scholarly journals Triple Disadvantage: Neighborhood Networks of Everyday Urban Mobility and Violence in U.S. Cities

2020 ◽  
Vol 85 (6) ◽  
pp. 925-956
Author(s):  
Brian L. Levy ◽  
Nolan E. Phillips ◽  
Robert J. Sampson
Keyword(s):  
Fixed Effects ◽  
Racial Inequality ◽  
Well Being ◽  
Neighborhood Disadvantage ◽  
Spatial Proximity ◽  
Urban Mobility ◽  
Mobility Patterns ◽  
Residential Neighborhood ◽  
Twitter Users ◽  
Structural Mobility

This article develops and assesses the concept of triple neighborhood disadvantage. We argue that a neighborhood’s well-being depends not only on its own socioeconomic conditions but also on the conditions of neighborhoods its residents visit and are visited by, connections that form through networks of everyday urban mobility. We construct measures of mobility-based disadvantage using geocoded patterns of movement estimated from hundreds of millions of tweets sent by nearly 400,000 Twitter users over 18 months. Analyzing nearly 32,000 neighborhoods and 9,700 homicides in 37 of the largest U.S. cities, we show that neighborhood triple disadvantage independently predicts homicides, adjusting for traditional neighborhood correlates of violence, spatial proximity to disadvantage, prior homicides, and city fixed effects. Not only is triple disadvantage a stronger predictor than traditional measures, it accounts for a sizable portion of the association between residential neighborhood disadvantage and homicides. In turn, potential mechanisms such as neighborhood drug activity, interpersonal friction, and gun crime prevalence account for much of the association between triple disadvantage and homicides. These findings implicate structural mobility patterns as an important source of triple (dis)advantage for neighborhoods and have implications for a broad range of phenomena beyond crime, including community capacity, gentrification, transmission in a pandemic, and racial inequality.

scholarly journals Context in Continuity: The Enduring Legacy of Neighborhood Disadvantage Across Generations

2021 ◽  
Author(s):  
Steven Elias Alvarado ◽  
Alexandra Cooperstock
Keyword(s):  
Fixed Effects ◽  
Well Being ◽  
Neighborhood Disadvantage ◽  
Neighborhood Association ◽  
Individual Level ◽  
Fixed Effects Models ◽  
Children And Young Adults ◽  
Successive Generations ◽  
Adult Exposure ◽  
Neighborhood Level

Neighborhoods may contribute to the maintenance of inequality in well-being across generations. We use 35 years of restricted geo-coded NLSY 1979 and NLSY Children and Young Adults data to estimate the association between multigenerational exposure to childhood neighborhood disadvantage and subsequent adult exposure. Invoking cousin fixed effects models that adjust for unobserved legacies of disadvantage that cascade across generations, we find that families where both parents and their children are exposed to childhood neighborhood disadvantage are likely to pass on the legacy of neighborhood disadvantage to successive generations, net of observed and unobserved confounders. Second, we find a direct intergenerational neighborhood association, net of observed and unobserved confounders. Third, we find that unobserved confounders nested in previous generations explain away the intragenerational neighborhood association. These findings reorient neighborhood theory to more seriously attend to the interdependence of neighborhood level and individual level antecedents of inequality across generations.

Digital Mapping of Urban Mobility Patterns

2019 ◽  
pp. 470-487
Author(s):  
Douglas J. Wiebe ◽  
Christopher N. Morrison
Keyword(s):  
Communication Technology ◽  
Communication Technologies ◽  
Well Being ◽  
Future Research ◽  
Urban Mobility ◽  
Mobility Patterns ◽  
Positioning Systems ◽  
Digital Mapping ◽  
Global Positioning ◽  
Complex Relationships

Achieving accurate measurements of mobility and where people spend time is an essential step toward understanding how environments influence people’s impressions, actions, well-being, and health. But identifying where people are located in space and time and drawing from these data conclusions about what people actually experience is a challenge. Advances in communication technologies are creating possibilities for research today that even recently would not have been possible. This chapter reviews a classic study in the field of mobility pattern research, demonstrates the interest of mobility patterns to investigators of geography and health, and describes how geographic information systems and Global Positioning Systems are being used to better understand the complex relationships between people’s physical locations and health outcomes. The chapter concludes with predictions about how advances in communication technology will shape future research.

