中国公共健康伦理学的理论自觉与范式转换

理论自觉不仅直接关乎中国特色公共健康伦理学的理论构建,也直接关乎中国公共健康伦理学的持续发展和现实功能的发挥。中国公共健康伦理学的理论自觉包括对学科关系、中西关系、古今关系以及理论与实践关系的自觉等四个基本维度;其问题域或基本理论结构包括本体论层面的基本问题、对象问题和范畴问题,认识论层面的视角和向度问题以及价值论层面的发展取向、价值追求和学者的价值选择问题。范式意识的自觉是中国公共健康伦理学理论自觉的方法论标志。当前,中国公共健康伦理学研究范式应该实现从西方范式向马克思主义范式、从个体论或整体论向个体论与整体论相结合的范式、从职业伦理或实践伦理向职业伦理与实践伦理相结合的范式转换。     

道器之辨中的三种范式及其转换

道器之辨在中国哲学发展史上形成了三种理论范式并实现了范式转换,即从汉唐宇宙生成论范式下的"道先器后"说转换为宋明本体论范式下的"道体器用"说,进而在明清之际转换为生存论范式下的"治器显道"说,而生存论范式开启了人文主义视野和趋时更新的开放价值取向。     

心理理论的自发反应范式：方法、结果与解释

近30年来, 心理理论一直是认知发展领域关键而充满挑战的研究主题, 儿童理解他人错误信念的能力是心理理论发展的标志。诱导反应范式(elicited-response tasks)的研究结果表明4岁时儿童获得心理理论, 但是自发反应范式(spontaneous-response tasks)的研究结果表明婴儿15个月大时就已经具备心理理论。自发反应范式(spontaneous-response task) 是近些年来心理理论研究领域发展起来的研究范式。针对幼儿能通过自发反应范式却不能通过诱导反应范式这一问题, 已有三种相关的理论解释：早期能力掩盖说、内隐知识解释论和观点追踪解释论。未来心理理论研究应注意将自发反应范式运用于特殊儿童, 并进一步验证和研究心理理论的发展机制。     

心理研究中引入贝叶斯统计推断的必要性、应用思路与领域

本文从科学范式演变和概率统计推断特征分析出发,就贝叶斯统计推断引入心理学的必要性、怎么应用、在哪些领域应用集中进行了论述。首先在分析科学范式演进各阶段统计推断任务需要、经典的频率概率统计推断不足基础上,得出科学范式处于危机和革命阶段时需要对相关理论做可信度检验。然后,在介绍贝叶斯定理及其统计推断的基础上,进一步分析了贝叶斯推断能解决理论可信度的多种假设检验情景。最后本文还就贝叶斯统计推断在心理学理论争鸣与建构、心理技术产品开发与评估具体领域应用做了分析。     

库恩的范式论及其在心理学革命上的有效性

文中,把库恩的范式论及其在心理学革命上的有效性分为几个部分来论述:库恩科学哲学的理论基础——范式论;他的范式论在心理学革命上的应用;他的范式论的贡献和局限。最后,笔者认为心理学革命必须在辩证唯物主义和历史唯物主义的指导下才能成功。     

职业发展的混沌理论

传统职业理论主要是还原论范式的,包括结构论和过程论;自引入混沌理论以来,职业发展的研究范式发生了重大转变;文章在国外相关研究的基础从3个方面深入分析了职业发展的混沌特征,包括初值敏感性,分形和吸引子的作用,通过分析指出这一理论在职业咨询中的应用及其对理论研究的启示     

心理研究引入贝叶斯统计推断的必要性、应用思路与领域

本文从科学范式演变和概率统计推断特征分析出发,就贝叶斯统计推断引入心理学的必要性、怎么应用、在哪些领域应用进行了论述。首先在分析科学范式演进各阶段统计推断任务需要、经典的频率概率统计推断不足基础上,得出科学范式处于危机和革命阶段时需要对相关理论做可信度检验。然后,在介绍贝叶斯定理及其统计推断的基础上,进一步分析了贝叶斯推断能解决理论可信度的多种假设检验情景。最后本文还就贝叶斯统计推断在心理学理论争鸣与建构、心理技术产品开发与评估具体领域应用做了分析。     

