主观概率判断的支持理论

支持理论是一个关于主观概率判断的非外延性理论,它有以下几个主要观点：1.主观概率判断受到描述的影响,具有描述的依赖性;2.主观概率判断的结果是判断者对中心假设的相对支持的反映;3.主观概率在二元判断中表现出二元互补性,在多元判断中表现出次可加性;4.主观概率判断存在分解效应和促进效应     

青少年学生自立人格的结构——基于中国人人格量表（QZPS）的结果

以中国人人格量表(QZPS)的项目为基础,经由大学生、高中生和初中生自己的挑选,编制出了探索青少年学生自立人格结构的<大学生问卷>、<高中生问卷>、<初中生问卷>和<青少年学生问卷>.分别对大学生、高中生和初中生进行调查和探索性因素分析后发现:①<大学生问卷>、<初中生问卷>与<青少年学生问卷>显示的自立人格都为个人责任(坚韧严谨)、个人主动(追求卓越)、人际开放(宽容随和)和人际主动(积极活跃);②<高中生问卷>显示的自立人格包括个人主动(追求卓越)、人际主动(积极活跃)、人际开放(宽容随和)、人际责任(坦诚记恩)和个人责任(坚韧严谨).最后,对青少年学生自立人格特质的分领域聚焦性等问题进行了讨论.     

不同年龄阶段Stroop效应及反转Stroop效应的特点

本实验以中学生和大学生为被试对Stroop效应及反转Stroop效应的年龄特征进行了研究,结果发现:在错误率指标上存在显著的年龄主效应,初中生的错误率显著高于大学生和高中生,高中生和大学生的差异不显著;颜色判断和单字判断任务中,不一致条件的反应时和错误率都显著高于一致条件的反应时和错误率,即两种任务分别产生了Stroop效应和反转的Stroop效应.     

青少年学生的自立人格

经过5个步骤编制出了人格特质词的《大学生问卷》、《高中生问卷》、《初中生问卷》和《青少年学生问卷》,分别对大学生、高中生和初中生进行调查和探索性因素分析。结果发现：①《大学生问卷》显示的自立人格包括主动性、开放性、人际责任、积极性和独立性五个维度;②《高中生问卷》显示的自立人格包括人际开放与责任性、灵活与独立性、主动性和行为责任四个维度;③《初中生问卷》显示的自立人格包括主动与行为责任、开放性、人际责任、积极性、灵活与独立性五个维度;④《青少年学生问卷》显示的自立人格包括灵活与独立性、责任性、主动性、人际开放四个维度。最后,对自立人格构念的合理性、自立人格中“开放性”与“责任性”维度的特点、青少年学生自立人格结构的一致性程度以及本研究在探索自立人格结构方面的优劣等问题进行了讨论     

中国中学生和大学生幸福感常模的制定

为建立中国中学生和大学生的幸福感常模，采用青少年幸福感问卷，在全国31个省（自治区、直辖市）取样43536名被试进行测量。结果发现：（1）青少年幸福感问卷的信效度达到可接受水平；（2）高中生的整体幸福感水平显著低于初中生和大学生；（3）家庭居住在市区的初、高中生的整体幸福感水平显著高于居住在县城和乡镇的学生。所建立的初中生、高中生和大学生的平均分常模和百分等级常模可作为评价学生幸福感的参照标准。     

青少年内隐与外显自尊的比较研究

运用两种程序分别测量了青少年的内隐自尊与外显自尊。内隐自尊由内隐联想测验测量,外显自尊由三项自尊量表测量。研究结果表明:在不同年龄阶段与不同性别的青少年中内隐自尊普遍存在;无论是内隐自尊还是外显自尊都不存在显著的性别差异;内隐自尊无显著的年龄差异;外显自尊存在显著的年龄差异,其中高中生比初中生和大学生有更低的外显自尊;内隐自尊与外显自尊之间无显著相关。     

家庭功能对青少年疏离感的影响: 有调节的中介效应

采用问卷法调查了608名初一至高二城市青少年, 通过结构方程模型探讨了青少年疏离感与家庭社会经济地位、家庭功能和同伴接纳的关系。结果发现: (1) 青少年疏离感年龄段差异显著, 高中生的疏离感显著高于初中生; (2) 青少年疏离感的三个维度之间存在显著差异。其中环境疏离感最高, 其次是社会疏离感, 人际疏离感最低; (3) 家庭功能在家庭社会经济地位与青少年疏离感之间起完全中介作用, 这一中介作用的实现受到同伴接纳的调节, 即家庭功能对青少年疏离感的影响是有调节的中介效应。     

