Little Between-Region and Between-Country Variance When People Form Impressions of Others

First Impressions ◽

Data Set ◽

Adult Participants ◽

Target Characteristics ◽

To what extent are perceivers’ first impressions of other individuals dictated by cultural background rather than personal idiosyncrasies? To address this question, we analyzed a globally diverse data set containing 11,481 adult participants’ ratings of 120 targets across 45 countries (2,597,624 total ratings). Across ratings of 13 traits, we found that perceivers’ idiosyncratic differences accounted for approximately 29% of variance and impressions on their own and approximately 16% in conjunction with target characteristics. However, country- and region-level differences, here a proxy for culture, accounted for 3.2% on average (i.e., both alone and in conjunction with target characteristics). We replicated this pattern of effects in a preregistered analysis on an entirely novel data set containing 7,007 participants’ ratings of 100 targets across 41 countries (24,886 total ratings). Together, these results suggest that perceivers’ impressions of other people are largely dictated by their individual characteristics and local environment rather than their cultural background.

Little between-region and between-country variance when forming impressions of others

10.31234/osf.io/ynhwz ◽

2021 ◽

Author(s):

Neil Hester ◽

Sally Y Xie ◽

Eric Hehman

Keyword(s):

Local Environment ◽

Cultural Background ◽

First Impressions ◽

Adult Participants ◽

Target Characteristics

To what extent are perceivers’ first impressions of others dictated by cultural background versus personal idiosyncrasies? To address this question, we analyzed a globally diverse dataset containing 11,481 adult participants’ ratings of 120 targets across 45 countries (2,597,624 total ratings). Across ratings of 13 traits, we find that perceivers’ idiosyncratic differences accounted for ~29% of variance and impressions on their own and ~16% in conjunction with target characteristics. However, country- and region-level differences, here a proxy for culture, accounted for on average 3.2% (i.e., both alone and in conjunction with target characteristics). We replicated this pattern of effects in a pre-registered analysis on an entirely novel dataset containing 7,007 participants’ ratings of 100 targets across 41 countries (24,886 total ratings). Together, this work suggests that perceivers’ impressions of others are largely dictated by their individual characteristics and local environment, rather than their cultural background.

Determinants of prepaid systems of healthcare financing: a worldwide country-level perspective

International Journal of Health Economics and Management ◽

10.1007/s10754-021-09301-w ◽

2021 ◽

Author(s):

Andrea M. Leiter ◽

Engelbert Theurl

Keyword(s):

Health Care ◽

Panel Data ◽

Health Care Financing ◽

Value Added ◽

The Elderly ◽

Dynamic Panel Data ◽

Minor Importance ◽

Data Set ◽

Country Level

AbstractIn this paper we examine determinants of prepaid modes of health care financing in a worldwide cross-country perspective. We use three different indicators to capture the role of prepaid modes in health care financing: (i) the share of total prepaid financing as percent of total current health expenditures, (ii) the share of voluntary prepaid financing as percent of total prepaid financing, and (iii) the share of compulsory health insurance as percent of total compulsory prepaid financing. In the econometric analysis, we refer to a panel data set comprising 154 countries and covering the time period 2000–2015. We apply a static as well as a dynamic panel data model. We find that the current structure of prepaid financing is significantly determined by its different forms in the past. The significant influence of GDP per capita, governmental revenues, the agricultural value added, development assistance for health, degree of urbanization and regulatory quality varies depending on the financing structure we look at. The share of the elderly and the education level are only of minor importance for explaining the variation in a country’s share of prepaid health care financing. The importance of the mentioned variables as determinants for prepaid health care financing also varies depending on the countries’ socio-economic development. From our analysis we conclude that more detailed information on indicators which reflect the distribution of individual characteristics (such as income, family size and structure and health risks) within a country’s population would be needed to gain deeper insight into the decisive determinants for prepaid health care financing.