Rank Status and Happiness in India: A Panel Ordered Probit Estimation of the Effect of Ordinal Relative Comparison on Well-being

2020 ◽  
Vol 11 (01) ◽  
Author(s):  
T. Lakshmanasamy ◽  
K. Maya
Keyword(s):  
Life Satisfaction ◽  
Fixed Effects ◽  
Reference Group ◽  
Well Being ◽  
Ordered Probit ◽  
Probit Regression ◽  
Differential Effects ◽  
Comparison Income ◽  
Average Reference ◽  
The Rich

Most often the social comparison or relative income hypothesis has been used as an explanation for the lack of systematic relationship between income and happiness, using the ordered probit regression method. The identification of relevant reference group and the estimation of the differential effects of comparison income have been controversial. To overcome these twin issues, this paper uses an ordinal comparison income approach based on rich/poor dichotomy and rank income. The rank income of an individual is defined as his relative position in the income distribution within the reference group and the average income of the reference group is used to define the rich/poor classification. The differential effects of ordinal incomes across life satisfaction distribution is estimated by the panel fixed effects ordered profit regression model using the WVS data for India. The estimated results show that ordinal income comparison, rather than cardinal average reference income, is a better predictor of life satisfaction levels. Raising income level is relatively important for less satisfied people while increasing rank status is important for highly satisfied people in India.

scholarly journals Individual differences limit predicting well-being and productivity using software repositories: a longitudinal industrial study

2021 ◽  
Vol 26 (5) ◽  
Author(s):  
Miikka Kuutila ◽  
Mika Mäntylä ◽  
Maëlick Claes ◽  
Marko Elovainio ◽  
Bram Adams
Keyword(s):  
Individual Differences ◽  
Fixed Effects ◽  
Prediction Models ◽  
Well Being ◽  
Software Project ◽  
Structured Interviews ◽  
Software Developers ◽  
Software Repositories ◽  
Generalized Linear Mixed Effects ◽  
Individualized Prediction

AbstractReports of poor work well-being and fluctuating productivity in software engineering have been reported in both academic and popular sources. Understanding and predicting these issues through repository analysis might help manage software developers’ well-being. Our objective is to link data from software repositories, that is commit activity, communication, expressed sentiments, and job events, with measures of well-being obtained with a daily experience sampling questionnaire. To achieve our objective, we studied a single software project team for eight months in the software industry. Additionally, we performed semi-structured interviews to explain our results. The acquired quantitative data are analyzed with generalized linear mixed-effects models with autocorrelation structure. We find that individual variance accounts for most of the R2 values in models predicting developers’ experienced well-being and productivity. In other words, using software repository variables to predict developers’ well-being or productivity is challenging due to individual differences. Prediction models developed for each developer individually work better, with fixed effects R2 value of up to 0.24. The semi-structured interviews give insights into the well-being of software developers and the benefits of chat interaction. Our study suggests that individualized prediction models are needed for well-being and productivity prediction in software development.

Changes in Family Roles and Subjective Well-Being among Japanese Adults

2021 ◽  
pp. 0192513X2199413
Author(s):  
Yuko Hara
Keyword(s):  
Fixed Effects ◽  
Transition To Parenthood ◽  
Well Being ◽  
Family Roles ◽  
Subjective Well Being ◽  
Men And Women ◽  
Self Rated Health ◽  
Japanese Adults ◽  
Effect Theory ◽  
And Gender

Research in Western countries has demonstrated that marriage is associated with improved well-being, and parenthood with decreased well-being, for both men and women. However, less is known about whether the associations are universal for both genders across countries. Using nine waves of panel data and fixed effects models, this study examines the relationship between changes in family roles and subjective well-being of men and women in the highly gendered social context of Japan. Well-being was assessed across two domains: self-rated health and mental health. The results broadly support the protective effect theory, which posits that marriage itself has a positive effect on well-being; however, no association was observed between becoming a wife and self-rated health. Contrary to what previous research predicts, only men’s self-rated health negatively responds to transition to parenthood. These findings highlight the importance of country context and gender differences in the significance of family obligations.

From residence to movement: The nature of racial segregation in everyday urban mobility

Urban Studies ◽  
2021 ◽  
pp. 004209802097896
Author(s):  
Jennifer Candipan ◽  
Nolan Edward Phillips ◽  
Robert J Sampson ◽  
Mario Small
Keyword(s):  
Distinct Element ◽  
Minority Group ◽  
Racial Segregation ◽  
Racial Groups ◽  
Urban Mobility ◽  
Racial Conflict ◽  
Twitter Users ◽  
Black Populations ◽  
And Shifts ◽  
Us Cities

While research on racial segregation in cities has grown rapidly over the last several decades, its foundation remains the analysis of the neighbourhoods where people reside. However, contact between racial groups depends not merely on where people live, but also on where they travel over the course of everyday activities. To capture this reality, we propose a new measure of racial segregation – the segregated mobility index (SMI) – that captures the extent to which neighbourhoods of given racial compositions are connected to other types of neighbourhoods in equal measure. Based on hundreds of millions of geotagged tweets sent by over 375,000 Twitter users in the 50 largest US cities, we show that the SMI captures a distinct element of racial segregation, one that is related to, but not solely a function of, residential segregation. A city’s racial composition also matters; minority group threat, especially in cities with large Black populations and a troubled legacy of racial conflict, appears to depress movement across neighbourhoods in ways that produce previously undocumented forms of racial segregation. Our index, which could be constructed using other data sources, expands the possibilities for studying dynamic forms of racial segregation including their effects and shifts over time.

scholarly journals Beyond Virtual Classrooms: Exploring Feelings in the Social World