社会距离与合作指数对不同年龄青少年合作行为影响的差异

本研究采用重复囚徒困境实验范式,考察了社会距离和合作指数对不同年龄青少年（初中生、高中生和大学生,且每个年龄段的被试数为40名）在博弈决策中的合作行为的影响。结果发现：（1）随着年龄的增加,青少年合作行为的总体趋势表现为下降;（2）社会距离对大学生的合作行为的正向作用显著,而中学生的合作行为却不受其影响;（3）个体合作率会受到合作指数的促进作用,但这种促进作用在大学生中表现的更为显著。即随年龄增长,个体会更少的采取合作行为,并且个体是否采取合作在更大程度上基于当前博弈中的收支情况和与博弈对象之间的社会距离。     

社会支持、学习观和自我效能感对学习主观幸福感的影响

通过对469名初中生的问卷调查,考察社会支持、学习观、自我效能感与学习主观幸福感的关系。结果表明:(1)初中生学习主观幸福感总体在中等水平以上,不存在性别差异;非重点学校学生学习主观幸福感低于重点学校的学生;学习主观幸福感随年级的升高而逐渐降低。(2)控制了人口学变量的影响后,社会支持、学习观和自我效能感对学习主观幸福感仍有显著影响,其中自我效能感对学习主观幸福感的影响作用较大。(3)社会支持对初中生学习主观幸福感既具有直接影响,同时也具有间接影响;初中生学习观和自我效能感在社会支持和学习主观幸福感之间起着部分中介作用。     

亲子沟通类型与青少年社会适应的关系

从北京市一所普通中学和济南市一所重点中学选取初一至高三六个年级720名学生为被试,探讨亲子沟通类型与青少年社会适应的关系。要求被试分别报告亲子沟通、学习成绩、自尊、抑郁、羞怯和问题行为的情况。结果发现:(1)在青少年与父母的沟通中,关系定向的沟通明显多于观念定向的沟通;随着年级的增长,关系定向和观念定向的沟通都有明显的增加;(2)在亲子沟通的类型中,保护型亲子沟通最多,其次为多元型亲子沟通,放任型和一致型亲子沟通最少;四种亲子沟通的年级分布存在明显的差异,初中生的放任型和保护型亲子沟通多于高中生,而高中生的多元型和一致型亲子沟通多于初中生;(3)同一种亲子沟通既可能促进青少年的积极社会适应,同时也可能增加青少年的消极社会适应。     

A random support model of the calibration of subjective probabilities

A stochastic model of the calibration of subjective probabilities based on support theory (Rottenstreich and Tversky, 1997, Tversky and Koehler, 1994) is presented. This model extends support theory—a general representation of probability judgment—to the domain of calibration, the analysis of the correspondence between subjective and objective probability. The random support model can account for the common finding of overconfidence, and also predicts the form of the relationship between overconfidence and item difficulty (the “hard–easy effect”). The parameters of the model have natural psychological interpretations, such as discriminability between correct and incorrect hypotheses, and extremity of judgment. The random support model can be distinguished from other stochastic models of calibration by: (a) using fewer parameters, (b) eliminating the use of variable cutoffs by mapping underlying support directly into judged probability, (c) allowing validation of model parameters with independent assessments of support, and (d) applying to a wide variety of tasks by framing probability judgment in the integrative context of support theory.     

Decision by sampling: The role of the decision environment in risky choice

Decision by sampling (DbS) is a theory about how our environment shapes the decisions that we make. Here, I review the application of DbS to risky decision making. According to classical theories of risky decision making, people make stable transformations between outcomes and probabilities and their subjective counterparts using fixed psychoeconomic functions. DbS offers a quite different account. In DbS, the subjective value of an outcome or probability is derived from a series of binary, ordinal comparisons with a sample of other outcomes or probabilities from the decision environment. In this way, the distribution of attribute values in the environment determines the subjective valuations of outcomes and probabilities. I show how DbS interacts with the real-world distributions of gains, losses, and probabilities to produce the classical psychoeconomic functions. I extend DbS to account for preferences in benchmark data sets. Finally, in a challenge to the classical notion of stable subjective valuations, I review evidence that manipulating the distribution of attribute values in the environment changes our subjective valuations just as DbS predicts.     

Decision Theory and Vocational Counseling: Important Concepts and Questions

Ignorance of specifics of career decision-making processes has prevented development and use of more effective vocational counseling procedures. Simply giving clients vocational information and assuming rational use of it is criticized. Contemporary decision theories suggest several relevant variables. Two variables, subjective probabilities (individual's self-estimates of success) and utilities (desirabilities held for outcomes or alternatives), are discussed in relation to presenting clients with objective probability information concerning future plans. Some relevant research is reviewed and two questions are discussed: (1) How do different methods of presenting information influence subjective probabilities? (2) How are utilities influenced by objective probability data?     

