Politeness and Etiquette Modeling

2011 ◽  
pp. 387-411 ◽  
Author(s):  
Christopher A. Miller ◽  
Tammy Ott ◽  
Peggy Wu ◽  
Vanessa Vakili
Keyword(s):  
Computational Models ◽  
Decision Aids ◽  
Central Element ◽  
Universal Theory ◽  
Subjective Perceptions ◽  
Patterns Of Behavior ◽  
Perception Model ◽  
Effective Decision ◽  
Coarse Model ◽  
And Behavior

If culture is expressed in the patterns of behavior, values and expectations of a group, then a central element in the practical modeling and understanding of culture is the expression of politeness and its roles in governing and influencing behavior. The authors have been developing computational models of “politeness” and its role in power and familiarity relationships, urgency, indebtedness, etc. Such a model, insofar as it extends to human-machine interactions, will enable better and more effective decision aids. This model, based on a universal theory of human politeness, links aspects of social context (power and familiarity relationships, imposition, character), which have culture-specific values, to produce expectations about the use of polite, redressive behaviors (also culturally defined). The authors have linked this “politeness perception” model to a coarse model of decision making and behavior in order to predict influences of politeness on behavior and attitudes. This chapter describes the algorithm along with results from multiple validation experiments: two addressing the model’s ability to predict perceived politeness and two predicting the impact of perceived politeness on compliance behaviors in response to directives. The authors conclude that their model tracks well with subjective perceptions of American cultural politeness and that its predictions broadly anticipate and explain situations in which perceived politeness in a directive yields improved affect, trust, perceived competence, subjective workload, and compliance, though somewhat decreased reaction time. The model proves better at accounting for the effects of social distance than for power differences.

INNOVATIVE SOCIETY: A SOCIAL CREDIT SYSTEM IN CHINA

2020 ◽  
pp. 50-59
Author(s):  
Weichzhen` Gao
Keyword(s):  
Latin American ◽  
Social Life ◽  
Credit System ◽  
Educational Mission ◽  
Social Transformations ◽  
Social Credit ◽  
Road Project ◽  
Patterns Of Behavior ◽  
The One ◽  
And Behavior

The basic principles of SCS implementation are as follows: Formation of sustainable social structure and its operational management; Monitoring and correction of social transformations and behavior of the general population: transparency as a major factor in the life of an innovative society; Stimulating competition as a motivation for success. Due to the transparency of social life, different patterns of behavior in different conditions are published in the information space of the society. Accordingly, actionable life scenarios are made available to the general public, which is fulfilling an educational mission regarding adaptation mechanisms in an innovative society; the SCS system is a significant component of the national strategy of integration and consolidation of the Chinese innovation society; carrying out softpolicy foreign policy: The positive experience of the Chinese innovation society in implementing SCS is a prerequisite for expanding its area of application in Asian, African and Latin American countries, especially the countries participating in the One Belt One Road project. SCS covers all spheres of social life of the modern Chinese citizen, forms a sustainable form of accountability to the society for the content and flow of their daily activities, aspirations and preferences.

scholarly journals Effectiveness of the Interventions Utilized in Genetic Counseling

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Jeeyae Choi ◽  
Hyeoneui Kim
Keyword(s):  
Genetic Counseling ◽  
Genetic Testing ◽  
Information Technologies ◽  
Decision Aids ◽  
Healthcare Providers ◽  
Experimental Studies ◽  
Well Being ◽  
Diagnostic Tools ◽  
Effective Decision ◽  
Single Intervention

Background. Advances in genetic science and biotechnology accumulated huge knowledge of genes and various genetic tests and diagnostic tools for healthcare providers including nurses. Genetic counseling became important to assist patients making decisions about obtaining genetic testing or preventive measures. Method. This review was conducted to describe the counseling topics, various interventions adopted in genetic counseling, and their effectiveness. Experimental studies (N=39) published between 1999 and 2012 were synthesized. Results. The most frequently covered topic was benefits and limitations of genetic testing on breast cancer ovarian and colorectal cancers. Most of researchers focused on evaluating cognitive aspect and psychological well-being. Conclusion. No single intervention was consistently reported to be effective. Decision aids enhanced with information technologies have potential to improve the outcomes of genetic counseling by providing tailored information and facilitating active engagement of patients in information uptake. Clinical Implication. When nurses are familiar with topics and interventions of genetic counseling, they are well positioned to provide genetic/genomic information to the patient and families.