发展科学及其语境论趋势探析

近年来,生物(遗传)-文化(坏境)共同构成论的语境论世界观在发展科学的元理论层面逐渐占据了主导地位,用以解释生命发展系统中深层的多方向、多维度的动态层级结构。由此,发展科学中已经逐渐形成了以辩证唯物主义思想为核心,进而整合语境论和机体论世界观的关联论和关联的发展系统范式。这种包含着丰富语境论思想的关联的发展系统范式可以更好地容纳发展科学中的新数据,为发展科学的进一步研究提供哲学基础,为心理学、社会学和人类学中涉及的个体发育和演化问题提供新的理论依据。     

特征捆绑机制的理论模型

捆绑问题被认为是认知科学和神经科学的中心问题之一,对心理过程的认知神经机制研究起到了重要推动作用。特征捆绑机制研究有认知和神经科学两大范式。特征整合论在认知理论中最具代表性,形式理论修正了其在错觉性结合测量等方面的不足,双阶段理论突出了前注意捆绑。时间同步性理论是影响最大的捆绑理论,神经网络模型为捆绑机制提出了更具体的结构模型。两大范式的整合及由低级认知过程向高级心理过程的深化可能是今后捆绑机制研究的重点     

少数民族地区马克思主义宗教观教育的重要性

针对我国少数民族地区的发展的问题,学者们提出几种理论范式：经济论、文化论和规制论等观点。相比较而言,马克思主义宗教观教育从根本上给定了宗教的本质,宗教教义,宗教礼仪制度的科学含义,从而给信教群众无论从心里上,还是宗教生活上以及宗教的观点态度上的科学指导。     

Instance-based learning: integrating sampling and repeated decisions from experience

In decisions from experience, there are 2 experimental paradigms: sampling and repeated-choice. In the sampling paradigm, participants sample between 2 options as many times as they want (i.e., the stopping point is variable), observe the outcome with no real consequences each time, and finally select 1 of the 2 options that cause them to earn or lose money. In the repeated-choice paradigm, participants select 1 of the 2 options for a fixed number of times and receive immediate outcome feedback that affects their earnings. These 2 experimental paradigms have been studied independently, and different cognitive processes have often been assumed to take place in each, as represented in widely diverse computational models. We demonstrate that behavior in these 2 paradigms relies upon common cognitive processes proposed by the instance-based learning theory (IBLT; Gonzalez, Lerch, & Lebiere, 2003) and that the stopping point is the only difference between the 2 paradigms. A single cognitive model based on IBLT (with an added stopping point rule in the sampling paradigm) captures human choices and predicts the sequence of choice selections across both paradigms. We integrate the paradigms through quantitative model comparison, where IBLT outperforms the best models created for each paradigm separately. We discuss the implications for the psychology of decision making.     

Maximizing Scales Do Not Reliably Predict Maximizing Behavior in Decisions from Experience

In this paper, we explore the relationships between psychometric and behavioral measures of maximization in decisions from experience (DfE). In two experiments, we measured choice behavior in two experimental paradigms of DfE and self‐reported maximizing tendencies using three prominent scales of maximization. In the repeated consequentialist choice paradigm, participants made repeated choices between two unlabeled options and received consequential feedback on each trial. In the sampling paradigm, participants freely sampled from two options and received feedback on their sampling before making a single consequential choice. Individuals exhibited different degrees of maximizing behavior in both paradigms and across different payoff distributions, but none of the maximizing scales predicted this behavior. These results indicate that maximization scales address constructs that are different from the maximization behavior observed in DfE, and that these measures will need to be improved to reflect behavioral aspects of choice and search from experience. Copyright © 2017 John Wiley & Sons, Ltd.     

Differences Between Minority,Majority, and Unanimous Group Members in the Communication of Information

This article integrates research on minority influence and information sampling in groups. The traditional information‐sampling paradigm implies that the discussion bias for common over unique information affects all types of groups universally. We proposed an alternative in which information sampling depends on the composition of opinions. We proposed that groups with a minority opinion may focus more on unique information and that a minority opinion may lead majority members to consider more preference‐inconsistent information. In a study that tested how minority, majority, and unanimous group members differ in their discussion of information, results lent no support for the alternative conception of information sampling. However, when the minority prevailed, minority members repeated significantly more common information than when the majority prevailed.     

