scholarly journals Geography of racial coresidence

2021 ◽  
Author(s):  
Anna Dmowska ◽  
Tomasz Stepinski
Keyword(s):  
Metropolitan Areas ◽  
Data Driven ◽  
Racial Groups ◽  
Census Block ◽  
Asian Populations ◽  
Racial Preferences ◽  
Level Data ◽  
Geographical Regions ◽  
Block Level ◽  
Us Cities

Whereas most work on residential race relations in US cities is based on the concept of segregation, our approach studies this issue from a who-lives-with-whom perspective. To this end, we study coresidence profiles – percentages of a given racial subpopulation living in different population zones. Population zones are data-driven divisions of a city based on characteristic racial compositions. We used 1990 and 2010 decennial census block-level data for 61 largest US metropolitan areas to calculate coresidence profiles for four major racial subpopulations in each city at both years. Profiles for each race/year combination were clustered into three archetypes. Cities, where given race profiles belong to the same archetype, have similar coresidence patterns with respect to this race. We present the geographic distributions of co-habitation profiles and show how they changed during the 1990-2010 period. Our results revealed that coresidence profiles depend not only on racial preferences but also on the availability of racial groups; cities in the different geographical regions have different coresidence profiles because they have different shares of White, Black, Hispanic, and Asian subpopulations. Temporal changes in coresidence profiles are linked to the increased share of Hispanic and Asian populations.

Foreign-born population concentration and neighbourhood growth and development within US metropolitan areas

Urban Studies ◽  
2016 ◽  
Vol 55 (4) ◽  
pp. 826-843 ◽  
Author(s):  
Matt Ruther ◽  
Rebbeca Tesfai ◽  
Janice Madden
Keyword(s):  
Population Growth ◽  
Metropolitan Areas ◽  
Spatial Regression ◽  
Relative Income ◽  
Immigrant Population ◽  
Racial Groups ◽  
Foreign Born ◽  
Immigrant Populations ◽  
Level Data ◽  
Population Concentration

Immigrant populations are a major driver of growth in many US metropolitan areas, and considerable research has focused on the effects of immigrant populations on neighbourhood outcomes. However, much of this research is based on data from 1990 or earlier, prior to substantial growth in the diversity of the immigrant population and to changes in immigrants’ US settlement patterns. This research uses tract-level data from the 2000 Decennial Census and the 2009–2013 American Community Survey to explore the relationship between an existing immigrant population and future changes in neighbourhood characteristics within the 100 largest US metropolitan areas. Spatial regression models are used to identify the neighbourhood features that predict future proportional growth in a neighbourhood’s foreign-born population. In addition, the associations between a neighbourhood’s initial foreign-born concentration and future neighbourhood relative income and population growth are investigated. Consistent with previous work, our results indicate that foreign-born populations of all races tend to move towards existing immigrant population clusters. All of the immigrant minority racial groups are also attracted to neighbourhoods with existing same-race US-born populations. Overall proportional population growth is positively associated with the initial presence of the white and Asian immigrant population; black and Hispanic immigrant concentrations are associated with proportional population loss. While immigrants do not contribute to neighbourhood relative income growth, a greater presence of immigrants – relative to their US-born co-racial group – is associated with lower rates of neighbourhood relative income decline.

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.

RiRiShun Logistics: Home Appliance Delivery Data for the 2021 Manufacturing & Service Operations Management Data-Driven Research Challenge

2021 ◽  
Author(s):  
Xiaolong Guo ◽  
Yugang Yu ◽  
Gad Allon ◽  
Meiyan Wang ◽  
Zhentai Zhang
Keyword(s):  
Operations Management ◽  
Service Operations ◽  
Optimization Techniques ◽  
Data Driven ◽  
Analytical Models ◽  
Data Set ◽  
Service Operations Management ◽  
Level Data ◽  
Home Appliance ◽  
Research Challenge

To support the 2021 Manufacturing & Service Operations Management (MSOM) Data-Driven Research Challenge, RiRiShun Logistics (a Haier group subsidiary focusing on logistics service for home appliances) provides MSOM members with logistics operational-level data for data-driven research. This paper provides a detailed description of the data associated with over 14 million orders from 149 clients (the consigners) associated with 4.2 million end consumers (the recipients and end users of the appliances) in China, involving 18,000 stock keeping units operated at 103 warehouses. Researchers are welcomed to develop econometric models, data-driven optimization techniques, analytical models, and algorithm designs by using this data set to address questions suggested by company managers.

scholarly journals Deduplication in Cloud Storage

2019 ◽  
Vol 9 (2S) ◽  
pp. 364-368
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Cloud Service ◽  
Information Storage ◽  
Cloud Environment ◽  
Data Deduplication ◽  
Cloud Service Provider ◽  
Level Data ◽  
Block Level ◽  
Individual Client

Cloud Computing is well known today on account of enormous measure of data storage and quick access of information over the system. It gives an individual client boundless extra space, accessibility and openness of information whenever at anyplace. Cloud service provider can boost information storage by incorporating data deduplication into cloud storage, despite the fact that information deduplication removes excess information and reproduced information happens in cloud environment. This paper presents a literature survey alongside different deduplication procedures that have been based on cloud information storage. To all the more likely guarantee secure deduplication in cloud, this paper examines file level data deduplication and block level data deduplication.