Towards a framework for measuring creative economy: evidence from Balkan countries

Measuring Business Excellence ◽

10.1108/mbe-03-2018-0013 ◽

2019 ◽

Vol 23 (1) ◽

pp. 41-62 ◽

Cited By ~ 1

Author(s):

Valentina Ndou ◽

Giovanni Schiuma ◽

Giuseppina Passiante

Keyword(s):

Business Environment ◽

Creative Economy ◽

Data Set ◽

Content Type ◽

Balkan Countries ◽

World Economic ◽

And Performance ◽

Diverse Data ◽

The Relationship ◽

Performance Dimension

PurposeThe creative process through which the territorial resources, knowledge and culture are used, exploited and configured to match needs and to achieve congruence with the changing business environment has become a crucial process for competitiveness. This is even more relevant for economies of developing countries which are continuously struggling to reap the benefits of globalisation, as well as to grasp the new opportunities for competitiveness. As such, this paper aims to try to concentrate on the dynamic perspectives of the creative economy of countries by distinguishing between the potentialities and performance. The paper tackles the influence that creativity capacities might have on performance of countries.Design/methodology/approachThe methodology consists in identifying creative economy indicators from a diverse data set of the World Economic Forum and distinguish them between potential and performance indicators.FindingsData reveal as good progress and emphasis is being devoted to increasing the level of creativity; however, the Balkan countries still holdup in their capacity to boost innovation.Practical implicationsThe paper provide a new focus of research on creativity measurement that is significant for understanding what creative capacities territories possess and the ability to make proficient use for growth and innovation.Originality/valueThis paper proposes a new operational framework for measuring and interpreting the creative economy indicators by identifying not only indicators that gauge the potentialities of a country, but also indicators that are linked with the performance dimension, as well as the relationship amongst them.

Social connectedness and political behavior

Research & Politics ◽

10.1177/2053168017719173 ◽

2017 ◽

Vol 4 (3) ◽

pp. 205316801771917 ◽

Cited By ~ 1

Author(s):

Jack Lyons Reilly

Keyword(s):

Social Networks ◽

Political Behavior ◽

Political Ideology ◽

Social Connectedness ◽

Local Environment ◽

Social Environments ◽

Data Set ◽

Individual Level ◽

Nationally Representative ◽

Socially Isolated

One of the focal points of social networks research has been the process by which individuals utilize information and cues from their social networks and communities to form political attitudes and make decisions about how and when to participate in politics. Not all individuals, however, have large social networks or are strongly connected to their local social environments. Furthermore, despite concerns about rising social isolation in American society, the role that relatively socially disconnected individuals play in politics is not well understood. Using a nationally representative data set with information about communities, social networks, and individual-level variables, this paper examines social connectedness and political behavior. Those who are more socially isolated, it is found, are neither more conservative nor liberal on any particular political issues, but clearly participate in politics less than individuals who are well connected to those around them. Finally, while individual political ideology is not correlated with isolation, the contextual influence of the local environment on individual preferences is correlated with social connectedness. When compared with well connected citizens, individuals who are more isolated are less likely to have their vote choices influenced by those around them. Individual social connectedness conditions the effect of contextual social influence.

Autonomous feature type selection based on environment using expectation maximization in self-localization

International Journal of Advanced Robotic Systems ◽

10.1177/1729881418814701 ◽

2018 ◽

Vol 15 (6) ◽

pp. 172988141881470

Author(s):

Nezih Ergin Özkucur ◽

H Levent Akın

Keyword(s):

Expectation Maximization ◽

Autonomous Robots ◽

Expectation Maximization Algorithm ◽

Sensory Information ◽

Ground Truth ◽

Local Environment ◽

Localization Algorithm ◽

Data Set ◽

Public Data ◽

The Individual

Self-localization in autonomous robots is one of the fundamental issues in the development of intelligent robots, and processing of raw sensory information into useful features is an integral part of this problem. In a typical scenario, there are several choices for the feature extraction algorithm, and each has its weaknesses and strengths depending on the characteristics of the environment. In this work, we introduce a localization algorithm that is capable of capturing the quality of a feature type based on the local environment and makes soft selection of feature types throughout different regions. A batch expectation–maximization algorithm is developed for both discrete and Monte Carlo localization models, exploiting the probabilistic pose estimations of the robot without requiring ground truth poses and also considering different observation types as blackbox algorithms. We tested our method in simulations, data collected from an indoor environment with a custom robot platform and a public data set. The results are compared with the individual feature types as well as naive fusion strategy.