Children and chess expertise: The role of calibration

Summary Three studies of calibration are reported. Calibration refers to the accuracy with which one can predict one's own performance. In the first study child chess players, non-chess playing parents, and statistics students were asked to predict chances of winning chess games against hypothetical opponents. These subjective probabilities were compared to the actual probabilities, based on the Elo rating system. Better players' predictions were better calibrated. Confidence and ratings are negatively correlated, indicating that with lower ratings, players are overconfident. Skilled child players' predictions were better calibrated than any of the adults'. In the second study subjects were asked to estimate chances of winning in conjunctive situations, e. g., winning all the rounds in a tournament. Again, better child players were more accurate in their predictions and more accurate than adults. In the third study, child players were asked to predict their chances of winning in a non-chess domain after hearing a hypothetical win/loss history. Higher-rated players' predictions were again better calibrated, even though the domain was outside their expertise. The motivational and cognitive implications of calibration are discussed.     

On Setting Response Criteria for Calibrated Subjective Probability Estimates

Framing the issue of subjective probability calibration in signal-detection-theory terms, this paper first proves a theorem regarding the placement of well-calibrated response criteria and then develops an algorithm guaranteed to find such criteria, should they exist. Application of this algorithm to tasks varying in difficulty and number of response categories shows that perfect calibration is easiest to attain under median difficulty levels (d' approximately 1.4) and is practically or theoretically impossible to attain when the task is either very hard (d' approximately 0.5) or very easy (d' approximately 10). Implications for calibration research, including the hard-easy effect, are discussed. Copyright 2001 Academic Press.     

The Calibration Issue: Theoretical Comments on Suantak,Bolger, and Ferrell (1996)

In this comment on a recent article in this journal on calibration of subjective probabilities by Suantak, Bolger, and Ferrell (1996) we point to methodological problems with the data presented in the article, with computer simulations we demonstrate that the results claimed by the authors to refute the ecological models (Gigerenzer, Hoffrage, & Kleinbölting, 1991; Juslin, 1994) are actually predicted by them, and we respond to the criticisms of the notion of “ecological cue validity.” It is further argued that contrary to the claims by the authors: Thedecision variable partition modeladvocated by the authors fails to account for the results reported in the article, but there is one error model—thecombined error model(Juslin, Olsson, & Björkman, 1997)—that predicts the observed symmetric hard-easy effect with crossover at proportion correct .75. Finally, an analysis of 44 cognitive and 21 sensory tasks demonstrates that there is a difference in calibration for sensory and cognitive tasks.     

Emotion as a boost to metacognition: How worry enhances the quality of confidence

Emotion and cognition are known to interact during human decision processes. In this study we focus on a specific kind of cognition, namely metacognition. Our experiment induces a negative emotion, worry, during a perceptual task. In a numerosity task subjects have to make a two alternative forced choice and then reveal their confidence in this decision. We measure metacognition in terms of discrimination and calibration abilities. Our results show that metacognition, but not choice, is affected by the level of worry anticipated before the decision. Under worry individuals tend to have better metacognition in terms of the two measures. Furthermore understanding the formation of confidence is better explained with taking into account the level of worry in the model. This study shows the importance of an emotional component in the formation and the quality of the subjective probabilities.     

Deterministic probability: neither chance nor credence

Some have argued that chance and determinism are compatible in order to account for the objectivity of probabilities in theories that are compatible with determinism, like Classical Statistical Mechanics (CSM) and Evolutionary Theory (ET). Contrarily, some have argued that chance and determinism are incompatible, and so such probabilities are subjective. In this paper, I argue that both of these positions are unsatisfactory. I argue that the probabilities of theories like CSM and ET are not chances, but also that they are not subjective probabilities either. Rather, they are a third type of probability, which I call counterfactual probability. The main distinguishing feature of counterfactual-probability is the role it plays in conveying important counterfactual information in explanations. This distinguishes counterfactual probability from chance as a second concept of objective probability.     

Bayesian decision theory,subjective and objective probabilities,and acceptance of empirical hypotheses

It is argued that we need a richer version of Bayesian decision theory, admitting both subjective and objective probabilities and providing rational criteria for choice of our prior probabilities. We also need a theory of tentative acceptance of empirical hypotheses. There is a discussion of subjective and of objective probabilities and of the relationship between them, as well as a discussion of the criteria used in choosing our prior probabilities, such as the principles of indifference and of maximum entropy, and the simplicity ranking of alternative hypotheses.     

A dual to the von Neumann-Morgenstern theorem

The paper examines Ramsey's proposition that preferences among uncertain prospects may be represented in terms of subjectively expected subjective values. While the von Neumann-Morgenstern approach presupposes probabilities and derives values, the present approach does the reverse: it presupposes values and derives probabilities. Necessary and sufficient conditions are presented for such representations for a fairly wide range of preference structures, including discrete as well as continuous spaces of states-of-nature. An operational procedure is suggested for constructing the subjective values and probabilities.