Causal Misconceptions
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Abstract
This paper is in response to a gentleman who once wrote a paper on Causality. He proposed to look at in a different way that to me seemed unsatisfactory.
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2024
The four main concepts of causality are: causation (deterministic causality) and natural spontaneity (non-volitional indeterminism), and volition (free will by human or other souls) and influence (things intuited, perceived or conceived, making will easier or harder, without however annulling its freedom). We use the term ‘causality’ to signify a genus for these four species of cause-effect relations.
Erkenntnis
Hall has argued recently that there are two concepts of causality, picking out two different kinds of causal relation. McGrath, and Hitchcock and Knobe, have recently argued that the facts about causality depend on what counts as a default or normal state, or even on the moral facts. In the light of these claims you might be tempted to agree with Skyrms that causal relations constitute, metaphysically speaking, an amiable jumble, or with Cartwright that causation, though a single word, encompasses many different kinds of things. This paper argues, drawing on the author's recent work on explanation, that the evidence adduced in support of causal pluralism can be accommodated easily by a unified theory of causality—a theory according to which all singular causal claims concern the same fundamental causal network.
2011
On one view, an adequate account of causal understanding may focus exclusively on what is involved in mastering general causal concepts (concepts such as ‘x causes y’ or ‘p causally explains q’). An alternative view is that causal understanding is, partly but irreducibly, a matter of grasping what Anscombe called special causal concepts, concepts such as ‘push’, ‘flatten’, or ‘knock over’. We can label these views generalist vs particularist approaches to causal understanding. It is worth emphasizing that the contrast here is not between two kinds of theories of the metaphysics of causation, but two views of the nature and perhaps source of ordinary causal understanding. One aim of this paper is to argue that it would be a mistake to dismiss particularism because of its putative metaphysical commitments. I begin by formulating an intuitively attractive version of particularism due to P.F. Strawson, a central element of which is what I will call naı̈ve realism concerning mechanical t...
Psychological Record, 1997
Behavior analysts take the position that prediction and control constitute the goals of science. This assumption has resulted in descriptive operations being overlooked and misunderstood. Among the most serious of these misunderstandings is the confusion of events with descriptive constructions. Confusion is likely when the events described present problems of observation, when they appear to resemble our descriptions of them, and when they are taken to be synonymous with our reactions to them. Examples of confusing events with their descriptions are examined in the context of the radical behavioral interpretation of causality, along with their implications for a scientific understanding. An alternative interpretation of causal knowledge is suggested. The purpose of all serious intellectual enterprises, including science and philosophy, is to formulate an understanding of the world that directly or indirectly enhances our well being. According to Kantor (1953, pp. 13-14) science is an enterprise directed at increasing our knowledge of the world and such is accomplished by describing confrontable events and elaborating upon our descriptions so as to produce what we may call explanations for the forms and operations of those events. Not all philosophers of science take this view. Science as the means by which our knowledge of the world is accumulated is inexplicably tied to more practical considerations of what use may be made of such knowledge, however; and these more practical considerations tend to take precedence in our characterizations of the scientific endeavor. That is to say, many scientists assume that prediction and control are the principal goals of science (e.g.,
Metascience, 2016
Sociological Methods Amp Research, 2001
N ot being able to carry out proper experiments as the true (physical) scientists and even the colleagues from the neighboring psychology department do, sociologists have thrown themselves into the promising arms of the attractive "causal" models. From the 1960s onward, linear structural equation modeling became the norm and standard for the causal analysis of the nonexperimental data, to such an extent that it elicited biting comments from Louis Guttman (1977): "There has been a flowering of causal discoveries in sociology at a pace unheard of in the history of science. .. which undoubtedly put sociology at the forefront of all sciences in terms of frequency of discovery of fundamental relationships" (p. 103). Many others for many different reasons and from many different angles have shared Guttman's criticisms and worries. An early criticism, directly relevant for the practicing social researcher, was Derek Philips's (1971) Knowledge From What?, asking incisive questions about the validity of the data on which causal analyses are based (and which later led him to Abandoning Method) (Philips 1973). Also from within the empiricist tradition, Lieberson's (1985) Making It Count attacked the too simplified and rigid nature of AUTHORS' NOTE: Earlier versions of the articles in this issue were presented at the sessions "Causality and Social Research I and II" of the 14th World Congress of Sociology in 1998 in Montreal. These sessions were organized by Truus Kantebeen, Johannes van der Zouwen,
Causality as a Cognitive Crutch, part two., 2026
Time-asymmetric, causal formulations dominate the presentation of physical theories, particularly in quantum mechanics. While such formulations are narratively convenient and computationally effective, they often obscure foundational questions concerning the ontology of quantum states and the origin of measurement phenomena. This essay argues that causal time evolution functions as a cognitive and methodological crutch: it enables forward prediction while postponing or avoiding deeper ontological commitments. By contrast, time-symmetric and constraintbased formulations force explicit answers to questions that causal narratives leave underdetermined-namely, what physical quantities are extremized or conserved, what relations define allowed configurations, and what role "time evolution" plays at a fundamental level. Using quantum mechanics as a primary case study, the essay situates standard interpretational difficulties within this broader structural issue and motivates a shift from causal narratives to symmetric constraint satisfaction as a framework for conceptual clarity.
