Agents and Causes: Dispositional Intuitions As a Guide to Causal Structure

Currently, two frameworks of causal reasoning compete: Whereas dependency theories focus on dependencies between causes and effects, dispositional theories model causation as an interaction between agents and patients endowed with intrinsic dispositions. One important finding providing a bridge between these two frameworks is that failures of causes to generate their effects tend to be differentially attributed to agents and patients regardless of their location on either the cause or the effect side. To model different types of error attribution, we augmented a causal Bayes net model with separate error sources for causes and effects. In several experiments, we tested this new model using the size of Markov violations as the empirical indicator of differential assumptions about the sources of error. As predicted by the model, the size of Markov violations was influenced by the location of the agents and was moderated by the causal structure and the type of causal variables.     

THE DISPOSITIONALIST DEITY: HOW GOD CREATES LAWS AND WHY THEISTS SHOULD CARE

How does God govern the world? For many theists “laws of nature” play a vital role. But what are these laws, metaphysically speaking? I shall argue that laws of nature are not external to the objects they govern, but instead should be thought of as reducible to internal features of properties. Recent work in metaphysics and philosophy of science has revived a dispositionalist conception of nature, according to which nature is not passive, but active and dynamic. Disposition theorists see particulars as being internally powerful rather than being governed by external laws of nature, making external laws in effect ontologically otiose. I will argue that theists should prefer a dispositionalist ontology, since it leads them toward the theory of concurrentism in divine conservation, rather than occasionalism, and revives the distinction between internal and external teleology. God on this view does not govern the world through external laws of nature, but rather through internal aspects of powerful properties.     

Causal judgements about two causal candidates: Accounting for occurrences,estimating strength,and the importance of interaction judgements

When two possible causes of an outcome are under consideration, contingency information concerns each possible combination of presence and absence of the two causes with occurrences and nonoccurrences of the outcome. White (2008) proposed that such judgements could be predicted by a weighted averaging model integrating these kinds of contingency information. The weights in the model are derived from the hypothesis that causal judgements seek to meet two main aims, accounting for occurrences of the outcome and estimating the strengths of the causes. Here it is shown that the model can explain many but not all relevant published findings. The remainder can be explained by reasoning about interactions between the two causes, by scenario-specific effects, and by variations in cell weight depending on quantity of available information. An experiment is reported that supports this argument. The review and experimental results support the case for a cognitive model of causal judgement in which different kinds of contingency information are utilised to satisfy particular aims of the judgement process.     

Intuitive understanding of the relation between velocities and masses in simulated collisions

The participants in our experiments were asked to judge whether simulated horizontal collisions appeared to be “natural” or “unnatural”. We manipulated the implied masses and the velocity ratio of two colliding objects. Implied masses were varied through manipulations of the objects' simulated materials (Experiment 1) and sizes (Experiments 2 and 3). For each participant, we determined the interval of velocity ratios that produced “natural” responses most of the time and evaluated how this interval varied as a function of implied masses. The results revealed a fair degree of consistency between predictions of Newtonian mechanics and the participants' responses; this consistency was greater when the implied masses of the colliding objects were varied through manipulations of the simulated materials. Overall, the results support the hypothesis that the cognitive system can integrate multiple sources of stimulus information, enabling individuals to understand multidimensional mechanical events.     

When functions and causes compete

The discounting principle states that ‘the role of a given cause in producing a given effect is discounted if other plausible causes are present’ (Kelley, 1972 Kelley, H. H. 1972. “Attribution theory in social psychology”. In Attribution: Perceiving the causes of behaviour, Edited by: Jones, E., Kanouse, D., Kelley, H., Nisbett, R., Valins, S. and Weiner, B. 1–26. Morristown, NJ: General Learning Press.  [Google Scholar], p. 8). The principle has only been tested with cases where the two explanations are of the same kind (i.e., causal explanations). However, explanations of properties of objects, people, or events often involve functions. Zebras have stripes in order to be better camouflaged. Humans have eyebrows to keep sweat from running into their eyes. Adrenaline is secreted in order to modulate fight and flight responses. Thus, what happens when we are faced with two different kinds of explanation for the same property: one functional and one causal? People evaluated explanations of properties for natural kinds and artefacts. Functional explanations were discounted in favour of causal explanations, however this was only true for properties of artefacts. The presence of an alternative explanation for properties of natural kinds did not affect the plausibility of either kind of explanation.     

