Good Athlete – Bad Athlete? on the ‘Role-Model Argument’ for Banning Performance-Enhancing Drugs

The paper critically discusses a role-model argument (RMA) in favour of banning performance-enhancing drugs in sport. The argument concludes that athletes should be banned from using performance-enhancing drugs because if they are allowed to use such drugs they will encourage, or cause, youngsters who look up to them to use drugs in a way that would be harmful. In Section 2 the structure of the argument and some versions of it are presented. In Section 3 a critical discussion of RMA is presented. It is argued that we should be reluctant to accept the argument as it stands for at least three reasons: (i) it rests on an unsupported empirical claim; (ii) it also makes a false empirical claim; and (iii) the normative premise of the argument is too demanding morally. Further objections to the RMA are also discussed, but argued to be beside the point     

Negation: A theory of its meaning,representation, and use

This article presents a model-based theory of what negation means, how it is mentally represented, and how it is understood. The theory postulates that negation takes a single argument that refers to a set of possibilities and returns the complement of that set. Individuals therefore tend to assign a small scope to negation in order to minimize the number of models of possibilities that they have to consider. Individuals untrained in logic do not know the possibilities corresponding to the negation of compound assertions formed with if, or, and and, and have to infer the possibilities one by one. It follows that negations are easier to understand, and to formulate, when individuals already have in mind the possibilities to be negated. The paper shows that the evidence, including the results of recent studies, corroborates the theory.     

Grounding Bayesian accounts of numerosity and variability effects in a similarity-based framework: the case of self-organising maps

ABSTRACT

In this paper, we propose self-organising maps as possible candidates to explain the psychological mechanisms underlying category generalisation. Self-organising maps are psychologically and biologically plausible neural network models that can learn after limited exposure to positive category examples, without any need of contrastive information. They reproduce human behaviour in category generalisation, in particular, the Numerosity and Variability effects, which are usually explained with Bayesian tools. Where category generalisation is concerned, self-organising maps deserve attention to bridge the gap between the computational level of analysis in Marr's hierarchy (where Bayesian models are often situated) and the algorithmic level of analysis in which plausible mechanisms are described.     

Heterogeneous factor analysis models: A bayesian approach

Multilevel factor analysis models are widely used in the social sciences to account for heterogeneity in mean structures. In this paper we extend previous work on multilevel models to account for general forms of heterogeneity in confirmatory factor analysis models. We specify various models of mean and covariance heterogeneity in confirmatory factor analysis and develop Markov Chain Monte Carlo (MCMC) procedures to perform Bayesian inference, model checking, and model comparison.We test our methodology using synthetic data and data from a consumption emotion study. The results from synthetic data show that our Bayesian model perform well in recovering the true parameters and selecting the appropriate model. More importantly, the results clearly illustrate the consequences of ignoring heterogeneity. Specifically, we find that ignoring heterogeneity can lead to sign reversals of the factor covariances, inflation of factor variances and underappreciation of uncertainty in parameter estimates. The results from the emotion study show that subjects vary both in means and covariances. Thus traditional psychometric methods cannot fully capture the heterogeneity in our data.     

Simple matrix methods for analyzing diffusion models of choice probability, choice response time, and simple response time

Diffusion processes (e.g., Wiener process, Ornstein-Uhlenbeck process) are powerful approaches to model human information processes in a variety of psychological tasks. Lack of mathematical tractability, however, has prevented broad applications of these models to empirical data. This tutorial explains step by step, using a matrix approach, how to construct these models, how to implement them on a computer, and how to calculate the predictions made by these models. In particular, we present models for binaries choices for unidimensional and multiattribute choice alternatives; for simple reaction time tasks; and for three alternatives choice problems.     

犯罪行为决策的理论与研究方法

犯罪行为是犯罪人决策的结果。犯罪行为决策研究旨在通过运用认知心理学的有关原理,说明犯罪行为实施之前的行为决策过程及影响因素,其成果能为国家制定刑事政策与犯罪预防政策等提供理论依据。犯罪行为决策的理论模型主要可分为犯罪理性模型、犯罪期望效用模型和犯罪前景理论模型。犯罪行为决策的研究方法主要采用心理物理法、过程追踪法、访谈法、投射测验法和犯罪统计法等。展望未来,应进一步探讨犯罪行为决策的理性与非理性问题,并加强对犯罪行为决策的验证性研究。     

信息保持、短时存贮与执行控制的脑模型

工作记忆的脑机制是认知神经科学研究的重要问题。研究者在分析大量脑成像研究数据的基础上,创建了许多解释工作记忆神经基础的模型。Smith和Jonides发展了工作记忆成分结构模型和贮存与执行加工分离模型。Postle和D’Esposito建构了工作记忆相对表征混合模型,D’Esposito, Postle和Rypma阐述了工作记忆加工阶段动态模型。Fletcher和Henson提出工作记忆额叶分区整合理论。该文通过对上述模型或理论的评价,总结了工作记忆脑成像研究中存在的问题,展望了该研究领域的发展趋势。     

文本加工中情境模型建构的五个维度

情境模型理论是当代西方文本阅读加工的一个重要理论。该文通过详细介绍情境模型建构的空间、时间、因果、主人公、意图五大维度,以助于对情境模型理论整体理解。通过总结可知,目前国内外关于情境模型建构中的空间、因果和主人公三个维度的研究成果较多,研究范式也较为成熟,时间和意图维度则研究成果较少     

Efficient nonparametric approaches for estimating the operating characteristics of discrete item responses

Rationale and the actual procedures of two nonparametric approaches, called Bivariate P.D.F. Approach and Conditional P.D.F. Approach, for estimating the operating characteristic of a discrete item response, or the conditional probability, given latent trait, that the examinee's response be that specific response, are introduced and discussed. These methods are featured by the facts that: (a) estimation is made without assuming any mathematical forms, and (b) it is based upon a relatively small sample of several hundred to a few thousand examinees.Some examples of the results obtained by the Simple Sum Procedure and the Differential Weight Procedure of the Conditional P.D.F. Approach are given, using simulated data. The usefulness of these nonparametric methods is also discussed.This research was mostly supported by the Office of Naval Research (N00014-77-C-0360, N00014-81-C-0569, N00014-87-K-0320, N00014-90-J-1456).