scholarly journals IMPLEMENTASI PENDIDIKAN BERBASIS ADAB DALAM PENGEMBANGAN KARAKTER

2020 ◽  
Vol 12 (1) ◽  
pp. 63-72
Author(s):  
Khubni Maghfirotun ◽  
Eka Nur Mahzumah
Keyword(s):  
Design Research ◽  
Human Life ◽  
Boarding School ◽  
Human Beings ◽  
Research Subjects ◽  
Patterns Of Behavior ◽  
Religious Concept ◽  
And Behavior ◽  
Attitudes And Behavior

The morality / character of the nation's students has collapsed. This is marked by the rise of bullying, child anarchism, mass contests, free sex and so on. Seeing the importance of the role of etiquette in human life, the education world should think more seriously about the concept of planting etiquette in its students, so that the introduction and cultivation of etiquette must begin at an early age. Rasulullah SAW has taught that the example is the main factor of success in educating children. Exemplary is also the best method in children's education, especially in the early childhood period. On this basis the research formulated the formulation of the problem namely (1) How is the concept of Adab in SDI Ar-Roudloh Miru? (2) How is the Implementation of Adab Based Education in SDI Ar-Roudloh Miru-Sekaran-Lamongan? This study uses qualitative research and case studies as its research design. Research subjects in this study were students at SDI Ar-Roudloh. Data collection techniques used were observation, semistructural interviews and documentation. Data were analyzed using the Miles and Huberman model, namely data reduction, data presentation, and drawing conclusions. The data checking technique uses triangulation techniques. The results of this study include: (1) the formation of students' character at SDI Ar Roudloh is with the Applicative Religious concept. This is evidenced by the existence of Boarding School since students go up to fourth grade. This is expected to be more intensive in applying civilized values ​​that are prioritized by the institution. The etiquette values ​​emphasized and prioritized at SDI Ar Roudloh in this case are divided into three aspects namely; Judging from the pattern of attitudes and behavior to God, patterns of behavior to fellow human beings, patterns of behavior to nature. (2) in implementing civilized education for the formation of students' character by applying the religious concept with the details of the sub-chapters above, there are several stages in order to obtain maximum results, before implementing and informing the values ​​of civilized education to students. In this case the researcher classifies into three stages; first; Socialization, second; Implementation and third; Evaluation.  

Effective Decision Aids in Marketing

1977 ◽  
Vol 11 (1) ◽  
pp. 62-71 ◽  
Author(s):  
J.R.C. Wensley
Keyword(s):  
Decision Aids ◽  
Effective Decision

LATERAL ELEMENT CROSS CONNECTIONS OF THE SYNAPTONEMAL COMPLEX AND THEIR RELATIONSHIP TO CHIASMATA IN RAT SPERMATOCYTES

1978 ◽  
Vol 20 (4) ◽  
pp. 567-579 ◽  
Author(s):  
Peter B. Moens
Keyword(s):  
Developmental Stage ◽  
Synaptonemal Complex ◽  
Meiotic Prophase ◽  
Central Element ◽  
Crossing Over ◽  
Lateral Element ◽  
Early Pachytene ◽  
Nonrandom Distribution ◽  
And Behavior ◽  
Cross Connection

Observations are presented in support of the hypothesis that at meiotic prophase a reciprocal crossover is accompanied by a crossover of the lateral elements of the synaptonemal complex, SC (Moens, 1974). Rat spermatocyte nuclei in developmental stage VII (Clermont, 1972) of the seminiferous epithelium cycle, but not pachytene nuclei in stages I to VI, were found to have SC modifications in the form of a cross connection between the lateral elements. In structure these crossover elements, CO elements, resemble the lateral element. It is found in a variety of positions, usually more or less perpendicular to the SC but also slanted or parallel along the central element or detached from the SC. Reconstructions of entire nuclei indicate an average of one such CO element per SC and a nonrandom distribution of CO elements among the SCs. Because the crossing-over of lateral elements produces a 180° twist or removes a 180° twist, the pattern of SC coiling was examined. Coiling starts in early pachytene prior to CO element formation. At stage VII one nucleus had a total of 78 coils, all counter clockwise, and another nucleus had 97 such 180° coils. It is noted that if SC coils are associated with the process of crossing-over, then the regulation of crossover distribution such as chiasma position interference has an explanation in the structure and behavior of the SC.

