The Role of Consistent Context in Rapid Movement Planning: Suboptimal Endpoint Adjustment to Changing Rewards

The authors' purpose was to determine if participants adjusted their endpoint during a rapid aiming task in the context of changing rewards and whether participants needed consistent feedback to do so. Participants aimed to a target that was overlapped by a penalty region. Participants gained points for hitting the target but lost points for hitting the penalty region. The reward value associated with target contact either changed trial to trial, reducing consistent feedback (variable condition) or changed between blocks of trials (blocked condition) with the repetition of reward value within a block increasing the consistency of feedback. Participants adjusted their endpoints with changing reward value in the blocked but not variable condition indicating consistent feedback is needed to adjust endpoint to changing rewards.     

思想史的"两重性"探求及意义衍生--李锦全先生对中国思想史本质的诠释

思想史的“两重性”是李锦全先生关注的焦点问题。文章通过考察他对思想史进行个案研究、学派分析、整体通观三个层次的翔实分析,探求他贯穿在对象研究中的“哲史融会”的方法取向和“承传创新”的文化立场,揭示他以传统观照现代的实践品格,把学术与社会紧密结合的学人精神。     

Improving judgmental forecasts with judgmental bootstrapping and task feedback support

This study examines the utility of two widely advocated methods for supporting judgmental forecasts—providing task feedback and providing judgmental bootstrapping support. In a simulated laboratory based experiment that focused on producing composite sales forecasts from three individual components, we compared the effectiveness of these two methods in improving final judgmental forecasts. In the presence of cognitive feedback task, feedback led to better forecasts than providing judgmental bootstrap forecasts. Simply providing bootstrap forecasts was of no additional benefit over a control condition. This was true in terms of the Brunswik Lens model measures of achievement, knowledge, and consistency, and in terms of forecast accuracy. This occurred both in stable environments and when special events (unusual one‐time events requiring adjustments to the forecasts) arose. Copyright © 2005 John Wiley & Sons, Ltd.     

Combinator Logics

Combinator logics are a broad family of substructual logics that are formed by extending the basic relevant logic B with axioms that correspond closely to the reduction rules of proper combinators in combinatory logic. In the Routley-Meyer relational semantics for relevant logic each such combinator logic is characterized by the class of frames that meet a first-order condition that also directly corresponds to the same combinator's reduction rule. A second family of logics is also introduced that extends B with the addition of propositional constants that correspond to combinators. These are characterized by relational frames that meet first-order conditions that reflect the structures of the combinators themselves.     

Wofür sprechen die Daten?

What Do the Data Tell Us? Justification of scientific theories is a three-place relation between data, theories, and background knowledge. Though this should be a commonplace, many methodologies in science neglect it. The article will elucidate the significance and function of our background knowledge in epistemic justification and their consequences for different scientific methodologies. It is argued that there is no simple and at the same time acceptable statistical algorithm that justifies a given theory merely on the basis of certain data. And even if we think to know the probability of a theory, that does not decide whether we should accept it or not.     

内隐学习研究方法述评

内隐学习自提出以来就成为认知心理学研究的热点,近40年内隐学习领域的研究在本质上都基于几种经典的研究方法和实验逻辑。本文拟对这些代表性的内隐学习研究方法做系统的介绍和归纳。     

共同方法变异的影响及其统计控制途径的模型分析

共同方法变异(common method variance, CMV)指两个变量之间变异的重叠是因为使用同类测量工具而导致, 而不是代表潜在构念之间的真实关系。虽然以往研究显示CMV不一定导致研究结果的偏差, 在实际研究中应当加以考量。特别是在使用测量方法的研究中, 如果数据来源越单一, 测量方法越类似, CMV效应使研究结果产生偏差的可能性越大。CMV效应的控制方法包括过程控制法和统计控制法。在统计控制法的选择和使用上, 需要重点考虑该方法是否分离了三大变异(特质变异、方法变异和误差变异), CMV效应是在测量构念层面还是题目层面, CMV效应是加法效应还是乘法效应。控制潜在方法因子途径是统计控制方法中最重要的一类方法, 理解其模型是正确使用这类方法的前提。未来研究应当关注多个研究的CMV效应和侧重评估某个理论研究中CMV所引起的潜在的效度威胁。     

"Just looking at food makes me gain weight": experimental induction of thought-shape fusion in eating-disordered and non-eating-disordered women

Thought-shape fusion (TSF) is a cognitive distortion that can be induced experimentally and is associated with eating pathology. The current study was conducted in order to elucidate the effects of TSF induction in females with eating disorders (n=35), as well as in restrained eaters (n=38) and unrestrained eaters (n=39). It was hypothesized that TSF induction would result in anxiety, guilt, increased feelings of fatness, perceived weight gain and feelings of moral wrong-doing relative to an anxiety and control induction. It was further hypothesized that restrained eaters and individuals with eating disorders would exhibit a stronger reaction to a TSF induction than would unrestrained eaters. The results indicated that, as predicted, TSF can be induced in individuals both with and without eating disorders, and individuals with eating disorders reported the highest levels of "state" TSF after the induction relative to the non-clinical controls. However, contrary to expectations, restrained eaters reported higher levels of perceived weight gain and moral wrong-doing after the anxiety induction (but not the TSF induction) relative to the control induction. Potential mechanisms for this pattern of results are discussed, and the clinical implications of research on TSF are also considered.     

A multilevel framework for understanding relationships among traits,states, situations and behaviours

A conceptual and analytic framework for understanding relationships among traits, states, situations, and behaviours is presented. The framework assumes that such relationships can be understood in terms of four questions. (1) What are the relationships between trait and state level constructs, which include psychological states, the situations people experience and behaviour? (2) What are the relationships between psychological states, between states and situations and between states and behaviours? (3) How do such state level relationships vary as a function of trait level individual differences? (4) How do the relationships that are the focus of questions 1, 2, and 3 change across time? This article describes how to use multilevel random coefficient modelling (MRCM) to examine such relationships. The framework can accommodate different definitions of traits and dispositions (Allportian, processing styles, profiles, etc.) and different ways of conceptualising relationships between states and traits (aggregationist, interactionist, etc.). Copyright © 2007 John Wiley & Sons, Ltd.