The Empirics of the Digital Divide

2013 ◽  
pp. 294-312
Author(s):  
Wei-Min Hu ◽  
James E. Prieger
Keyword(s):  
Digital Divide ◽  
Empirical Studies ◽  
Duration Analysis ◽  
Estimation Methods ◽  
Cross Sectional ◽  
Technological Adoption ◽  
Digital Divides ◽  
Econometric Methodology ◽  
Catch Up ◽  
The U.S

Accurate measurement of digital divides is important for policy purposes. Empirical studies of broadband subscription gaps have largely used cross-sectional data, which cannot speak to the timing of technological adoption. Yet, the dynamics of a digital divide are important and deserve study. With the goal of improving our understanding of appropriate techniques for analyzing digital divides, we review econometric methodology and propose the use of duration analysis. We compare the performance of alternative estimation methods using a large dataset on DSL subscription in the U.S., paying particular attention to whether women, blacks, and Hispanics catch up to others in the broadband adoption race. We conclude that duration analysis best captures the dynamics of the broadband gaps and is a useful addition to the analytic tool box of digital divide researchers. Our results support the official collection of broadband statistics in panel form, where the same households are followed over time.

The Empirics of the Digital Divide

2010 ◽  
pp. 645-665 ◽  
Author(s):  
Wei-Min Hu ◽  
James E. Prieger
Keyword(s):  
Digital Divide ◽  
Empirical Studies ◽  
Duration Analysis ◽  
Estimation Methods ◽  
Cross Sectional ◽  
Technological Adoption ◽  
Digital Divides ◽  
Econometric Methodology ◽  
Catch Up ◽  
The U.S

Accurate measurement of digital divides is important for policy purposes. Empirical studies of broadband subscription gaps have largely used cross-sectional data, which cannot speak to the timing of technological adoption. Yet, the dynamics of a digital divide are important and deserve study. With the goal of improving our understanding of appropriate techniques for analyzing digital divides, we review econometric methodology and propose the use of duration analysis. We compare the performance of alternative estimation methods using a large dataset on DSL subscription in the U.S., paying particular attention to whether women, blacks, and Hispanics catch up to others in the broadband adoption race. We conclude that duration analysis best captures the dynamics of the broadband gaps and is a useful addition to the analytic tool box of digital divide researchers. Our results support the official collection of broadband statistics in panel form, where the same households are followed over time.

scholarly journals Does Ageism Widen the Digital Divide? And Does It Vary by Gender?

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 315-315
Author(s):  
Eun Young Choi ◽  
Youngsun Kim ◽  
Edson Chipalo ◽  
Hee Yun Lee
Keyword(s):  
Digital Divide ◽  
Internet Use ◽  
Empirical Studies ◽  
Age Groups ◽  
Interaction Effects ◽  
The Internet ◽  
Older Individuals ◽  
Cross Sectional ◽  
Use Of The Internet ◽  
Retirement Study

Abstract Existing literature informed that ageism might affect Internet use among older adults, further widening the digital divide among age groups. However, little empirical studies have been conducted on this topic. Our study aims to investigate (1) the current use of the Internet by gender, (2) the association between ageism and Internet use, and (3) potential gender differences. A cross-sectional data drawn from the 2016 Health and Retirement Study (HRS) was analyzed. Separate multiple regression analyses were conducted by gender to determine the varying impact of ageism on Internet use. We used two types of ageism (1) internal ageism (ingroup discrimination) and (2) external ageism (discrimination from external entities) to observe each type’s contribution to Internet use. About half of the sample (52% male and 54% female) reported using the Internet “daily,” while a quarter (26% male and 25% female) responded, “never/not relevant.” No significant differences between gender were found in levels of Internet use, the rates of external ageism, or the degree of internal ageism. A higher level of ageism was associated with a lower level of Internet use. Interaction effects between age groups and ageism varied across gender: external ageism had interaction effects on men’s Internet use whereas internal ageism showed significant results for women. Our findings suggest that ageism may influence Internet use and its impact differs by gender. Gender-tailored intervention strategies should be developed to help older individuals to diminish the adverse effects of ageism on Internet use.

