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PloS One 2021The emergence of a new tech elite in Silicon Valley and beyond raises questions about the economic reach, political influence, and social importance of this group. How...
The emergence of a new tech elite in Silicon Valley and beyond raises questions about the economic reach, political influence, and social importance of this group. How do these inordinately influential people think about the world and about our common future? In this paper, we test a) whether members of the tech elite share a common, meritocratic view of the world, b) whether they have a "mission" for the future, and c) how they view democracy as a political system. Our data set consists of information about the 100 richest people in the tech world, according to Forbes, and rests on their published pronouncements on Twitter, as well as on their statements on the websites of their philanthropic endeavors. Automated "bag-of-words" text and sentiment analyses reveal that the tech elite has a more meritocratic view of the world than the general US Twitter-using population. The tech elite also frequently promise to "make the world a better place," but they do not differ from other extremely wealthy people in this respect. However, their relationship to democracy is contradictory. Based on these results, we conclude that the tech elite may be thought of as a "class for itself" in Marx's sense-a social group that shares particular views of the world, which in this case means meritocratic, missionary, and inconsistent democratic ideology.
Topics: Democracy; Economic Development; Logistic Models; Machine Learning; Social Media; Technology
PubMed: 33471828
DOI: 10.1371/journal.pone.0244071 -
NEAWalk: Inferring missing social interactions via topological-temporal embeddings of social groups.Knowledge and Information Systems 2022Real-world network data consisting of social interactions can be incomplete due to deliberately erased or unsuccessful data collection, which cause the misleading of...
Real-world network data consisting of social interactions can be incomplete due to deliberately erased or unsuccessful data collection, which cause the misleading of social interaction analysis for many various time-aware applications. Naturally, the link prediction task has drawn much research interest to predict the missing edges in the incomplete social network. However, existing studies of link prediction cannot effectively capture the entangling topological and temporal dynamics already residing in the social network, thus cannot effectively reasoning the missing interactions in dynamic networks. In this paper, we propose the NEAWalk, a novel model to infer the missing social interaction based on topological-temporal features of patterns in the social group. NEAWalk samples the query-relevant walks containing both the historical and evolving information by focusing on the temporal constraint and designs a dual-view anonymization procedure for extracting both topological and temporal features from the collected walks to conduct the inference. Two-track experiments on several well-known network datasets demonstrate that the NEAWalk stably achieves superior performance against several state-of-the-art baseline methods.
PubMed: 36035894
DOI: 10.1007/s10115-022-01724-2 -
Journal of Exposure Science &... Jan 2023Precipitated by an unusual winter storm, the 2021 Texas Power Crisis lasted February 10 to 27 leaving millions of customers without power. Such large-scale outages can...
BACKGROUND
Precipitated by an unusual winter storm, the 2021 Texas Power Crisis lasted February 10 to 27 leaving millions of customers without power. Such large-scale outages can have severe health consequences, especially among vulnerable subpopulations such as those reliant on electricity to power medical equipment, but limited studies have evaluated sociodemographic disparities associated with outages.
OBJECTIVE
To characterize the 2021 Texas Power Crisis in relation to distribution, duration, preparedness, and issues of environmental justice.
METHODS
We used hourly Texas-wide county-level power outage data to estimate geographic clustering and association between outage exposure (distribution and duration) and six measures of racial, social, political, and/or medical vulnerability: Black and Hispanic populations, the Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI), Medicare electricity-dependent durable medical equipment (DME) usage, nursing homes, and hospitals. To examine individual-level experience and preparedness, we used a preexisting and non-representative internet survey.
RESULTS
At the peak of the Texas Power Crisis, nearly 1/3 of customers statewide (N = 4,011,776 households/businesses) lost power. We identified multiple counties that faced a dual burden of racial/social/medical vulnerability and power outage exposure, after accounting for multiple comparisons. County-level spatial analyses indicated that counties where more Hispanic residents resided tended to endure more severe outages (OR = 1.16, 95% CI: 1.02, 1.40). We did not observe socioeconomic or medical disparities. With individual-level survey data among 1038 respondents, we found that Black respondents were more likely to report outages lasting 24+ hours and that younger individuals and those with lower educational attainment were less likely to be prepared for outages.
SIGNIFICANCE
Power outages can be deadly, and medically vulnerable, socioeconomically vulnerable, and marginalized groups may be disproportionately impacted or less prepared. Climate and energy policy must equitably address power outages, future grid improvements, and disaster preparedness and management.
Topics: Aged; Humans; United States; Texas; Medicare; Disasters; Electricity; Social Group
PubMed: 35963946
DOI: 10.1038/s41370-022-00462-5 -
Scientific Reports Mar 2022Social isolation might be considered as a marker of poor health and higher mortality. The aim of our analysis was to assess the association of social network index (SNI)...
