Physics and the direction of causation

Two proposals for a physicalistic analysis of causation — the so-called transference model and an account given by J. L. Mackie — are examined and found wanting on the score of physical objectivity. This shortcoming can be remedied, but it is further argued that both proposals embody a too restricted conception of what a physicalistic analysis of causation should be. A more general program is proposed.     

Trumping the causal influence account of causation

Here is a simple counterexample to David Lewis’s causal influence account of causation, one that is especially illuminating due to its connection to what Lewis himself writes: it is a variant of his trumping example

From covariation to causation: a test of the assumption of causal power

How humans infer causation from covariation has been the subject of a vigorous debate, most recently between the computational causal power account (P. W. Cheng, 1997) and associative learning theorists (e.g., K. Lober & D. R. Shanks, 2000). Whereas most researchers in the subject area agree that causal power as computed by the power PC theory offers a normative account of the inductive process. Lober and Shanks, among others, have questioned the empirical validity of the theory. This article offers a full report and additional analyses of the original study featured in Lober and Shanks's critique (M. J. Buehner & P. W. Cheng, 1997) and reports tests of Lober and Shanks's and other explanations of the pattern of causal judgments. Deviations from normativity, including the outcome-density bias, were found to be misperceptions of the input or other artifacts of the experimental procedures rather than inherent to the process of causal induction.     

Models of causation and the semantics of causal verbs

This research examines the relationship between the concept of CAUSE as it is characterized in psychological models of causation and the meaning of causal verbs, such as the verb cause itself. According to focal set models of causation (; ), the concept of CAUSE should be more similar to the concepts of ENABLE and PREVENT than either is to each other. According to a model based on theory of force dynamics, the force dynamic model, the concepts of CAUSE, ENABLE, and PREVENT should be roughly equally similar to one another. The relationship between these predictions and the meaning of causal verbs was examined by having participants sort causal verbs and rate them with respect to the dimensions specified by the two models. The results from five experiments indicated that the force dynamic model provides a better account of the meaning of causal verbs than do focal set models of causation. Implications for causal inference and induction are discussed.     

Commentary: causal processes leading to antisocial behavior

Conceptual, and empirical, questions are raised regarding the notion that physical aggression is the main individual risk factor for antisocial behavior, that language impairment also constitutes a risk factor, the meaning of the male preponderance for antisocial behavior, the findings on environmentally mediated risk; the role of biosocial interplay; social context effects; the construct of antisocial behavior, developmental trends; processing of experiences; and transactional effects. The main blocks to using research to develop policy are the lack of evidence on (a) the mediators of the causal processes, (b) what is needed to bring about change, (c) ways to ensure that individuals who need interventions actually receive them, and (d) differences in levels of antisocial behavior.     

Causal condition,causal asymmetry,and the counterfactual analysis of causation

In a recent paper Causal Asymmetry, Douglas Ehring has proposed an intriguing solution to the vexing problem of causal asymmetry. The aim of this paper is to show that his theory is not satisfactory. Moreover, the examples that I use in showing the defect of Ehring's theory also indicate that the counterfactual analysis of causation has a problem that cannot be remedied by Marshall Swain's suggested refinement of the counterfactual analysis of causation in Causation and Distinct Events.     

Evolutionary history versus current causal role in the definition of disorder: reply to McNally

The harmful dysfunction (HD) analysis (Wakefield, American Psychologist 47 (1992a) 373) asserts that "disorder" means "harmful dysfunction", where "harm" is a value concept anchored in social values and "dysfunction" is a factual concept referring to failure of a mechanism to perform a natural function. Additionally, the HD analysis claims that a mechanism's natural functions are its naturally selected effects. McNally (Behaviour Research and Therapy (2000) pp. 309-314) argues to the contrary that "dysfunction" is a value concept referring to negative failures of function, that "function" refers to current causal roles and not evolutionarily designed causal roles, and that "disorder" consequently means "harmful failure of a mechanism to perform a valued current causal role." I reply by showing that McNally's proposals lack the HD analysis's power to explain common judgments about function, dysfunction, and disorder. "Dysfunction" cannot be a negative value concept because many dysfunctions are positive or neutral; "function" cannot refer to current causal roles because many current causal roles are not functions and some functions are not current causal roles; and "disorder" cannot refer to harmful failures of current causal roles because that definition allows almost any negative condition whatever to be a disorder and thus fails to explain the distinctions we make between disorder and non-disorder.     