Digital Inequality Among States at an European Level

2021 ◽  
Vol 12 (3) ◽  
pp. 0-0
Keyword(s):  
Digital Divide ◽  
Empirical Studies ◽  
Secondary Data ◽  
Social Phenomenon ◽  
European Level ◽  
Digital Inequality ◽  
The Past ◽  
Digital Divides ◽  
Digital Skills ◽  
The Web

For the past twenty-five years, digital inequalities have been analyzed by several scholars. Many empirical studies have shaped a theoretical framework that identifies three main digital divides. However, most of the scientific contributions have been focusing on digital inequalities within countries, leaving inequalities among countries behind. This paper aims at analyzing what kind of digital inequalities emerge among European countries, focusing on the trends that characterized Europe in the last decade, to consider whether some of the main elements of the digital divide literature replicate at the continental level. The paper analyzes secondary data, mainly retrieved from Eurostat. It emerges that inequalities in digital skills and use of the Web persist in Europe, and some of the trends that scholars found among individuals are identifiable among countries as well. These findings contribute to the description of digital inequalities, a social phenomenon not so deeply studied at the continental level.

scholarly journals The Latent Digital Divides and Its Drivers in E-Learning: Among Bangladeshi Student During COVID-19 Pandemic

2021 ◽  
Author(s):  
Md Badiuzzaman ◽  
Md. Rafiquzzaman ◽  
Md Insiat Islam Rabby ◽  
Mohammad Mustaineer Rahman
Keyword(s):  
Online Learning ◽  
Digital Divide ◽  
Learning Activities ◽  
Educational Institutions ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Student Community ◽  
Digital Divides ◽  
Learning Programs ◽  
Physical Access

The devastating COVID-19 pandemic forced academia to go virtual. Educational institutions around the world have stressed online learning programs in the aftermath of the pandemic. However, because of insufficient access to ICT, a substantial number of students failed to harness the opportunity of online learning. This study explores the latent digital divide exhibited during the COVID-19 pandemic while online learning activities are emphasized among Bangladeshi students. It also explores the digital divide exposure and the significant underlying drivers of the divide. A cross-sectional survey was employed to collect quantitative data mixed with open-ended questions to collect qualitative information from the student community. The findings revealed that despite the majority of students have physical access to ICT but only 32.5% of students could attend online classes seamlessly, 34.1% of the students reported the data prices as the critical barrier, and 39.8% of students identified the poor network infrastructure is the significant barrier for them to participate in online learning activities. This paper aimed to explore the underlying issues of the digital divide among Bangladeshi students to assist relevant stakeholders (e.g., the Bangladesh government, Educational Institutions, Researchers) in providing the necessary insights to arrange for students to undertake online learning activities successfully.

scholarly journals Public Health Workforce Burnout in the COVID-19 Response in the U.S.

2021 ◽  
Vol 18 (8) ◽  
pp. 4369
Author(s):  
Kahler W. Stone ◽  
Kristina W. Kintziger ◽  
Meredith A. Jagger ◽  
Jennifer A. Horney
Keyword(s):  
Public Health ◽  
Health Workforce ◽  
Work Experience ◽  
Large Scale ◽  
Health Workers ◽  
Public Health Workforce ◽  
Cross Sectional Survey ◽  
Public Health Response ◽  
Cross Sectional ◽  
The U.S

While the health impacts of the COVID-19 pandemic on frontline health care workers have been well described, the effects of the COVID-19 response on the U.S. public health workforce, which has been impacted by the prolonged public health response to the pandemic, has not been adequately characterized. A cross-sectional survey of public health professionals was conducted to assess mental and physical health, risk and protective factors for burnout, and short- and long-term career decisions during the pandemic response. The survey was completed online using the Qualtrics survey platform. Descriptive statistics and prevalence ratios (95% confidence intervals) were calculated. Among responses received from 23 August and 11 September 2020, 66.2% of public health workers reported burnout. Those with more work experience (1–4 vs. <1 years: prevalence ratio (PR) = 1.90, 95% confidence interval (CI) = 1.08−3.36; 5–9 vs. <1 years: PR = 1.89, CI = 1.07−3.34) or working in academic settings (vs. practice: PR = 1.31, CI = 1.08–1.58) were most likely to report burnout. As of September 2020, 23.6% fewer respondents planned to remain in the U.S. public health workforce for three or more years compared to their retrospectively reported January 2020 plans. A large-scale public health emergency response places unsustainable burdens on an already underfunded and understaffed public health workforce. Pandemic-related burnout threatens the U.S. public health workforce’s future when many challenges related to the ongoing COVID-19 response remain unaddressed.

