Internet - Our World in Data
Digital Inequality and Low-Income Households Highlights Research on digital inequality has shifted toward frameworks Internet as the main income consider multiple dimensions and levels, including social supports and other neighborhood-level factors. Low-income households have lower rates of in-home Internet connectivity compared with higher-income groups. Connectivity rates are particularly low among HUD-assisted renter households, who are also more likely to depend exclusively on smartphones and other handheld devices to access the Internet in the home.
Broadband access This chart shows the number of fixed broadband subscriptions per people. Means of connection include cable modem, DSL, fiber-to-the-home, other fixed wired -broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. Excluded are subscriptions via mobile-cellular networks. Click to open interactive version Mobile phone use A truly disruptive technological development has been the rise of mobile phones.
Low-income households are most likely to cite affordability constraints as a substantial barrier to in-home broadband adoption. Eighty percent of respondents to the — ConnectHome baseline survey who lacked Internet access at home cited Internet costs as one reason they lacked in-home Internet access, and 37 percent cited device costs. Source: Thom File and Camille Ryan.
Census Bureau, 3. As information, services, and resources increasingly move online, digital inequality has come to both reflect and contribute to other persistent forms of social inequality. Building on the idea that digital inclusion is an important part of broader efforts to create strong, inclusive communities and improve opportunities and quality of life for all Americans, this article offers a series of frameworks, points of reference, and data for developing strategies to address current relationships between low-income housing and digital inequality.
Digital Inequality Frameworks Dominant approaches to thinking about and measuring digital inequality have evolved since the commercialization of the Internet in the mids. Studies rooted in this framework sought to identify gaps in access to the Internet and computers by income, new ideas of making money on the Internet, age, education, and other types of inequality,8 both within and between countries.
Multidimensional Digital Inequality. One key way in which digital inequality frameworks shifted was by focusing on the multiple dimensions of digital inequality, highlighting how access to, and the use of, digital technologies varies even among people with formal access to the Internet. This multidimensional approach draws attention to five key aspects of digital inequality, each of which shapes Internet use as well as returns to use.
This aspect of digital inequality includes the extent to which households have computers, software, and connections that allow them to effectively engage with online content.
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- Digital Inequality and Low-Income Households | HUD USER
Multidimensional approaches also emphasize variations in the autonomy of Internet use. Autonomy includes whether users access the Internet from work or home, whether their use is monitored, their frequency of use, whether they must compete with others for time and access, and the extent to which their use is circumscribed by filters or other constraints. Such support can include formal technical assistance, technical assistance from friends and family, and emotional reinforcement from friends and family.
Finally, a multidimensional perspective emphasizes variations in the purposes for which people use technology. This dimension involves the ways in which people use the Internet to increase their economic productivity and their political and social capital.
In addition to highlighting multiple dimensions of digital inequality, digital inequality frameworks have also paid increasing attention to how social dynamics at different levels of society influence Internet access and use. This multilevel perspective builds on earlier digital inequality literature that focused on individual-level characteristics, behaviors, and outcomes, to also consider how family, community, neighborhood, and network factors contribute to digital inequalities.
High-speed Internet indicates that a household has Internet service other than dial-up. Source: U. Census Bureau and U.
Those in higher-income households are different from other Americans in their tech ownership and use.
Department of Housing and Urban Development. This approach emphasizes the role that human-to-human interactions play in shaping digital adoption, situating broadband use within broader communications networks and social resources.
These dynamics, particularly within networks consisting of people of similar status, can increase inequality by significantly reducing adoption rates in less privileged groups. In short, research on digital inequalities has shifted over the past several decades from frameworks focused on capturing inequalities between the connected and unconnected to more nuanced frameworks that consider digital inequalities along multiple dimensions and at multiple levels of society.
By Investopedia Updated Feb 1, It may seem contradictory that companies that operate Internet businesses are able to make substantial profits each year despite offering their services for free. Companies that operate in Internet services have grown in number consistently over the years as more consumers are utilizing the Internet to purchase products and services, connect with family and friends, search for employment, or gain access to information and news on virtually any topic. The majority of content provided through these Internet companies is offered to users at little to no cost, and consumers have grown accustomed to accessing information found on the Internet for free.
These new frameworks call for strategies that address multiple aspects of digital inequality, including affordable devices and broadband access, digital literacy training, and publicly accessible computing centers with helpful staff and support.
Although assisted housing providers are well positioned to address many of the central challenges that shape digital inequality today, relatively little research has examined specific associations between low-income housing and Internet access.
This section Internet as the main income recent data detailing the relationship between low-income housing and digital inequality. Internet Connectivity Trends.
One dimension of digital inequality focuses on Internet connectivity, defined here as in-home adoption of high-speed Internet. Connectivity disparities — by both income and geography — align in important ways with low-income housing patterns.
Household income is strongly associated with in-home Internet connectivity levels, with low-income households being less connected than higher-income households. As a result, modest declines in broadband adoption from to were concentrated among low- to middle-income households. Broadband continues to be less available in rural areas than in urban areas, particularly at higher speeds. Many rural areas have only one Internet service provider, and some rural areas have access to only satellite and cellular modem service or have no broadband availability at all.
As a result, small-town residents tend to have less broadband availability than ex-urbanites despite living in much more densely populated areas. Census Bureau, 3, 9.
Internet use over time
Substantial variation in adoption rates, Internet quality, and connection speeds exists within cities and is correlated with household income. Examining merged ACS and HUD administrative data offers insight into the relationship between housing and in-home Internet access. These data indicate that connectivity rates among HUD-assisted households are very low; only 43 percent of HUD-assisted renters subscribed to high-speed Internet service at home compared with 69 percent of unassisted renters and 80 percent of owners table 1.
The connectivity rate for HUD-assisted renters is even lower than the rate for all U.
The survey collected data on in-home Internet access in 22 of these communities in and