Social isolation might be considered as a marker of poor health and higher mortality. The aim of our analysis was to assess the association of social network index (SNI) with incident AF and death. We selected participants aged ≥ 55 years without prevalent AF from the Framingham Heart Study. We evaluated the association between social isolation measured by the Berkman-Syme Social Network Index (SNI), incident AF, and mortality without diagnosed AF. We assessed the risk factor-adjusted associations between SNI (the sum of 4 components: marriage status, close friends/relatives, religious service attendance, social group participation), incident AF, and mortality without AF by using Fine-Gray competing risk regression models. We secondarily examined the outcome of all-cause mortality. We included 3454 participants (mean age 67 ± 10 years, 58% female). During 11.8 ± 5.2 mean years of follow-up, there were 686 incident AF cases and 965 mortality without AF events. Individuals with fewer connections had lower rates of incident AF (P = 0.04) but higher rates of mortality without AF (P = 0.03). Among SNI components, only social group participation was associated with higher incident AF (subdistribution hazards ratio [sHR] 1.35, 95% CI 1.16-1.57, P = 0.0001). For mortality without AF, social group participation (sHR = 0.81, 95% CI 0.71-0.93, P = 0.002) and regular religious service attendance sHR = 0.76, 95% CI 0.67-0.87, P < 0.0001) were associated with lower risk of death. Social isolation was associated with a higher rate of mortality without diagnosed AF. In contrast to our hypothesis, we observed that poor social connectedness was associated with a lower rate of incident AF. This finding should be interpreted cautiously since there were very few participants in the lowest social connectedness group. Additionally, the seemingly protective effect of social isolation on AF incidence may be simply an artifact of the strong association between social isolation and increased mortality rate in combination with the large number of deaths as compared to AF events in our study. Further study is warranted.
Topics: Aged; Atrial Fibrillation; Female; Humans; Incidence; Longitudinal Studies; Male; Middle Aged; Proportional Hazards Models; Risk Factors; Social Networking
PubMed: 35273243
DOI: 10.1038/s41598-022-07850-9 -
Facts, Views & Vision in ObGyn Jun 2016Originated as a mainly social group of befriended colleagues, the VVOG has evolved over the past 55 years to become a truly professional society facing successfully such...
Originated as a mainly social group of befriended colleagues, the VVOG has evolved over the past 55 years to become a truly professional society facing successfully such diverse challenges as organizing scientific congresses, postgraduate training, ethical debates, hands-on training courses, social events, interactions with national and international sister societies but also with the industry, insurers, the government, politicians and patient organisations.
PubMed: 27909563
DOI: No ID Found -
Alcoholism Treatment Quarterly 2020Research has shown that aspects of group dynamics of AA meetings are associated with AA attendance, alcohol use, and engagement in prescribed AA behaviors. This study...
Research has shown that aspects of group dynamics of AA meetings are associated with AA attendance, alcohol use, and engagement in prescribed AA behaviors. This study investigated whether perceptions of AA meeting group dynamics changed over 12-months and whether these dynamics predicted the probability that a new member would get a sponsor. Results showed that perceptions of the group dynamics of AA meetings did not change over the 12-month assessment period. Member perception of group cohesion was the only AA meeting group dynamic that predicted a new member getting a sponsor. Findings suggest that group cohesion plays an important role in AA members recovery efforts.
PubMed: 32742071
DOI: 10.1080/07347324.2019.1613942 -
Clinical Gerontologist 2022: To investigate the psychometric properties of the 10-item Social Engagement and Activities Questionnaire (SEAQ) to assess social-group, interpersonal interaction, and...
: To investigate the psychometric properties of the 10-item Social Engagement and Activities Questionnaire (SEAQ) to assess social-group, interpersonal interaction, and solitary activities among low-income, depressed homebound older adults (n = 269).: We used principal component analysis (PCA) to evaluate the underlying dimensions of the 10-item full SEAQ and a 6-item abbreviated item set. We assessed evidence of validity for the SEAQ by examining relationships between the SEAQ and older adults' clinical characteristics: perceived social support, disability, and depressive symptoms.: PCA results showed two components: (1) a general social-group activities engagement component; and (2) a low level of socialization (i.e., strong negative coefficients on the recreational activities and self-enrichment/educational activities and a negative coefficient for interpersonal interaction activities). The general social-group activities engagement component in both the full and abbreviated SEAQ were significantly positively correlated with the full and abbreviated SEAQ and perceived social support, providing evidence for convergent validity, and they were significantly negatively correlated with disability and depressive symptoms, providing evidence for discriminant validity.: The present study provides evidence of validity for the use of the SEAQ to assess social engagement and activities among low-income, depressed homebound older adults.: The SEAQ may be used in future studies measuring changes in social engagement and activities in these older adults.