2021 ◽  
pp. 104837132098516
Author(s):  
Chiao-Wei Liu
Keyword(s):  
Racial Inequality ◽  
Well Being ◽  
Virtual Classroom ◽  
Supportive Relationships ◽  
Virtual Classrooms ◽  
Social Unrest ◽  
The Social ◽  
Personal Experiences ◽  
Embodied Experiences ◽  
Chronic Stressor

In this column, I continue to focus on creating supportive relationships in the virtual classroom amid the pandemic and growing social unrest. As many schools continue to shift between hybrid and remote learning, I ask, how do we address our own and students’ emotional well-being to promote active learning during the pandemic? How can we as teachers help students cope with this chronic stressor, be it the COVID-19 pandemic or the racial inequality? I share my own personal experiences and argue that affect/feelings/emotions are embodied thoughts imbricated with social values and often involved in the preservation of social expectations and power relations. I suggest that educators recognize affect/feelings/emotions as a critical part of students’ embodied experiences, encourage students to attend to their surrounding world and live their life with heightened consciousness and reflectiveness. I end this column with a few curriculum ideas for readers to consider.

scholarly journals Mobility patterns are associated with experienced income segregation in large US cities

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Esteban Moro ◽  
Dan Calacci ◽  
Xiaowen Dong ◽  
Alex Pentland
Keyword(s):  
Large Scale ◽  
Mobility Model ◽  
Coarse Grained ◽  
Spatial Proximity ◽  
Mobility Patterns ◽  
Data Set ◽  
Residential Patterns ◽  
Income Segregation ◽  
Mobility Data ◽  
Mobility Behavior

AbstractTraditional understanding of urban income segregation is largely based on static coarse-grained residential patterns. However, these do not capture the income segregation experience implied by the rich social interactions that happen in places that may relate to individual choices, opportunities, and mobility behavior. Using a large-scale high-resolution mobility data set of 4.5 million mobile phone users and 1.1 million places in 11 large American cities, we show that income segregation experienced in places and by individuals can differ greatly even within close spatial proximity. To further understand these fine-grained income segregation patterns, we introduce a Schelling extension of a well-known mobility model, and show that experienced income segregation is associated with an individual’s tendency to explore new places (place exploration) as well as places with visitors from different income groups (social exploration). Interestingly, while the latter is more strongly associated with demographic characteristics, the former is more strongly associated with mobility behavioral variables. Our results suggest that mobility behavior plays an important role in experienced income segregation of individuals. To measure this form of income segregation, urban researchers should take into account mobility behavior and not only residential patterns.

scholarly journals Cities, the Urban Green Environment, and Individual Subjective Well-Being: The Case of Milan, Italy

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Giorgio Tavano Blessi ◽  
Enzo Grossi ◽  
Giovanni Pieretti ◽  
Guido Ferilli ◽  
Alessandra Landi
Keyword(s):  
Urban Areas ◽  
Well Being ◽  
Spatial Proximity ◽  
Independent Effect ◽  
Subjective Well Being ◽  
Residential Proximity ◽  
Urban Green ◽  
Urban Green Areas ◽  
Green Areas ◽  
The Individual

This paper evaluates the independent effect of the spatial proximity of green urban areas upon the individual subjective well-being of the Milan population (Italy). The methodology is based on a survey undertaken in 2010 using a sample of 1,000 of Milan citizens. Univariate and multivariate analyses and GIS localization have been employed in order to rank the major individual well-being determinants and the relationship between citizens and urban green areas. Results show that the residential proximity of citizens to urban green areas seems to have little bearing on individual subjective well-being.

scholarly journals Does the Credit Cycle Have an Impact on Happiness?

2019 ◽  
Vol 17 (1) ◽  
pp. 183 ◽  
Author(s):  
Tinghui Li ◽  
Junhao Zhong ◽  
Mark Xu
Keyword(s):  
Fixed Effects ◽  
Well Being ◽  
Gdp Per Capita ◽  
Subjective Well Being ◽  
Fixed Effects Model ◽  
Credit Expansion ◽  
Transmission Channels ◽  
Credit Cycle ◽  
Per Capita ◽  
The Relationship

The 2008 international financial crisis triggered a heated discussion of the relationship between public health and the economic environment. We test the relationship between the credit cycle and happiness using the fixed effects model and explore the transmission channels between them by adding the moderating effect. The results show the following empirical regularities. First, the credit cycle has a negative correlation with happiness. This means that credit growth will reduce the overall happiness score in a country/region. Second, the transmission channels between the credit cycle and happiness are different during credit expansion and recession. Life expectancy and generosity can moderate the relationship between the credit cycle and happiness only during credit expansion. GDP per capita can moderate this relationship only during credit recession. Social support, freedom, and positive affect can moderate this relationship throughout the credit cycle. Third, the total impact of the credit cycle on happiness will become positive by the changes in the moderating effects. In general, we can improve subjective well-being if one of the following five conditions holds: (1) with the adequate support from the family and society, (2) with enough freedom, (3) with social generosity, (4) with a positive and optimistic outlook, and (5) with a high level of GDP per capita.

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