The pond-and-duckweed problem; Three experiments on the misperception of exponential growth

The representation of duckweed multiplying itself in a pond is used as a research paradigm to study underestimation of exponential growth. The advantage of this paradigm is that the growth process is presented in a direct non-numerical way. The results show that the underestimation observed in earlier studies where growth was presented by means of tables or graphs, occurs in the pond-and-duckweed situation as well. By manipulating the way the process is presented it is possible to obtain some insight into the sampling strategies used by the subjects when they subjectively extrapolate the perceived processes. These experiments lead to the conclusion that subjects base their extrapolations on three or four samples only.     

The good,the bad and the ugly thing to do when sharing information: Revealing,concealing and lying depend on social motivation,distribution and importance of information

Research on information sharing in group decision-making has widely assumed a cooperative context and focused on the exchange of shared or unshared information in the hidden profile paradigm (36 and 37), neglecting the role of information importance. We argue that information sharing is a mixed-motive conflict setting that gives rise to motivated strategic behavior. We introduce a research paradigm that combines aspects of the traditional information sampling paradigm with aspects of a public good dilemma: the information pooling game. In three experiments, we show that information sharing is strategic behavior that depends on people’s pro-social or pro-self motivation, and that people consider information sharedness and information importance when deciding whether to reveal, withhold, or falsify their private or public information. Pro-social individuals were consistently found to honestly reveal their private and important information, while selfish individuals strategically concealed or even lied about their private and important information.     

A sampling approach to biases in conditional probability judgments: beyond base rate neglect and statistical format

Conditional probability judgments of rare events are often inflated. Early accounts assumed a general deficit in using statistical base rates. More recent approaches predict improvement when problems are presented in frequency format or refer to natural categories. The present theory focuses on sampling processes. Experiment 1 showed that a seeming advantage of frequency over probability formats is due to a confounded factor, the need to mentally transform stimulus samples. An information search paradigm was used in Experiment 2. When sampling by the predictor, the probability to be estimated, p(criterion/predictor), was conserved in the samples and judgments were quite accurate. However, when sampling by the criterion, the low base-rate event was strongly overrepresented, accounting for the entire bias. Judgments were quite sensitive to the sampled data, but failed to take sampling constraints into account, as shown in Experiments 3 and 4.     

Adaptive sampling for active learning with genetic programming

Active learning is a machine learning paradigm allowing to decide which inputs to use for training. It is introduced to Genetic Programming (GP) essentially thanks to the dynamic data sampling, used to address some known issues such as the computational cost, the over-fitting problem and the imbalanced databases. The traditional dynamic sampling for GP gives to the algorithm a new sample periodically, often each generation, without considering the state of the evolution. In so doing, individuals do not have enough time to extract the hidden knowledge. An alternative approach is to use some information about the learning state to adapt the periodicity of the training data change. In this work, we propose an adaptive sampling strategy for classification tasks based on the state of solved fitness cases throughout learning. It is a flexible approach that could be applied with any dynamic sampling. We implemented some sampling algorithms extended with dynamic and adaptive controlling re-sampling frequency. We experimented them to solve the KDD intrusion detection and the Adult incomes prediction problems with GP. The experimental study demonstrates how the sampling frequency control preserves the power of dynamic sampling with possible improvements in learning time and quality. We also demonstrate that adaptive sampling can be an alternative to multi-level sampling. This work opens many new relevant extension paths.     

Hoping for more: The influence of outcome desirability on information seeking and predictions about relative quantities

People must often engage in sequential sampling in order to make predictions about the relative quantities of two options. We investigated how directional motives influence sampling selections and resulting predictions in such cases. We used a paradigm in which participants had limited time to sample items and make predictions about which side of the screen contained more of a critical item. Sampling selections were biased by monetary desirability manipulations, and participants exhibited a desirability bias for both dichotomous and continuous predictions.