It is shown that two models of causality exist. There is dialectic model and evolution model. Two models have mutual tie. It is shown that the interactions must be analysed only within framework of dialectic model. Instantaneous interactions do not contradict dialectic model. The velocity of propagation of interactions is nonsense, and indeterminism is a false branch in philosophy and physics.
Quality and Quantity, 2008
We analyse the concept of causality in the social sciences, whose development is insufficient and lesser than the methodology developed for its study. The nature of the causal process as the production of effects remains unclear and the relationships considered to be manifestations of that process cannot be taken for proof of its existence. Given these difficulties, we suggest that, aside from the inherited interpretations, the practice of the concept of causality makes reference to correctly specified relationships not confounded by others; characteristics identical to those which define validity. In that way, causality is equivalent to the validity of a relationship. Beyond merely re-understanding causality, this proposal permits the deduction that the temporal precedence of the cause is a necessary condition only for one type of causality, making it possible to consider other types, not admitted by the traditional notion, in which the cause is consequent or simultaneous to the variable to be explained. Examples and characteristics of these types of causality are presented and considered to be useful for the social sciences.
Ph.D from Texas A&M University - Corpus Christi. My Concentration is in Curriculum & Instruction with an emphasis in reading theory...
Related papers
2005
Is the common cause principle merely one of a set of useful heuristics for discovering causal relations, or is it rather a piece of heavy duty metaphysics, capable of grounding the direction of causation itself? Since the principle was introduced in Reichenbach’s groundbreaking work The Direction of Time (1956), there have been a series of attempts to pursue the latter program—to take the probabilistic relationships constitutive of the principle of the common cause and use them to ground the direction of causation. These attempts have not all explicitly appealed to the principle as originally formulated; it has also appeared in the guise of independence conditions, counterfactual overdetermination, and, in the causal modelling literature, as the causal markov condition. In this paper, I identify a set of difficulties for grounding the asymmetry of causation on the principle and its descendents. The first difficulty, concerning what I call the vertical placement of causation, consist...
Synthese
It seems to be a platitude that there must be a close connection between causality and the laws of nature: the laws somehow cover in general what happens in each specific case of causation. But so-called singularists disagree, and it is often thought that the locus classicus for that kind of dissent is Anscombe's famous Causality & Determination. Moreover, it is often thought that Anscombe's rejection of determinism is premised on singularism. In this paper, I show that this is a mistake: Anscombe is not a singularist, but in fact only objects to a very specific, Humean understanding of the generality of laws of nature and their importance to causality. I argue that Anscombe provides us with the contours of a radically different understanding of the generality of the laws, which I suggest can be fruitfully developed in terms of recently popular dispositional accounts. And as I will show, it is this account of laws of nature (and not singularism) that allows for the possibili...
2006
Is the common cause principle merely one of a set of useful heuristics for dis-covering causal relations, or is it rather a piece of heavy duty metaphysics, capable of grounding the direction of causation itself? Since the princi-ple was introduced in Reichenbach’s groundbreaking work The Direction of Time (1956), there have been a series of attempts to pursue the latter program—to take the probabilistic relationships constitutive of the princi-ple of the common cause and use them to ground the direction of causation. These attempts have not all explicitly appealed to the principle as originally formulated; it has also appeared in the guise of independence conditions, counterfactual overdetermination, and, in the causal modelling literature, as the causal markov condition. In this paper, I identify a set of difficulties for grounding the asymmetry of causation on the principle and its descen-dents. The first difficulty, concerning what I call the vertical placement of causation, con...