Autonomous processes in comprehension: A reply to Marslen-Wilson and Tyler

A criterion which has been proposed for distinguishing minds from computing systems is examined from the point of view of some current work on computer induction.     

Time factors in conscious processes: reply to Gilberto Gomes

The critical reinterpretations of Libet's research by G. Gomes make speculative, unwarranted, and untested assumptions. These assumptions and arguments are analyzed and their status relative to Libet's findings is criticized.     

The hierarchical order of processes underlying the direction illusion and the direction aftereffect

Motion perception involves the processing of velocity signals through several hierarchical stages of the visual cortex. To better understand this process, a number of studies have sought to localise the neural substrates of two misperceptions of motion direction, the direction illusion (DI) and the direction aftereffect (DAE). These studies have produced contradictory evidence as to the hierarchical order of the processing stages from which the respective phenomena arise. We have used a simple stimulus configuration to further investigate the sequential order of processes giving rise to the DI and DAE. To this end, we measured the two phenomena invoked in combination, and also manually parsed this combined effect into its two constituents by measuring the two phenomena individually in both possible sequential orders. Comparing the predictions made from each order to the outcome from the combined effect allowed us to test the tenability of two models: the DAE-first model and the DI-first model. Our results indicate that DAE-invoking activity does not occur earlier in the motion processing hierarchy than DI-invoking activity. Although the DI-first model is not inconsistent with our data, the possible involvement of non-sequential processing may be better able to reconcile these results with those of previous studies.     

Probabilities,causation, and logic programming in conditional reasoning: reply to Stenning and Van Lambalgen (2016)

Oaksford and Chater (2014 Oaksford, M., &; Chater, N. (2014). Probabilistic single function dual process theory and logic programming as approaches to non-monotonicity in human vs. artificial reasoning. Thinking and Reasoning, 20, 269–295. doi:10.1080/13546783.2013.877401[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar], Thinking and Reasoning, 20, 269–295) critiqued the logic programming (LP) approach to nonmonotonicity and proposed that a Bayesian probabilistic approach to conditional reasoning provided a more empirically adequate theory. The current paper is a reply to Stenning and van Lambalgen's rejoinder to this earlier paper entitled ‘Logic programming, probability, and two-system accounts of reasoning: a rejoinder to Oaksford and Chater’ (2016) in Thinking and Reasoning. It is argued that causation is basic in human cognition and that explaining how abnormality lists are created in LP requires causal models. Each specific rejoinder to the original critique is then addressed. While many areas of agreement are identified, with respect to the key differences, it is concluded the current evidence favours the Bayesian approach, at least for the moment.     

Interpolation processes in object perception: reply to Anderson (2007)

P. J. Kellman, P. Garrigan, & T. F. Shipley presented a theory of 3-D interpolation in object perception. Along with results from many researchers, this work supports an emerging picture of how the visual system connects separate visible fragments to form objects. In his commentary, B. L. Anderson challenges parts of that view, especially the idea of a common underlying interpolation component in modal and amodal completion (the identity hypothesis). Here the authors analyze Anderson's evidence and argue that he neither provides any reason to abandon the identity hypothesis nor offers a viable alternative theory. The authors offer demonstrations and analyses indicating that interpolated contours can appear modally despite absence of the luminance relations, occlusion geometry, and surface attachment that Anderson claims to be necessary. The authors elaborate crossing interpolations as key cases in which modal and amodal appearance must be consequences of interpolation. Finally, the authors dispute Anderson's assertion that vision researchers are misguided in using objective performance methods, and they argue that his challenges to relatability fail because contour and surface processes, as well as local and global influences, have been distinguished experimentally.     

The influence of complexity and reasoning direction on children's causal reasoning

Causal reasoning is the core and basis of cognition about the objective world. This experiment studied the development of causal reasoning in 86 3.5–4.5-year-olds using a ramp apparatus with two input holes and two output holes [Frye, D., Zelazo, P. D., & Palfai, T. (1995). Theory of mind and rule-based reasoning. Cognitive Development 10, 483–527]. Results revealed that: (1) children performed better on cause–effect inferences than on effect–cause inferences; (2) there was an effect of rule complexity such that uni-dimensional causal inferences were easier than bi-dimensional inferences which, in turn, were easier than tri-dimensional causal inferences; and (3) children's causal reasoning develops rapidly between the ages of age of 3.5 and 4 years.