In-Group Versus Out-Group Source Memory

2016 ◽  
Vol 63 (3) ◽  
pp. 150-158 ◽  
Author(s):  
Michael Greenstein ◽  
Nancy Franklin ◽  
Jessica Klug
Keyword(s):  
Source Memory ◽  
Source Monitoring ◽  
A Priori ◽  
Group Versus ◽  
Common Finding ◽  
Source Characteristics ◽  
Group Homogeneity ◽  
Group Members ◽  
Homogeneity Effect ◽  
Improved Performance

Abstract. A common finding in the source monitoring literature is that greater similarity impairs source discriminability. Experiments traditionally manipulate similarity overtly by describing or showing sources with explicitly differentiable features. However, people may also infer source characteristics themselves, which should also affect discriminability. Two studies examined inferred source characteristics by capitalizing on the out-group homogeneity effect, whereby in-group members are conceptualized as more diverse than out-group members. Participants learned about two sources who were described only as members of an in-group or an out-group and whose actions did not have higher a priori association with either group. Source memory was superior when participants believed the sources to be in-group members. This demonstrates that people spontaneously include inferred features with source representations and can capitalize on these features during source monitoring. Interestingly, information suggesting membership in one’s in-group improved performance even for sources who had previously been considered out-group members (Experiment 2).

Multidimensional source monitoring: Prior retrieval of one source attribute improves source memory for a second

2010 ◽  
Author(s):  
Michael R. Dewitt ◽  
Justin B. Knight ◽  
B. Hunter Ball ◽  
Jason L. Hicks
Keyword(s):  
Source Memory ◽  
Source Monitoring

A Two Phases Self-healing Framework for Service-oriented Systems

2021 ◽  
Vol 15 (2) ◽  
pp. 1-25
Author(s):  
Amal Alhosban ◽  
Zaki Malik ◽  
Khayyam Hashmi ◽  
Brahim Medjahed ◽  
Hassan Al-Ababneh
Keyword(s):  
Web Services ◽  
A Priori ◽  
Fault Management ◽  
Service Selection ◽  
Exception Handling ◽  
Self Healing ◽  
Service Oriented Architectures ◽  
Service Oriented ◽  
Improved Performance ◽  
High Level

Service-Oriented Architectures (SOA) enable the automatic creation of business applications from independently developed and deployed Web services. As Web services are inherently a priori unknown, how to deliver reliable Web services compositions is a significant and challenging problem. Services involved in an SOA often do not operate under a single processing environment and need to communicate using different protocols over a network. Under such conditions, designing a fault management system that is both efficient and extensible is a challenging task. In this article, we propose SFSS, a self-healing framework for SOA fault management. SFSS is predicting, identifying, and solving faults in SOAs. In SFSS, we identified a set of high-level exception handling strategies based on the QoS performances of different component services and the preferences articled by the service consumers. Multiple recovery plans are generated and evaluated according to the performance of the selected component services, and then we execute the best recovery plan. We assess the overall user dependence (i.e., the service is independent of other services) using the generated plan and the available invocation information of the component services. Due to the experiment results, the given technique enhances the service selection quality by choosing the services that have the highest score and betters the overall system performance. The experiment results indicate the applicability of SFSS and show improved performance in comparison to similar approaches.

Metacognitive inferences in source memory judgements: The role of perceived differences in item recognition

2007 ◽  
Vol 60 (7) ◽  
pp. 1015-1040 ◽  
Author(s):  
Thorsten Meiser ◽  
Christine Sattler ◽  
Ulrich Von Hecker
Keyword(s):  
Source Memory ◽  
Source Monitoring ◽  
Item Recognition ◽  
World Knowledge ◽  
Source Information ◽  
Monitoring Model ◽  
Metacognitive Beliefs ◽  
Presentation Time ◽  
Different Sources

