组织社会化视角下员工组织公民行为动态变化趋势及其形成机制

日益复杂多变的市场竞争环境对组织的灵活性和适应性都提出了更高的要求, 员工的组织公民行为在这一背景下显得尤为重要, 因它能有效提高组织在不确定环境下的生存能力和核心竞争力、提升组织的绩效水平。虽然已有大量研究关注员工的组织公民行为, 但研究者多采用相对静态的研究范式, 而忽视了组织公民行为的长期动态变化趋势。基于组织社会化视角, 本研究重点关注新员工和工作变更员工组织公民行为的长期动态变化趋势、探索影响组织公民行为动态变化趋势的内在机制和边界条件, 以期为培养和激发员工持续性高水平的组织公民行为提供可参考的理论依据。     

情感计算技术如何推动犯罪风险评估工具的发展？

摘 要 随着近年来人工智能深度学习技术的发展,情感计算与人格计算技术日渐成熟,在许多实际应用场景中取得了良好的表现,当前人工智能情感计算技术应用于犯罪风险评估领域,能够有效解决目前主流的风险评估工具难以解决的个体内差异性的预测因子评估问题以及被测评参与者因社会赞许性而导致结果失真的问题。本文在详细阐述目前主流评估工具的局限性基础上,详细阐述了以情感计算技术为支撑的动态风险评估工具的设计思路、目前已有的技术方案以及设计细节的理论依据,在此基础上最后提出以人工智能技术为支撑的新型评估工具的未来发展方向。     

Citizen Advocacy Observed: Tool or Tokenism?

Citizen advocacy, where a volunteer works in partnership with a vulnerable person, compliments self- and legal advocacy. In the context of mental health services, citizen advocacy is a tool for enabling and empowering people who use these services, and is founded on the recognition that mental health service users are frequently socially oppressed and disadvantaged. This article describes the development of a Citizen Advocacy service for people with mental health difficulties, and also the problems they brought to this service. The problems encountered in sustaining the service are noted and lessons are drawn for the future.     

青少年早期同伴侵害的亚类别及其稳定性:个体定向的分析

以山东省济南市12所初中的2015名初一学生为被试,对其持续追踪至初二年级,采用自我报告法测查青少年的同伴侵害、受欺负和社交退缩,采用同伴提名法测查青少年的攻击行为。采用潜在剖面分析和潜在转变分析,探讨青少年早期同伴侵害的亚类别以及各亚类别中青少年受侵害身份的稳定性与发展变化。结果发现：（1）同伴侵害亚类别可以分为：未受侵害组、低受侵害组、中等受侵害组和高受侵害组四类,各亚类别间的异质性主要体现在受侵害程度上;（2）中等受侵害组和高受侵害组表现出高水平的攻击行为和社交退缩,且高受侵害组的社交退缩行为更多;（3）青少年早期个体的受侵害身份具有中到高水平的稳定性,同时也存在着一定的发展变化,主要表现为高受侵害组青少年倾向于向中等受侵害组转变,中等受侵害组青少年倾向于向低受侵害组转变。攻击行为是受侵害身份转变的重要预测因素。     

Road user interactions in a shared space setting: Priority and communication in a UK car park

Appropriate communication between road users can lead to safe and efficient interactions in mixed traffic. Understanding how road users communicate can support the development of effective communication methods for automated vehicles. We carried out observations of 66 pedestrian-driver and 124 driver-driver interactions in a shared space setting. Specific actions and reactions of the road users involved were recorded using a novel observation protocol. Overall, results showed that pedestrians’ failure to look towards a driver created the greatest uncertainty in the interaction, with the driver slowing down, but not completely stopping, in response to pedestrians. Looking towards the driver also influenced which road user took priority in driver-driver interactions. Groups of pedestrians were more likely to be given priority than an individual pedestrian, and the use of vehicle-based signals were also associated with taking priority during an interaction. Our observations show the importance of non-verbal communication during road user interactions, highlighting it as an essential area of research in the development of automated vehicles, to allow their safe, cooperative, interactions with other road users. Observations were made on a limited number of interactions to inform challenges facing future automated vehicles. Further work should therefore be done to corroborate and extend our findings, to examine interactions between human road users and automated vehicles in shared space settings.     

