The impact of uniform color on judging tackles in association football

ObjectivesThe aim of the study was to question whether uniform color had any impact on judging tackles in football.DesignFifty-two videos showing the tackles of an achromatic and a chromatic team were individually presented in random order. The chromatic team's uniform color was changed to blue, green, red and yellow.MethodsFootball referees and participants with a high and minor level of understanding of the rules of football judged the roughness of each tackle.ResultsBy analyzing all four colors, results did not reveal any impact of uniform color. Restricting analysis to blue and red showed that referees and participants with a high level of understanding of the rules judged tackles from behind more harshly for players wearing red.ConclusionsThe study found some empirical support for associating red with aggression and emphasized a differential impact of blue versus red uniforms for tackles committed from behind.     

Decision-specific reinvestment scale: An exploration of its construct validity,and association with stress and coping appraisals

ObjectiveThis research project aimed to explore the construct validity of the Decision-Specific Reinvestment Scale (DSRS); more specifically, its links with stress and coping appraisals.DesignStudy 1 validated the DSRS and the Movement-Specific Reinvestment Scale (MSRS) to the French language, in order to examine the construct validity of the DSRS using the MSRS, the Preference for Intuition and Deliberation (PID) inventory and the Melbourne Decision-Making Questionnaire (MDMQ). In addition, sex differences in reinvestment were investigated. Study 2 examined stress and coping appraisals of high and low reinvesters.MethodIn study 1, 379 athletes completed the DSRS, MSRS, PID, and MDMQ. In study 2, 100 handball players, classified as low and high reinvesters, completed surveys aimed to assess stressor intensity, stressor perceived controllability, coping effectiveness, subjective performance and coping strategies with the Coping Inventory for Competitive Sport over three games.ResultsIn study 1, we found that intuitive athletes scored lower on the DSRS in comparison to deliberative athletes, whilst no difference was found for the MSRS. Convergent and discriminant validity was illustrated with the subscales of the MDMQ. No sex differences were found regarding reinvestment. In study 2, findings showed that low reinvesters scored higher than high reinvesters in terms of stressor perceived controllability, coping effectiveness and subjective performance.DiscussionIn addition to confirmation of construct validity, these findings strengthen our understanding of how high decision reinvesters perceive a pressured situation. Key applications are derived from our findings informing coaches and athletes in offsetting the negative effects of reinvestment on sport performance.     

SAwSu: An Integrated Model of Associative and Reinforcement Learning

Successfully explaining and replicating the complexity and generality of human and animal learning will require the integration of a variety of learning mechanisms. Here, we introduce a computational model which integrates associative learning (AL) and reinforcement learning (RL). We contrast the integrated model with standalone AL and RL models in three simulation studies. First, a synthetic grid‐navigation task is employed to highlight performance advantages for the integrated model in an environment where the reward structure is both diverse and dynamic. The second and third simulations contrast the performances of the three models in behavioral experiments, demonstrating advantages for the integrated model in accounting for behavioral data.     

Moral cognition,affect, and psychopathy

Few theorists would challenge the idea that affect and emotion directly influence decision-making and moral judgment. There is good reason to think that they also significantly assist in decision-making and judgment, and in fact are necessary for fully effective moral cognition. However, they are not sufficient. Deliberation and more reflective thought processes likewise play a crucial role, and in fact are inseparable from affective processes. I will argue that while the dual-process account of moral judgment set forth by Craigie (2011) has great merit, it fails to appreciate fully the extent to which affective and reflective processes are not only integrated, but also mutually interdependent. Evidence from psychopathy indicates that when reflective processes are not assisted adequately by what I will call ‘affective framing’, and moral cognition is of the “cooler,” less emotionally-informed variety, what results is not effective cognitive functioning, but rather psychopathology. My proposed account of affective framing aims to make sense of the way in which affect plays a strictly necessary and integral role not just in intuitive moral responses, but also in reflective moral judgments, so that moral cognition is accomplished by the joint operation of affective processes and reflective reasoning processes.     

Driving speed choice: The role of conscious monitoring and control (reinvestment) when driving

This study aimed to examine the role of reinvestment - the propensity to consciously monitor and control actions (movement specific reinvestment) and to consciously monitor and evaluate decision making processes (Decision specific reinvestment) while driving in everyday risky scenarios. The study also aimed to evaluate the association between reinvestment and previously validated driver attitude measures. Fifty one participants completed a series of questionnaires (Driving Self-Efficacy Scale, Driver Attitude Questionnaire, Movement Specific Reinvestment Scale, Decision Specific Reinvestment Scale) after which they completed a test phase in a driving simulator. In the test phase, driving scenarios included roads with different markings (i.e., double yellow, wide centrelines, wire rope barriers, Audio Tactile Profiled markings) and alerting scenarios (i.e., police car present, high crash risk area sign, reduced speed zone). Results revealed that on risky roads (wide centrelines), participants with a high propensity for decision specific reinvestment drove slower than those with a low propensity. Driver experience, attitudes towards speeding and scores on the Decision Reinvestment subscale of the Decision Specific Reinvestment Scale significantly predicted speed choice. More experienced participants with higher scores on the Decision Reinvestment subscale were more likely to drive slower and participants with worse attitudes towards speeding were likely to drive faster. Participants with a low propensity for movement specific reinvestment (specifically, Movement Self-Consciousness) reduced their speed to a greater extent than those with a high propensity when driving in the police car scenario. There was some evidence to suggest that high decision specific and movement specific reinvesters were more likely to be involved in crashes and receive driving infringements. The current study is the first to demonstrate a significant relationship between reinvestment and driving. The implications of these findings for road safety are discussed.     

Particle swarm optimised analysis of investment decision

A portfolio forecasting model based on particle swarm optimization (PSO) algorithm with automatic factor scaling is proposed in this Article to effectively improve the accuracy of related analysis model in portfolio application. Firstly, the portfolio problem is analyzed and a hybrid constraint portfolio model is obtained by improving portfolio model with consideration of general portfolio model and combination of market value constraint and upper bound constraint according to Markowitz's theory. Secondly, PSO algorithm is introduced during analysis on portfolio model and solution is found with the hybrid constraint portfolio model of PSO on portfolio. In addition, in order to further improve the performance of PSO in model solution, automatic factor scaling is used for adaptive learning on parameters associated with PSO, to improve convergence of the algorithm. At last, simulation experiments show that the algorithm proposed can obtain a more ideal investment portfolio scheme, thereby reducing investment risks and obtaining greater investment returns.     

Evaluating performance over time: Is improving better than being consistently good?

In many decision contexts, people evaluate others based on intertemporal performance records and commonly face a choice between two distinct profiles: performance that is consistently high versus performance that improves over time to that high level. We proposed that these two profiles could be appealing for different reasons, and thus evaluators’ preferences will differ across decision contexts. In three studies, participants were presented with candidates (e.g., students, employees) displaying the two profiles, and evaluated each candidate in terms of performance, future expectations, and deservingness. The consistent candidate was rated higher on performance, but lower on future expectations, than the improved candidate. Consequently, in achievement-based decisions (e.g., selecting a student for a scholarship), the consistent candidate was viewed as most deserving, whereas in potential-based decisions (e.g., selecting an employee for promotion), the improved candidate was preferred. These effects were mediated by the relative weight that evaluators placed on performance and future expectations.