorts of representations, tasks, and tests that should be applied to the causal model approach to concepts.
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47

Johnson-Laird, P. N., and Sangeet S. Khemlani. Mental Models and Causation. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.4.

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The theory of mental models accounts for the meanings of causal relations in daily life. They refer to seven temporally-ordered deterministic relations between possibilities, which include causes, prevents, and enables. Various factors—forces, mechanisms, interventions—can enter into the interpretation of causal assertions, but they are not part of their core meanings. Mental models represent only salient possibilities, and so they are identical for causes and enables, which may explain failures to distinguish between their meanings. Yet, reasoners deduce different conclusions from them, and distinguish between them in scenarios, such as those in which one event enables a cause to have its effect. Neither causation itself nor the distinction between causes and enables can be captured in the pure probability calculus. Statistical regularities, however, often underlie the induction of causal relations. The chapter shows how models help to resolve inconsistent causal scenarios and to reverse engineer electrical circuits.
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48

Wolff, Phillip. Force Dynamics. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.13.

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Force dynamics is an approach to knowledge representation that aims to describe how notions of force, resistance, and tendency enter into the representation of certain kinds of words and concepts. As a theory of causation, it specifies how the concept of cause may be grounded in people’s representations of force and spatial relations. This chapter reviews theories of force dynamics that have recently emerged in the linguistic, psychological, and philosophical literatures. In discussing these theories, it reveals how a force dynamic account of causation is able to account for many of the key phenomena in causal cognition, including the representation of individual causal events, the encoding of causal relations in language, the encoding of causal chains, and causation by omission.
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49

Gehring, David S. Anglo-German Relations and the Protestant Cause. Routledge, 2015. http://dx.doi.org/10.4324/9781315654812.

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50

Danks, David. Singular Causation. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.15.

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Causal relations between specific events are often critically important for learning, understanding, and reasoning about the world. This chapter examines both philosophical accounts of the nature of singular causation, and psychological theories of people’s judgments and reasoning about singular causation. It explores the content of different classes of theories, many of which are based on either some type of physical process connecting cause and effect, or else some kind of difference-making (or counterfactual) impact of the cause on the effect. In addition, this chapter examines various theoretical similarities and differences, particularly between philosophical and psychological theories that appear superficially similar. One consistent theme that emerges in almost every account is the role of general causal relations in shaping human judgments and understandings about singular causation.
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