Evidence for an illusion of causality when using the Implicit Association Test to measure learning

Our ability to detect causal relations and patterns of covariation is easily biased by a number of well-known factors. For example, people tend to overestimate the strength of the relation between a cue and an outcome if the outcome tends to occur very frequently. During the last years, several accounts have attempted to explain the outcome-density bias. On the one hand, dual-process performance accounts propose that biases are not due to the way associations are encoded, but to the higher-order cognitive processes involved in the retrieval and use of this information. In other words, the outcome-density bias is seen as a performance effect, not a learning effect. From this point of view, it is predicted that the outcome-density bias should be absent in any testing procedure that reduces the motivation or opportunity to engage in higher-order cognitive processes. Contrary to this prediction, but consistent with the most common single-process learning accounts, our results show that the outcome-density effect can be detected when the Implicit Association Test is used to measure the strength of cue–outcome associations.     

Sticking to the Evidence? A Behavioral and Computational Case Study of Micro‐Theory Change in the Domain of Magnetism

Constructing an intuitive theory from data confronts learners with a “chicken‐and‐egg” problem: The laws can only be expressed in terms of the theory's core concepts, but these concepts are only meaningful in terms of the role they play in the theory's laws; how can a learner discover appropriate concepts and laws simultaneously, knowing neither to begin with? We explore how children can solve this chicken‐and‐egg problem in the domain of magnetism, drawing on perspectives from computational modeling and behavioral experiments. We present 4‐ and 5‐year‐olds with two different simplified magnet‐learning tasks. Children appropriately constrain their beliefs to two hypotheses following ambiguous but informative evidence. Following a critical intervention, they learn the correct theory. In the second study, children infer the correct number of categories given no information about the possible causal laws. Children's hypotheses in these tasks are explained as rational inferences within a Bayesian computational framework.     

Methodological Challenges in Causal Research on Racial and Ethnic Patterns of Cognitive Trajectories: Measurement, Selection, and Bias

Research focused on understanding how and why cognitive trajectories differ across racial and ethnic groups can be compromised by several possible methodological challenges. These difficulties are especially relevant in research on racial and ethnic disparities and neuropsychological outcomes because of the particular influence of selection and measurement in these contexts. In this article, we review the counterfactual framework for thinking about causal effects versus statistical associations. We emphasize that causal inferences are key to predicting the likely consequences of possible interventions, for example in clinical settings. We summarize a number of common biases that can obscure causal relationships, including confounding, measurement ceilings/floors, baseline adjustment bias, practice or retest effects, differential measurement error, conditioning on common effects in direct and indirect effects decompositions, and differential survival. For each, we describe how to recognize when such biases may be relevant and some possible analytic or design approaches to remediating these biases.     

Expressed emotion and causal attributions in relatives of post-traumatic stress disorder patients

This study investigates the relationship between expressed emotion (EE) and causal attributions in relatives of post-traumatic stress disorder (PTSD) patients, and examines the contributions of EE and attributions to patient outcomes. Thirty-eight relatives of patients with PTSD participating in a treatment trial were assessed on EE, causal attributions for patient problems and nature of attributions. Patients' PTSD symptoms at 6 and 12 months were assessed. Criticism and hostility in relatives were associated with attributing problems to factors controllable by patients. Relatives with marked emotional over-involvement (EOI) had an attributional profile similar to low EE relatives. Deficits in normal behaviour ("negative symptoms") were perceived as more controllable, internal and stable than were more obvious signs of an illness or mental health problem such as hypervigilance and intrusive thoughts and nightmares ("positive symptoms"). Irritability or anger was perceived as more controllable and personal than any other problem. Hostility was associated with less psychological understanding. EE (hostility) but not attributions was found to predict clinical outcome. The results are consistent with previous studies of relatives of schizophrenia patients. The study suggests a need for interventions, which focus on helping relatives to reappraise the impact of PTSD.     

针刺作用四大规律的统一与现代针灸学理论的发展

探求事物的内在联系或内在统一性是科学活动的重要目标。针刺作用的四大规律：针刺作用的双向调节规律、针刺手法作用的基本规律、针刺时间作用的基本规律、针刺作用的时效规律,其所涉及的影响因素各不相同,但这四大作用规律在“机能状态”这个基本环节获得了统一。