Estimating relatedness between malaria parasites

10.1101/575985 ◽

2019 ◽

Cited By ~ 5

Author(s):

Aimee R. Taylor ◽

Pierre E. Jacob ◽

Daniel E. Neafsey ◽

Caroline O. Buckee

Keyword(s):

Genetic Epidemiology ◽

Ad Hoc ◽

Pathogen Transmission ◽

Identity By Descent ◽

Malaria Parasites ◽

Data Set ◽

Epidemiology Studies ◽

Diverse Data ◽

Prospective Study Design ◽

Identity By State

1.AbstractUnderstanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. It remains unclear how to compare different studies, therefore, and which measures to use. Here, we systematically compare measures based on identity-by-state and identity-by-descent using a globally diverse data set of malaria parasites,Plasmodium falciparumandPlasmodium vivax, and provide marker requirements for estimates based on identity-by-descent. We formally show that the informativeness of polyallelic markers for relatedness inference is maximised when alleles are equifrequent. Estimates based on identity-by-state are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on identity-by-descent. To generate reliable estimates, we recommend approximately 200 biallelic or 100 polyallelic markers. Confidence intervals illuminate inference across studies based on different sets of markers. These marker requirements, unlike many thus far reported, are immediately applicable to haploid malaria parasites and other haploid eukaryotes. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology, and will provide a basis for statistically informed prospective study design and surveillance strategies.

The Relationship Between Gratitude and Religious Identification of NCAA Athletes: A Replication Study

Journal of Clinical Sport Psychology ◽

10.1123/jcsp.2020-0035 ◽

2021 ◽

pp. 1-17

Author(s):

Nicole T. Gabana ◽

Jeffrey B. Ruser ◽

Mariya A. Yukhymenko-Lescroart ◽

Jenelle N. Gilbert

Keyword(s):

National Collegiate Athletic Association ◽

Past Research ◽

Well Being ◽

Spiritual Identity ◽

General State ◽

Data Set ◽

Religious Identification ◽

Dispositional Trait ◽

And Performance ◽

A holistic, multicultural approach to student-athlete mental health, well-being, and performance promotes the consideration of spiritual and religious identities in counseling and consultation. Preliminary research supports the interconnectedness of spirituality, religiosity, and gratitude in athletes; thus, this study sought to replicate Gabana, D’Addario, Luzzeri, and Soendergaard's study (2020) and extend the literature by examining a larger, independently sampled, more diverse data set and multiple types of gratitude. National Collegiate Athletic Association Division I–III student-athletes (N = 596) were surveyed to better understand how religious and spiritual identity related to trait, general-state, and sport-state gratitude. Results supported past research; athletes who self-identified as being both spiritual and religious reported greater dispositional (trait) gratitude than those who self-identified as spiritual/nonreligious or nonspiritual/nonreligious. Between group differences were not found when comparing general-state and sport-state gratitude. Findings strengthen and extend the understanding of spirituality, religion, and gratitude in sport. Limitations, practical implications, and future directions are discussed.

Effect of Group Size and Individual Characteristics on Intergroup Encounters in Primates

International Journal of Primatology ◽

10.1007/s10764-019-00119-5 ◽

2020 ◽

Vol 41 (2) ◽

pp. 325-341 ◽

Cited By ~ 6

Author(s):

Bonaventura Majolo ◽

Aurora deBortoli Vizioli ◽

Laura Martínez-Íñigo ◽

Julia Lehmann

Keyword(s):

Group Size ◽

Dominance Rank ◽

Primate Species ◽

New World Monkeys ◽

Older Individuals ◽

Data Set ◽

Unequal Distribution ◽

Intergroup Encounters ◽

Group 2

AbstractIntergroup encounters are common in nonhuman primates and can vary from affiliative to aggressive. We extracted data from the literature to test five different hypotheses: 1) where there are group size differences between opposing groups, whether the larger group is more likely to win an intergroup encounter than the smaller group; 2) whether the likelihood of a group engaging in aggressive intergroup encounters increases with group size; and 3–5) whether dominant, older individuals, and/or males are more likely to participate aggressively in intergroup encounters than subordinate, younger individuals and/or females. Our data set comprised 52 studies on 31 primate species (3 lemur species, 5 New World monkeys, 19 Old World monkeys, and 4 apes). We found that the larger group is more likely to win an encounter against a smaller group than vice versa. We found no significant relationship between group size and propensity to be aggressive during intergroup encounters. We found weak/no support for the effect of age, dominance rank, and sex on the frequency of aggression displayed toward outgroup individuals during intergroup encounters. Species- and population-specific differences in inter- and intragroup competition and in the degree of the unequal distribution of resources across group members may explain why age, dominance rank, and sex are not strong predictors of aggression during intergroup encounters.

