价值观的稳定性与可变性

价值观是人们区分好坏、善恶、美丑、损益、是非的信念系统,通常是充满情感的。价值观具有稳定性与可变性的特点。价值观的稳定性表现为:基本价值观具有跨时间的稳定性和跨情境的一致性; 特别是保护性价值观和人生价值观具有较强的稳定性。个人的发展、经历重大事件以及实验干预可导致价值观的改变,可变性主要表现为价值观的重要性发生变化。从我国的实际出发,探讨个人的核心价值观问题、以及价值观研究中国化、价值观研究对价值观教育的启示,乃是我们今后研究的关注点。     

Preference for Human (vs. Robotic) Labor is Stronger in Symbolic Consumption Contexts

Advances in robotics, automation, and artificial intelligence increasingly enable firms to replace human labor with technology, thereby fundamentally transforming how goods and services are produced. From both managerial and societal points of view, it is therefore important to understand demand‐side incentives for firms to employ human labor. We begin to address this question by examining for which products and services consumers are more likely to favor human (vs. robotic) labor. In six studies, we demonstrate that consumers prefer human (vs. robotic) labor more for products with higher (vs. lower) symbolic value (e.g., when expressing something about one's beliefs and personality is of greater importance). We theorize that this is because consumers have stronger uniqueness motives in more (vs. less) symbolic consumption contexts (and associate human labor more strongly with product uniqueness). In line with this account, we demonstrate that individual differences in need for uniqueness moderate the interaction between production mode and symbolic motives and that a measure of uniqueness motives mediates the effect of consumption context on preferences for human (vs. robotic) production.     

Evaluating pedestrian interaction preferences with a game theoretic autonomous vehicle in virtual reality

Localisation and navigation of autonomous vehicles (AVs) in static environments are now solved problems, but how to control their interactions with other road users in mixed traffic environments, especially with pedestrians, remains an open question. Recent work has begun to apply game theory to model and control AV-pedestrian interactions as they compete for space on the road whilst trying to avoid collisions. But this game theory model has been developed only in unrealistic lab environments. To improve their realism, this study empirically examines pedestrian behaviour during road crossing in the presence of approaching autonomous vehicles in more realistic virtual reality (VR) environments. The autonomous vehicles are controlled using game theory, and this study seeks to find the best parameters for these controls to produce comfortable interactions for the pedestrians. In a first experiment, participants’ trajectories reveal a more cautious crossing behaviour in VR than in previous laboratory experiments. In two further experiments, a gradient descent approach is used to investigate participants’ preference for AV driving style. The results show that the majority of participants were not expecting the AV to stop in some scenarios, and there was no change in their crossing behaviour in two environments and with different car models suggestive of car and last-mile style vehicles. These results provide some initial estimates for game theoretic parameters needed by future AVs in their pedestrian interactions and more generally show how such parameters can be inferred from virtual reality experiments.     

Using Lexicographic Parametric Programming for Searching a Non-dominated Set in Multiple-Objective Linear Programming

In this paper we propose an approach which makes it possible to search non-dominated and only non-dominated solutions in multiple-objective linear programming. The approach is based on the use of a reference direction and lexicographic parametric programming. The requisite theory is developed in the paper. The use of the approach is illustrated with a numerical example.     

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.     

Personal values and unsanctioned aggression inherent in contact sports: The role of self-regulatory mechanisms,aggressiveness, and demographic variables

IntroductionTo date, research-examining factors related to the sociocognitive self-regulatory mechanisms governing unsanctioned aggression have received scant attention in applied sport psychology.ObjectiveA mediating model as influenced by various demographic variables was applied to explore the relationships between athletes’ personal values and their unsanctioned aggression directly and indirectly through the mediating role of resistive self-regulatory efficacy, moral disengagement, and aggressiveness.MethodA sample of 301 French competitors of different age (young: n = 200 and adult: n = 101), gender (male: n = 172 and female: n = 129), type of sport (high: n = 131 and low contact: n = 170), level of competition (beginner: n = 115, intermediate: n = 110, and advanced: n = 76), and length of practice (brief: n = 109, intermediate: n = 49, and extensive: n = 143) completed a questionnaire assessing the aforementioned variables.ResultsStructural equation modelling demonstrates that self-transcendence and self-enhancement values have only indirect negative and positive effects, respectively, on unsanctioned aggression through the full mediating effect of the mediators. Also, age, gender, and type of sport were predictive only of some personal values and mediators.ConclusionThese findings offer evidence that resistive self-regulatory efficacy, moral disengagement, and aggressiveness are mediators that fully govern the impact of athletes’ personal values and certain demographic variables on their unsanctioned aggression. Several limitations, implications and suggestions for further research are discussed.     

Human factors evaluation of an in-vehicle active traffic and demand management (ATDM) system

This research study focused on the evaluation of an emulated in-vehicle Active Traffic and Demand Management (ATDM) system on Interstate 66 in Northern Virginia. Traditional ATDM systems rely on infrastructure-mounted variable message signs (VMS) to provide information (speed limits, lane availability, etc.) to the traveling public. By providing information about dynamic roadway conditions on an in-vehicle device, the ATDM may improve driving safety and performance by allowing drivers to remain consistently aware of forthcoming traffic conditions and roadway requirements; even when external signage is inaccessible. This study represents an initial investigation of an emulated in-vehicle ATDM to provide developers with design guidance and ensure that unintended consequences, such as distraction, do not undermine the potential benefits.Twenty younger and 20 older participants, accompanied by a member of the research team, experienced the following ATDM features on an in-vehicle device (IVD) mounted to the dashboard: (1) dynamic speed limits, (2) dynamic lane use/shoulder control, (3) High Occupancy Vehicle (HOV) restrictions, and (4) roadway information from variable message signs. The IVD was equipped with auditory and visual alerts notifying the driver when relevant visual information was updated. Research questions addressed distraction and driver behavior associated with use of the system. Qualitative and quantitative participant data was acquired from the instrumented vehicle, various questionnaires, and researcher observation.Several key findings were uncovered: (1) The IVD, as tested, did not warrant classification as a source of distraction according to the NHTSA guidelines; v2) There was a significant difference in eye-glance durations to the IVD when comparing the VMS alerts to both the speed limit and lane management alerts; and (3) The speed limit alert motivated participants to alter their speed (per survey results and participant speed data).     

价值观的稳定性与可变性：基于认知神经科学的视角

价值观的稳定性和可变性一直是该领域争论的焦点所在。近些年来, 研究者开始从认知神经科学的角度来探讨导致价值观稳定性差异的机制问题。已有的神经反应证据表明, 当某种价值观是基于道义主义的绝对规则来进行认知建构的, 或与自我概念在表征上存在一致性时, 其更倾向于保持稳定的状态; 若非如此, 便可能会在外界影响(如他人劝说)下发生重要程度上的改变。未来需要进一步丰富和完善认识价值观稳定性与可变性关系的认知神经加工模型, 并探索价值观长效改变背后的认知神经机制, 以促进理论研究在价值观教育中的实践和应用。