Census-block-level Property Risk Assessment for Wildfire in Louisiana, U.S.A

2021 ◽  
Author(s):  
Rubayet Bin Mostafiz ◽  
Carol Friedland ◽  
Robert Rohli ◽  
Nazla Bushra
Keyword(s):  
Risk Assessment ◽  
Census Block ◽  
Block Level ◽  
Level Property

Equity in high school computer science: Beyond access

2021 ◽  
pp. 147821032110630
Author(s):  
Paul Bruno ◽  
Colleen M Lewis
Keyword(s):  
High School ◽  
Native American ◽  
High School Students ◽  
Computer Science ◽  
Female Students ◽  
Racial Groups ◽  
School Students ◽  
Level Data ◽  
And Gender ◽  
K 12

Little is known about the extent to which expansions of K-12 computer science (CS) have been equitable for students of different racial backgrounds and gender identities. Using longitudinal course-level data from all high schools in California between the 2003–2004 and 2018–2019 school years we find that 79% of high school students in California, including majorities of all racial groups, are enrolled in schools that offer CS, up from 45% in 2003. However, while male and female students are equally likely to attend schools that offer CS courses, CS courses represent a much smaller share of course enrollments for female students than for male students. Non-Asian students enroll in relatively few CS courses, and this is particularly true for Black, Hispanic, and Native American students. Race gaps in CS participation are to a substantial degree explicable in terms of access gaps, but gender gaps in CS participation are not. Different groups of students have access to CS teachers with similar observable qualifications, but CS teachers remain predominantly white and male. Consequently, white and male CS students are much more likely than other students to have same-race or same-gender instructors. Our findings and the implications we draw for practice will be of interest to administrators and policymakers who, over and above needing to ensure equitable access to CS courses for students, need to attend carefully to equity-related course participation and staffing considerations.

Product-level profitability

2019 ◽  
Vol 33 (1) ◽  
pp. 214-237
Author(s):  
Hannu Hannila ◽  
Joni Koskinen ◽  
Janne Harkonen ◽  
Harri Haapasalo
Keyword(s):  
Business Processes ◽  
Data Driven ◽  
Product Portfolio ◽  
Data Governance ◽  
Content Type ◽  
Technical Product ◽  
Product Level ◽  
Level Data ◽  
Corporate Level

Purpose The purpose of this paper is to analyse current challenges and to articulate the preconditions for data-driven, fact-based product portfolio management (PPM) based on commercial and technical product structures, critical business processes, corporate business IT and company data assets. Here, data assets were classified from a PPM perspective in terms of (product/customer/supplier) master data, transaction data and Internet of Things data. The study also addresses the supporting role of corporate-level data governance. Design/methodology/approach The study combines a literature review and qualitative analysis of empirical data collected from eight international companies of varying size. Findings Companies’ current inability to analyse products effectively based on existing data is surprising. The present findings identify a number of preconditions for data-driven, fact-based PPM, including mutual understanding of company products (to establish a consistent commercial and technical product structure), product classification as strategic, supportive or non-strategic (to link commercial and technical product structures with product strategy) and a holistic, corporate-level data model for adjusting the company’s business IT (to support product portfolio visualisation). Practical implications The findings provide a logical and empirical basis for fact-based, product-level analysis of product profitability and analysis of the product portfolio over the product life cycle, supporting a data-driven approach to the optimisation of commercial and technical product structure, business IT systems and company product strategy. As a virtual representation of reality, the company data model facilitates product visualisation. The findings are of great practical value, as they demonstrate the significance of corporate-level data assets, data governance and business-critical data for managing a company’s products and portfolio. Originality/value The study contributes to the existing literature by specifying the preconditions for data-driven, fact-based PPM as a basis for product-level analysis and decision making, emphasising the role of company data assets and clarifying the links between business processes, information systems and data assets for PPM.

Do Asian patients have worse lupus?

Lupus ◽  
2010 ◽  
Vol 19 (12) ◽  
pp. 1384-1390 ◽  
Author(s):  
MY Mok ◽  
WL Li
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Nephritis ◽  
Lupus Erythematosus ◽  
Renal Outcome ◽  
Receptor Subtypes ◽  
Systemic Lupus ◽  
Asian Populations ◽  
Asian Patients ◽  
Geographical Regions ◽  
White Patients

The predisposition to and clinical phenotype of systemic lupus erythematosus, an autoimmune disease that is associated with significant morbidity and mortality, are affected by genetic and environmental factors. This article aims to examine whether Asians have worse lupus by reviewing the literature on genetic predisposition and clinical outcomes, including major organ involvement, damage score and mortality in Asian populations compared with other ethnicities. A number of lupus nephritis susceptibility genes have been identified in Asians and White patients, with further variations among different Asian populations. Meta-analysis studies on various Fcγ receptor subtypes revealed that FcγRIIIA-F158 allele, which is associated with low binding affinity to IgG1 and IgG3, predisposed to lupus nephritis in Asian patients. Asian patients were reported to have higher rates of lupus nephritis-associated autoantibodies, lupus nephritis and more active glomerulonephritis compared with White patients. Renal outcome and the level of immunosuppressant use in Asians were comparable to Afro-American Blacks in some studies. Asians were also found to have higher overall damage scores compared with Whites. The difference in mortality between Asian patients and other ethnicities in different geographical regions was found to vary depending on socioeconomic factors such as access to health care. Poverty, education level, cultural and behavioural factors are confounders to ethnicity in determining clinical outcome of systemic lupus erythematosus.

Sign in / Sign up

Export Citation Format

Share Document