Idiographic network analysis of discrete mood states prior to treatment

Idiographic network models based on time‐series data have received recent attention for their ability to model relationships among symptoms and behaviours as they unfold in time within a single individual (cf. Epskamp, Borsboom, & Fried, 2018; Fisher, Medaglia, & Jeronimus, 2018). Rather than examine the correlational relationships between variables in a sample of individuals, an idiographic network examines correlations within a single person, averaged over many time points. Because the approach averages over time, the data must be stationary (i.e. relatively consistent over time). If individuals experience varying states over time—different mixtures of symptoms and behaviours in one moment or another—then averaging over categorically different moments may undermine model accuracy. Fisher and Bosley (2019) address these concerns via the application of Gaussian finite mixture modelling to identify latent classes of time points in intraindividual time‐series data from a sample of adults with major depressive disorder and/or generalised anxiety disorder (n = 45). The present paper outlines an extension of this work, wherein network analysis is used to model within‐class covariation of symptoms. To illustrate this approach, network models were constructed for each intraindividual class identified by Fisher and Bosley (137 networks across the 45 participants, mean classes/person = ~3, range = 2–4 classes/person). We examine the relative consistency in symptom organisation between each individual's multiple mood state networks and assess emergent group‐level patterns. We highlight opportunities for enhanced treatment personalisation and review nomothetic patterns relevant to transdiagnostic conceptualisations of psychopathology. We address opportunities for integrating this approach into clinical practice and outline potential shortcomings.     

中学教师工作狂类型与工作绩效的关系研究：基于潜在剖面分析

以229名中学教师对研究对象,采用潜在剖面分析方法探索其工作狂类型,并进一步揭示这些类型与工作绩效间的关系。结果表明:（1）教师按工作狂得分可分为三类：重度工作狂、中等偏高工作狂和中等偏低工作狂;（2）不同类别工作狂会对工作绩效产生不同程度的影响。     

Quantitative chromatographic profiling of odours associated with dominance in male laboratory mice

Triads of male NMRI mice were housed together and dominance hierarchies allowed to form. At age 19 weeks the mice were ranked on the basis of wins in spontaneous aggressive encounters, and whole-body volatiles were sampled by the dynamic solvent effect and quantitatively analysed by capillary gas chromatography. At age 26 weeks the mice were again ranked on the basis of wins in aggressive encounters, number of aggressive encounters initiated, and scent marking patterns, and whole-body volatiles were sampled and analysed. Chromatographic odour profile ranks agreed perfectly with aggressive initiator ranks and poorly with encounter winner ranks. Eight components of the whole-body odour were identified by gas chromatography-mass spectrometry; two of these are known semiochemicals. The results demonstrate that murine semiochemicals are accessible to quantitative analysis at the level of the individual.     

What are symbols symbols of? Situated action,mythological bootstrapping and the emergence of the Self

This paper addresses the question of how symbols should be understood in analytical psychology and psychoanalysis. The point of view examined focuses on the recent turn to more cognitive and developmental models in both disciplines and briefly reviews and critiques the evolutionary and cognitive arguments. The paper then presents an argument based on dynamic systems theory in which no pre-existing template or structure for either mind or behaviour is assumed. Within the dynamic systems model the Self is viewed as an emergent phenomenon deriving from the dynamic patterns existing in a complex system that includes the physiological characteristics of the infant, the intentional attributions of the caregiver and the cultural or symbolic resources that constitute the environment. The symbol can then be seen as a discrete, and in important ways an autonomous, element in the dynamic system. Conclusions are drawn for further research into the nature of the symbol with implications for both theory and practice in analytical psychology and psychoanalysis.     

Interactions between Knowledge,Action and Commitment within Agent Dynamic Logic

This paper considers a new class of agent dynamic logics which provide a formal means of specifying and reasoning about the agents activities and informational, motivational and practical aspects of the behaviour of the agents. We present a Hilbert-style deductive system for a basic agent dynamic logic and consider a number of extensions of this logic with axiom schemata formalising interactions between knowledge and commitment (expressing an agent s awareness of her commitments), and interactions between knowledge and actions (expressing no learning and persistence of knowledge after actions). The deductive systems are proved sound and complete with respect to a Kripke-style semantics. Each of the considered logics is shown to have the small model property and therefore decidable.Presented by Ewa Orlowska