TAKING UP MCLUHAN'S CAUSE, 2017
Formal causality has, in large part, been eschewed by both the philosophic and scientific communities alike. David Hume in particular levied an assault against any form of causality other than material cause. But formal cause is as viable a notion as material cause, and one that is of vital importance in both philosophy and science. By re-assessing Aristotle’s notion of formal causality, and interweaving it with inspirations from such diverse disciplines as Anthropology, Semiotics, and Communication Studies the notion of formal cause can be restored to its rightful place, along side material cause, as a fundamental principle of scientific and philosophical methods alike.
Journal of the American Statistical Association, 2005
Judea Pearl has been at the forefront of research in the burgeoning field of causal modeling, and Causality is the culmination of his work over the last dozen or so years. For philosophers of science with a serious interest in causal modeling, Causality is simply mandatory reading. Chapter 2, in particular, addresses many of the issues familiar from works such as Causation, Prediction and Search by Peter Spirtes, Clark Glymour, and Richard Scheines (New York: Springer-Verlag, 1993). But philosophers with a more general interest in causation will also profit from reading Pearl's book, especially the material in chapters 7, 9, and 10 (not to mention the delightful epilogue), which is selfcontained and less technical than other parts of the book. The present review is aimed primarily at readers of the second type. Pearl represents a system of causal relationships by a causal model. A causal model consists of a set of variables, a set of functions, and a probability measure representing our ignorance of the actual values of the variables. Each function generates an equation of the form V i = f i (V i1 ,…,V im), where V i is distinct from each V ij. These equations represent "mechanisms" whereby the value of one variable is causally determined by the values of others. Mechanisms differ from what philosophers call "laws" in that the former are asymmetric. If it is a law that Y = f(X) (and f is an invertible function), then it is also a law that X = f-1 (Y). By contrast, if a causal model contains the mechanism Y = f(X), then it will not also contain the mechanism X = f-1 (Y) (except in very special cases). The system of equations may be represented qualitatively in a directed graph, with an "arrow" drawn from V i to V j just in case V i figures in the function for V j. The directed graph representation greatly facilitates inferences about the model. A causal model may be used to evaluate counterfactuals of the following form: if the value of V i were v i , then the value of V j would be …. The resultant value of V j is determined by replacing the equation V i = f i (V i1 ,…,V im) with V i = v i , and then solving the resulting system of equations. This replacement indicates that V i is set directly to v i by an intervention from outside the system, rather than having its value causally determined by the values of the variables within the system. The intervention need not be miraculous: mechanisms are not inviolable laws, but rather ceteris paribus laws that can be disrupted by external interventions. Such an intervention will not affect the functional forms of the other mechanisms in the causal system: the mechanisms are autonomous. The bulk of Pearl's book deals with inference problems where we have only partial information about the causal system being modeled. Our partial information may be of various kinds. Observational evidence may give us information about probabilistic correlations between variables; background assumptions may give us information about the graphical structure; and con
A new theory of causality based on an empirical analysis of causality and its language in everyday life, craft, the practical arts, the technologies and the sciences.
2014
Abstract: The paper tries to analyze critically what is usually taken for granted – the causal relation between empirical knowledge about ex-ternal world and the world which is (supposedly) known. The aim is neither to propose a new definition of knowledge nor to restate an old one but rather to take a closer look at the claim that knowledge is a true belief caused in a proper way by facts, events, etc. of the external world. This claim is a core of the epistemological approach usually la-beled as “causal theory of knowledge”, but there are many causal theories distinct from each other. The paper therefore sketches the causal components of D. Davidson’s epistemology and the roles they play in the process of cognizing, first. Then it exposes more details of Davidson’s approach and pushes some of them further critically.
1987
~ 4.3.2. Example 1 4.3.3. Example 4. 4.3.4. Suppes' Defense of the Requirements of Spurious 2 4.4. Spurious 3 and Direct 3 Causes 4.4.1. The Definition of a Spu.ious~ Cause 4.4.2. The Defil1i~ion of a Direct:\ cause. 4.4.3. Relations Among the Defimtions of Spurious Causes 4.4.4. Spurious 3 Causes and Examples 2, 3, and 4 4.4.5. Spurious 3 Causes and Example 1 4.5. Spurious Causes and Interactive Forks 4.6. Final Remarks on Suppes v
Acta Sociologica, 2014
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Mark Carbajal, Ph.D