Topics: Aged; Homebound Persons; Humans; Poverty; Social Participation; Social Support; Surveys and Questionnaires
PubMed: 32292129
DOI: 10.1080/07317115.2020.1753275 -
Evolutionary Human Sciences 2023Dispersal does not only mean moving from one environment to another, but can also refer to shifting from one social group to another. Individual characteristics such as...
Dispersal does not only mean moving from one environment to another, but can also refer to shifting from one social group to another. Individual characteristics such as sex, age and family structure might influence an individual's propensity to disperse. In this study, we use a unique dataset of an evacuated World War II Finnish population, to test how sex, age, number of siblings and birth order influence an individual's dispersal away from their own social group at a time when society was rapidly changing. We found that young women dispersed more than young men, but the difference decreased with age. This suggests that young men might benefit more from staying near a familiar social group, whereas young women could benefit more from moving elsewhere to find work or spouses. We also found that having more younger brothers increased the propensity for firstborns to disperse more than for laterborns, indicating that younger brothers might pressure firstborn individuals into leaving. However, sisters did not have the same effect as brothers. Overall, the results show that individual characteristics are important in understanding dispersal behaviour, but environmental properties such as social structure and the period of flux after World War II might upend the standard predictions concerning residence and dispersal. Individual characteristics influence dispersal away from social group after a forced migration in a Finnish population.
PubMed: 37587948
DOI: 10.1017/ehs.2023.16 -
Animals : An Open Access Journal From... Feb 2021Natural social systems within animal groups are an essential aspect of agricultural optimization and livestock management strategy. Assessing elements of animal... (Review)
Review
Natural social systems within animal groups are an essential aspect of agricultural optimization and livestock management strategy. Assessing elements of animal behaviour under domesticated conditions in comparison to natural behaviours found in wild settings has the potential to address issues of animal welfare effectively, such as focusing on reproduction and production success. This review discusses and evaluates to what extent social network analysis (SNA) can be incorporated with sensor-based data collection methods, and what impact the results may have concerning welfare assessment and future farm management processes. The effectiveness and critical features of automated sensor-based technologies deployed in farms include tools for measuring animal social group interactions and the monitoring and recording of farm animal behaviour using SNA. Comparative analyses between the quality of sensor-collected data and traditional observational methods provide an enhanced understanding of the behavioural dynamics of farm animals. The effectiveness of sensor-based approaches in data collection for farm animal behaviour measurement offers unique opportunities for social network research. Sensor-enabled data in livestock SNA addresses the biological aspects of animal behaviour via remote real-time data collection, and the results both directly and indirectly influence welfare assessments, and farm management processes. Finally, we conclude with potential implications of SNA on modern animal farming for improvement of animal welfare.
PubMed: 33567488
DOI: 10.3390/ani11020434 -
American Journal of Primatology Jul 2023Improving captive conditions of pygmy slow lorises (Nekaris and Nijman have recently suggested that the pygmy slow loris should be called the pygmy loris and is...
Improving captive conditions of pygmy slow lorises (Nekaris and Nijman have recently suggested that the pygmy slow loris should be called the pygmy loris and is distinctive enough to warrant a new genus, Xanthonycticebu) (Nycticebus pygmeaus) poses many challenges because detailed aspects of their lives in the wild are incomplete. This hinders efforts to replicate sustainable environments for them. To improve their well-being in captivity, eight rescued female pygmy slow lorises at the Japan Monkey Center (JMC) were socially housed in two types of groups following their solitary housing: two pairs and one group of four individuals. They spent much of their time in affiliative behaviors, as well as sharing sleeping sites after placement in a social group. The purpose of my study was to examine whether social housing helped in reducing stress by comparing fecal glucocorticoids and stereotypic behaviors when housed alone and when with conspecifics. Overall, the levels of fecal glucocorticoids were significantly lower when socially housed than when kept alone. One individual exhibited stereotypic behavior when housed alone, but this behavior disappeared after social housing. These findings support recent evidence that pygmy slow lorises are social animals and will benefit from group housing in captivity. We conclude that social housing of pygmy slow lorises improves their well-being by reducing stress levels, and that their group housing in captivity can provide dividends for the conservation of this endangered nocturnal primate because lorises intended for release should find it easier to adapt to natural conditions.
Topics: Animals; Female; Lorisidae; Glucocorticoids; Stereotyped Behavior; Primates; Feces
PubMed: 37128737
DOI: 10.1002/ajp.23495