Video Data Mining

Encyclopedia of Data Warehousing and Mining ◽

10.4018/978-1-59140-557-3.ch223 ◽

2011 ◽

pp. 1185-1189 ◽

Cited By ~ 2

Author(s):

Jung Hwan Oh ◽

Jeong Kyu Lee ◽

Sae Hwang

Keyword(s):

Data Mining ◽

Research Area ◽

Multimedia Databases ◽

Video Data ◽

Multimedia Data ◽

Data Sets ◽

Data Set ◽

Useful Knowledge ◽

Active Research ◽

Data mining, which is defined as the process of extracting previously unknown knowledge and detecting interesting patterns from a massive set of data, has been an active research area. As a result, several commercial products and research prototypes are available nowadays. However, most of these studies have focused on corporate data — typically in an alpha-numeric database, and relatively less work has been pursued for the mining of multimedia data (Zaïane, Han, & Zhu, 2000). Digital multimedia differs from previous forms of combined media in that the bits representing texts, images, audios, and videos can be treated as data by computer programs (Simoff, Djeraba, & Zaïane, 2002). One facet of these diverse data in terms of underlying models and formats is that they are synchronized and integrated hence, can be treated as integrated data records. The collection of such integral data records constitutes a multimedia data set. The challenge of extracting meaningful patterns from such data sets has lead to research and development in the area of multimedia data mining. This is a challenging field due to the non-structured nature of multimedia data. Such ubiquitous data is required in many applications such as financial, medical, advertising and Command, Control, Communications and Intelligence (C3I) (Thuraisingham, Clifton, Maurer, & Ceruti, 2001). Multimedia databases are widespread and multimedia data sets are extremely large. There are tools for managing and searching within such collections, but the need for tools to extract hidden and useful knowledge embedded within multimedia data is becoming critical for many decision-making applications.

ACAT1 Benchmark of RANS-Informed Analytical Methods for Fan Broadband Noise Prediction—Part I—Influence of the RANS Simulation

Acoustics ◽

10.3390/acoustics2030029 ◽

2020 ◽

Vol 2 (3) ◽

pp. 539-578

Author(s):

Carolin Kissner ◽

Sébastien Guérin ◽

Pascal Seeler ◽

Mattias Billson ◽

Paruchuri Chaitanya ◽

...

Keyword(s):

Turbulence Model ◽

Analytical Methods ◽

Companion Paper ◽

Broadband Noise ◽

Operating Conditions ◽

Navier Stokes ◽

Data Set ◽

The Past ◽

Flow Turbulence ◽

A benchmark of Reynolds-Averaged Navier-Stokes (RANS)-informed analytical methods, which are attractive for predicting fan broadband noise, was conducted within the framework of the European project TurboNoiseBB. This paper discusses the first part of the benchmark, which investigates the influence of the RANS inputs. Its companion paper focuses on the influence of the applied acoustic models on predicted fan broadband noise levels. While similar benchmarking activities were conducted in the past, this benchmark is unique due to its large and diverse data set involving members from more than ten institutions. In this work, the authors analyze RANS solutions performed at approach conditions for the ACAT1 fan. The RANS solutions were obtained using different CFD codes, mesh resolutions, and computational settings. The flow, turbulence, and resulting fan broadband noise predictions are analyzed to pinpoint critical influencing parameters related to the RANS inputs. Experimental data are used for comparison. It is shown that when turbomachinery experts perform RANS simulations using the same geometry and the same operating conditions, the most crucial choices in terms of predicted fan broadband noise are the type of turbulence model and applied turbulence model extensions. Chosen mesh resolutions, CFD solvers, and other computational settings are less critical.