Reliability Estimates for IRT-Based Forced-Choice Assessment Scores

2021 ◽  
pp. 109442812199908
Author(s):  
Yin Lin
Keyword(s):  
Impression Management ◽  
Empirical Studies ◽  
Forced Choice ◽  
Reliability Estimation ◽  
Estimation Methods ◽  
High Stakes ◽  
Personnel Decisions ◽  
Assessment Scores ◽  
Reliability Estimates ◽  
Different Types

Forced-choice (FC) assessments of noncognitive psychological constructs (e.g., personality, behavioral tendencies) are popular in high-stakes organizational testing scenarios (e.g., informing hiring decisions) due to their enhanced resistance against response distortions (e.g., faking good, impression management). The measurement precisions of FC assessment scores used to inform personnel decisions are of paramount importance in practice. Different types of reliability estimates are reported for FC assessment scores in current publications, while consensus on best practices appears to be lacking. In order to provide understanding and structure around the reporting of FC reliability, this study systematically examined different types of reliability estimation methods for Thurstonian IRT-based FC assessment scores: their theoretical differences were discussed, and their numerical differences were illustrated through a series of simulations and empirical studies. In doing so, this study provides a practical guide for appraising different reliability estimation methods for IRT-based FC assessment scores.

Assessment of needs for care among patients with schizophrenic disorders 15 and 17 years after first onset of psychosis

1997 ◽  
Vol 6 (S1) ◽  
pp. 21-28 ◽  
Author(s):  
Durk Wiersma ◽  
Fokko J. Nienhuis ◽  
Cees J. Slooff ◽  
Robert Giel ◽  
Aant De Jong
Keyword(s):  
Mental Disorders ◽  
Empirical Studies ◽  
Signs And Symptoms ◽  
Expected Improvement ◽  
Chronic Patients ◽  
Cross Sectional ◽  
Wide Range ◽  
Social Disablement ◽  
First Onset

Severe and long term mental disorders, like schizophrenia, show in general a wide range of psychiatric signs and symptoms, psychological and physiological impairments and social disablement (Shepherd, 1994; Wing, 1982) reflecting a variety of mental health needs. Many studies provide only a cross-sectional view of the clinical and social problems of the patient population, for example at intake or admission to a mental hospital. Longitudinal studies following patients after discharge for some period of months or years show in general the expected improvement of functioning (e.g. Nienhuis et al., 1994), but as far as only chronic patients are concerned such a positive change is much less noted. The concept of chronicity of mental disorders would presume that after some time needs are fairly predictable and stable and do not change much over time. Our investigation on the long-term course of schizophrenia (Wiersma et al., 1996; 1997) enables us to study over a period of two years, from 15 to 17 years since first onset of psychosis, the stability or variability of needs in schizophrenic disorder. We are not aware of empirical studies on changes in needs among patients with long-term disorders.

scholarly journals POWER LAWS IN REAL ESTATE PRICES DURING BUBBLE PERIODS

2012 ◽  
Vol 16 ◽  
pp. 61-81 ◽  
Author(s):  
TAKAAKI OHNISHI ◽  
TAKAYUKI MIZUNO ◽  
CHIHIRO SHIMIZU ◽  
TSUTOMU WATANABE
Keyword(s):  
Real Estate ◽  
Power Law ◽  
House Price ◽  
Power Laws ◽  
Cross Sectional ◽  
Price Distribution ◽  
Before And After ◽  
Real Estate Prices ◽  
Using Data ◽  
The U.S

How can we detect real estate bubbles? In this paper, we propose making use of information on the cross-sectional dispersion of real estate prices. During bubble periods, prices tend to go up considerably for some properties, but less so for others, so that price inequality across properties increases. In other words, a key characteristic of real estate bubbles is not the rapid price hike itself but a rise in price dispersion. Given this, the purpose of this paper is to examine whether developments in the dispersion in real estate prices can be used to detect bubbles in property markets as they arise, using data from Japan and the U.S. First, we show that the land price distribution in Tokyo had a power-law tail during the bubble period in the late 1980s, while it was very close to a lognormal before and after the bubble period. Second, in the U.S. data we find that the tail of the house price distribution tends to be heavier in those states which experienced a housing bubble. We also provide evidence suggesting that the power-law tail observed during bubble periods arises due to the lack of price arbitrage across regions.

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