scholarly journals Deficits in Prediction Ability Trigger Asymmetries in Behavior and Internal Representation

2020 ◽  
Vol 11 ◽  
Author(s):  
Anja Philippsen ◽  
Yukie Nagai
Keyword(s):  
Developmental Disorders ◽  
Computational Models ◽  
Predictive Coding ◽  
Sensory Information ◽  
Internal Representation ◽  
Human Perception ◽  
Underlying Mechanism ◽  
Autism Spectrum ◽  
Prediction Ability ◽  
And Behavior

Predictive coding is an emerging theoretical framework for explaining human perception and behavior. The proposed underlying mechanism is that signals encoding sensory information are integrated with signals representing the brain's prior prediction. Imbalance or aberrant precision of the two signals has been suggested as a potential cause for developmental disorders. Computational models may help to understand how such aberrant tendencies in prediction affect development and behavior. In this study, we used a computational approach to test the hypothesis that parametric modifications of prediction ability generate a spectrum of network representations that might reflect the spectrum from typical development to potential disorders. Specifically, we trained recurrent neural networks to draw simple figure trajectories, and found that altering reliance on sensory and prior signals during learning affected the networks' performance and the emergent internal representation. Specifically, both overly strong or weak reliance on predictions impaired network representations, but drawing performance did not always reflect this impairment. Thus, aberrant predictive coding causes asymmetries in behavioral output and internal representations. We discuss the findings in the context of autism spectrum disorder, where we hypothesize that too weak or too strong a reliance on predictions may be the cause of the large diversity of symptoms associated with this disorder.

scholarly journals Feature-reweighted RSA: A method for improving the fit between computational models, brains, and behavior

2021 ◽  
Author(s):  
Philipp Kaniuth ◽  
Martin N. Hebart
Keyword(s):  
Model Selection ◽  
Computational Models ◽  
Model Comparison ◽  
Brain Activity ◽  
Activity Patterns ◽  
Behavioral Data ◽  
Novel Approach ◽  
Improve Model ◽  
And Behavior ◽  
Model Features

AbstractRepresentational Similarity Analysis (RSA) has emerged as a popular method for relating representational spaces from human brain activity, behavioral data, and computational models. RSA is based on the comparison of representational dissimilarity matrices (RDM), which characterize the pairwise dissimilarities of all conditions across all features (e.g. fMRI voxels or units of a model). However, classical RSA treats each feature as equally important. This ‘equal weights’ assumption contrasts with the flexibility of multivariate decoding, which reweights individual features for predicting a target variable. As a consequence, classical RSA may lead researchers to underestimate the correspondence between a model and a brain region and, for model comparison, it may lead to selecting the inferior model. While previous work has suggested that reweighting can improve model selection in RSA, it has remained unclear to what extent these results generalize across datasets and data modalities. To fill this gap, the aim of this work is twofold: First, utilizing a range of publicly available datasets and three popular deep neural networks (DNNs), we seek to broadly test feature-reweighted RSA (FR-RSA) applied to computational models and reveal the extent to which reweighting model features improves RDM correspondence and affects model selection. Second, we propose voxel-reweighted RSA, a novel use case of FR-RSA that reweights fMRI voxels, mirroring the rationale of multivariate decoding of optimally combining voxel activity patterns. We find that reweighting individual model units (1) markedly improves the fit between model RDMs and target RDMs derived from several fMRI and behavioral datasets and (2) affects model selection, highlighting the importance of considering FR-RSA. For voxel-reweighted RSA, improvements in RDM correspondence were even more pronounced, demonstrating the utility of this novel approach. We additionally demonstrate that classical noise ceilings can be exceeded when FR-RSA is applied and propose an updated approach for their computation. Taken together, our results broadly validate the use of FR-RSA for improving the fit between computational models, brain and behavioral data, possibly allowing us to better adjudicate between competing computational models. Further, our results suggest that FR-RSA applied to brain measurement channels could become an important new method to assess the match between representational spaces.

scholarly journals Bioentity2vec: Attribute- and behavior-driven representation for predicting multi-type relationships between bioentities

GigaScience ◽  
2020 ◽  
Vol 9 (6) ◽  
Author(s):  
Zhen-Hao Guo ◽  
Zhu-Hong You ◽  
Yan-Bin Wang ◽  
De-Shuang Huang ◽  
Hai-Cheng Yi ◽  
...  
Keyword(s):  
Computational Models ◽  
Molecular Level ◽  
Area Under The Curve ◽  
Biological Information ◽  
Precision Recall Curve ◽  
Classification Tasks ◽  
Systematic Understanding ◽  
Biological Entities ◽  
And Behavior ◽  
Recall Curve