This research investigated the hypothesis that metacognitive inferences in source memory judgements are based on the recognition or nonrecognition of an event together with perceived or expected differences in the recognizability of events from different sources. The hypothesis was tested with a multinomial source-monitoring model that allowed separation of source-guessing tendencies for recognized and unrecognized items. Experiments 1A and 1B manipulated the number of item presentations as relevant source information and revealed differential guessing tendencies for recognized and unrecognized items, with a bias to attribute unrecognized items to the source associated with poor item recognition. Experiments 2A and 2B replicated the findings with a manipulation of presentation time and extended the analysis to subjective differences in item recognition. Experiments 3A and 3B used more natural source information by varying type of acoustic signal and demonstrated that subjective theories about differences in item recognition are sufficient to elicit differential source-guessing biases for recognized and unrecognized items. Together the findings provide new insights into the cognitive processes underlying source memory decisions, which involve episodic memory and reconstructive tendencies based on metacognitive beliefs and general world knowledge.

Perceptions of Similarity and Agreement in Partisan Groups

2011 ◽  
Author(s):  
Eric A. Whitaker ◽  
John M. Fulwider
Keyword(s):  
Voter Turnout ◽  
Social Identity Theory ◽  
Future Research ◽  
Perceptual Differences ◽  
Group Homogeneity ◽  
Homogeneity Effect ◽  
Political Behaviors ◽  
Democrats And Republicans ◽  
Political Groups ◽  
Group Similarity

This chapter examines whether there are perceptual differences in how partisan identifiers think about the in-group and out-group, and whether these judgments relate reliably to other attitudes and political behaviors. It first selectively reviews the psychological literature on social identity theory and group-based perceptual differences, focusing primarily on the out-group homogeneity effect. The subsequent analyses then consider and examine: how perceptions of in-group and out-group similarity and agreement vary among Democrats and Republicans, whether these judgments are systematically related to affective judgments about political groups and political figures, and whether these judgments relate to conventional political behaviors, such as voter turnout and vote choice. Finally, the chapter concludes with a set of recommendations for future research.

scholarly journals Nonverbal leadership emergence in walking groups

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Maria Lombardi ◽  
William H. Warren ◽  
Mario di Bernardo
Keyword(s):  
A Priori ◽  
Team Sports ◽  
Personal Factors ◽  
Multi Agent Systems ◽  
Leadership Emergence ◽  
Emergency Evacuations ◽  
Multi Agent ◽  
Group Members ◽  
Walking Group ◽  
Specific Scenario

Abstract The mechanisms underlying the emergence of leadership in multi-agent systems are under investigation in many areas of research where group coordination is involved. Nonverbal leadership has been mostly investigated in the case of animal groups, and only a few works address the problem in human ensembles, e.g. pedestrian walking, group dance. In this paper we study the emergence of leadership in the specific scenario of a small walking group. Our aim is to propose a rigorous mathematical methodology capable of unveiling the mechanisms of leadership emergence in a human group when leader or follower roles are not designated a priori. Two groups of participants were asked to walk together and turn or change speed at self-selected times. Data were analysed using time-dependent cross correlation to infer leader-follower interactions between each pair of group members. The results indicate that leadership emergence is due both to contextual factors, such as an individual’s position in the group, and to personal factors, such as an individual’s characteristic locomotor behaviour. Our approach can easily be extended to larger groups and other scenarios such as team sports and emergency evacuations.