Abstract Background The explosive growth of genomic, chemical, and pathological data provides new opportunities and challenges for humans to thoroughly understand life activities in cells. However, there exist few computational models that aggregate various bioentities to comprehensively reveal the physical and functional landscape of biological systems. Results We constructed a molecular association network, which contains 18 edges (relationships) between 8 nodes (bioentities). Based on this, we propose Bioentity2vec, a new method for representing bioentities, which integrates information about the attributes and behaviors of a bioentity. Applying the random forest classifier, we achieved promising performance on 18 relationships, with an area under the curve of 0.9608 and an area under the precision-recall curve of 0.9572. Conclusions Our study shows that constructing a network with rich topological and biological information is important for systematic understanding of the biological landscape at the molecular level. Our results show that Bioentity2vec can effectively represent biological entities and provides easily distinguishable information about classification tasks. Our method is also able to simultaneously predict relationships between single types and multiple types, which will accelerate progress in biological experimental research and industrial product development.

scholarly journals The Integration of Marketing Problem-Solving Modes and Marketing Management Support Systems

1997 ◽  
Vol 61 (3) ◽  
pp. 21-37 ◽  
Author(s):  
Berend Wierenga ◽  
Gerrit H. van Bruggen
Keyword(s):  
Problem Solving ◽  
Support Systems ◽  
Decision Aids ◽  
Decision Makers ◽  
Marketing Management ◽  
Management Support ◽  
Cognitive Approach ◽  
Management Support Systems ◽  
Effective Decision

To be effective, decision aids for marketing managers should match with the thinking and reasoning processes of the marketing decision makers who use them. The authors take a cognitive approach to problem solving in marketing. They develop a classification of “marketing problem-solving modes” and distinguish four modes: optimizing, reasoning, analogizing, and creating. They also present a typology of what they call “marketing management support systems.” In an integrating framework, they then link the four marketing problem-solving modes with the most appropriate marketing management support systems. The authors conclude with a discussion of the implications of this “demand-side” approach to marketing management support systems.

Searching for the Environment in Environmental Cognition Research

1992 ◽  
Author(s):  
Craig Zimring ◽  
Mark Gross
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Value Judgments ◽  
Environmental Cognition ◽  
Cognitive Mediators ◽  
Environment And Behavior ◽  
Spatial Decision Making ◽  
Alternative Approaches ◽  
Natural Settings ◽  
And Behavior

Research in environmental cognition has been fragmented into at least three related but separate areas that reflect different purposes, viewpoints, and disciplinary conventions (Evans and Gärling, this volume). One tradition has focused on predicting spatial choices such as choosing shops or modes of transportation (Timmermans, this volume). A second tradition, driven in part by the necessity to make value judgments about settings to be spared or modified in development, has focused on the assessment of environments, and particularly on the visual quality of natural settings (R. Kaplan, this volume). Finally, a third tradition, coming principally from psychology and geography, has focused on exploring the content and structure of mental representations of the environment (Golledge, this volume). In this chapter we discuss these three approaches to environmental cognition and examine how they can contribute to each other and to a more general view of action, evaluation, and cognition. We focus specifically on the linkages between the physical environment, cognitive mediators, and outcomes such as wayfinding, decision making, and other actions. We pay particular attention to how the environment and mediators are represented. This chapter is organized into several sections. After the introduction, we review the chapters in this volume by Timmermans, R. Kaplan, and Golledge. Unlike much previous work in evaluation and in spatial decision making, all three authors discuss the cognitive processes that mediate between environment and behavior. The following section considers alternative approaches to cognitive mediators such as mental models and schemas. Following this, we briefly examine how the physical setting has been represented in environmental cognition. We then turn to computational models that attempt to provide rigorous definitions of both environment and mediator. Next, we propose our own preliminary schema-based model of wayfinding. Finally, we suggest some questions for further research. In artificial intelligence research a distinction is made between two alternative approaches to theory: “scruffy” and “neat” (Luger & Stubblefield, 1989). Whereas researchers following both traditions are interested in simulating human cognitive behavior, the scruffies primarily focus on producing a computational system where the outcomes mimic human behavior.

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