Source attributions for detected new items: Persistent evidence for schematic guessing

2020 ◽  
Vol 73 (9) ◽  
pp. 1407-1422 ◽  
Author(s):  
Raoul Bell ◽  
Laura Mieth ◽  
Axel Buchner
Keyword(s):  
Source Memory ◽  
Source Monitoring ◽  
Matching Theory ◽  
World Knowledge ◽  
Probability Matching ◽  
Learning History ◽  
Specific Item ◽  
Apply Probability

Performance in source-monitoring tests is not only determined by source memory but also by source guessing. Source guessing is not random as it is informed by two distinct mechanisms. (1) People may show a schema-based guessing bias and rely on cross-situationally stable world knowledge. (2) They may apply probability matching and rely on the specific item-source contingency experienced at encoding. According to probability matching theory, source guessing is based on probability matching when a specific contingency representation is available. This conclusion is derived from a source-monitoring paradigm in which no source judgements for detected new items are required. Here, we extend this paradigm to examine source guessing not only for detected old items but also for detected new items. The results suggest that participants take the old–new recognition status of the items into account when making source attributions. Probability matching is used only for detected old items: Source guessing sensitively reflects the item-source contingency for these items. For detected new items, participants resort to schema-based guessing. Using schema-based guessing rather than probability matching when judging detected new items may have the advantage that a newly acquired contingency representation that may only be locally valid is not generalised too readily at the expense of a schematic expectation that reflects a larger and more comprehensive learning history.

scholarly journals Political Ideology, Trust, and Cooperation

2016 ◽  
Vol 62 (4) ◽  
pp. 797-818 ◽  
Author(s):  
Daniel Balliet ◽  
Joshua M. Tybur ◽  
Junhui Wu ◽  
Christian Antonellis ◽  
Paul A. M. Van Lange
Keyword(s):  
Political Party ◽  
Presidential Election ◽  
Political Ideology ◽  
Meta Analysis ◽  
Group Versus ◽  
Party Affiliation ◽  
Two Samples ◽  
Group Members ◽  
Us Presidential Election ◽  
Political Party Affiliation

Theories suggest that political ideology relates to cooperation, with conservatives being more likely to pursue selfish outcomes, and liberals more likely to pursue egalitarian outcomes. In study 1, we examine how political ideology and political party affiliation (Republican vs. Democrat) predict cooperation with a partner who self-identifies as Republican or Democrat in two samples before ( n = 362) and after ( n = 366) the 2012 US presidential election. Liberals show slightly more concern for their partners’ outcomes compared to conservatives (study 1), and in study 2 this relation is supported by a meta-analysis ( r = .15). However, in study 1, political ideology did not relate to cooperation in general. Both Republicans and Democrats extend more cooperation to their in-group relative to the out-group, and this is explained by expectations of cooperation from in-group versus out-group members. We discuss the relation between political ideology and cooperation within and between groups.

scholarly journals Optimization of Sensors to be Used in a Voltammetric Electronic Tongue Based on Clustering Metrics

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4798
Author(s):  
Munmi Sarma ◽  
Noelia Romero ◽  
Xavier Cetó ◽  
Manel del Valle
Keyword(s):  
A Priori ◽  
Electronic Tongue ◽  
Principal Component ◽  
Canonical Variate ◽  
Ann Model ◽  
Inclusion Removal ◽  
Discrimination Ability ◽  
Improved Performance ◽  
Voltammetric Electronic Tongue ◽  
The Impact

Herein we investigate the usage of principal component analysis (PCA) and canonical variate analysis (CVA), in combination with the F factor clustering metric, for the a priori tailored selection of the optimal sensor array for a given electronic tongue (ET) application. The former allows us to visually compare the performance of the different sensors, while the latter allows us to numerically assess the impact that the inclusion/removal of the different sensors has on the discrimination ability of the ET. The proposed methodology is based on the measurement of a pure stock solution of each of the compounds under study, and the posterior analysis by PCA/CVA with stepwise iterative removal of the sensors that demote the clustering when retained as part of the array. To illustrate and assess the potential of such an approach, the quantification of paracetamol, ascorbic acid, and uric acid mixtures were chosen as the study case. Initially, an array of eight different electrodes was considered, from which an optimal array of four sensors was derived to build the quantitative ANN model. Finally, the performance of the optimized ET was benchmarked against the results previously reported for the analysis of the same mixtures, showing improved performance.

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