Digital Inequalities and Social Stratification

Introduction to Digital Inequalities and the Social World

The distribution of benefits and profits derived from technology is a core concern for sociologists.
Examining technology use reveals critical insights into how power operates within a specific society and the social dynamics that result from it.
Societal structures are inherently unequal, which leads to disparities in who benefits from the introduction and diffusion of new technologies.
Positions for accessing, learning about, and utilizing technology are not uniform across the population.
A fundamental question for digital sociologists is: Who possesses the power to create, understand, and use technology?
Social patterns of inequality are often reinforced and reproduced by digital tools, though they also hold the potential to be altered.

Global Digital Inequalities

The internet is not distributed equally on a global scale.
The digital landscape has significantly rearranged global labor markets.
Offshoring: The internet has made it economically advantageous to move jobs like customer service and sales offshore. This often occurs without the customer's knowledge, raising questions about who is advantaged or disadvantaged in these economic shifts.
Unequal access constrains individuals in countries with low internet penetration, limiting their ability to participate and benefit in the global economy.
Consequences of low penetration include a significant disadvantage in economic attainment and overall quality of life.
Impact areas: Digital inequality directly affects education, employment, and access to healthcare.
Compounding effects: The gap between those reliably connected and those who are not becomes increasingly difficult to bridge over time (DiMaggio, 2014; McKinsey and Company, 2014).
Economic barriers: Even where access is technically available, low income and standard of living remain barriers. Costs for hardware (computers, smartphones) and connectivity may be unaffordable for many.

Social Stratification and the Digital Hierarchy

Societal groups are differentiated by various characteristics: age, race, ethnicity, gender, sexual orientation, socioeconomic status (SES), intellectual or physical ability, occupation, religious beliefs, and political or national affiliation.
Social Stratification: The metaphorical division of society into tiers or layers (upper class, middle class, working class, the poor) that form a ranking system.
Individuals within the same rank often share common perspectives, attitudes, and worldviews.
These shared rankings also influence dispositions toward technology, including comfort levels, access, literacy, and competency.
Chayko ( $2017$ ) argues that an individual's attitude and use of technology affect multiple life domains, including wealth, career trajectories, family relationships, and cultural activities.

Internet Access Statistics and Global Metrics (2024-2025)

Global User Counts: - Estimated internet users: $5.44 \text{ billion}$ (Statista $2025$ ) or $5.52 \text{ billion}$ (Data Reportal $2024$ ). - User growth: Increased by $151 \text{ million}$ between October $2023$ and October $2024$ (Data Reportal $2024$ ). - Total reach: Approximately two-thirds of the global population is connected to the world-wide web.
National Rankings and Penetration: - China has the highest total number of internet users, followed by India and the United States. - East Asia contains the most users overall, but Northern Europe has the highest penetration rate (the percentage of the population with access). - China’s penetration rate is $77.5\%$ . - The Netherlands, Norway, Saudi Arabia, and the United Arab Emirates (UAE) have penetration rates of nearly $100\%$ . - North Korea remains almost entirely offline ( $99.9\% \text{ offline}$ ). - Paradoxically, while China and India have the most users, they also have some of the lowest penetration rates among major nations.
The Unconnected: Approximately $2.66 \text{ billion}$ people remain unconnected, primarily located in Southern Asia, Eastern Asia, and Africa.

Transition to Mobile Digital Society

Modern internet access has moved past desktop computers and dial-up connections.
Smartphone Usage: $96.2\%$ of internet users utilize a mobile phone to go online (Data Reportal $2024$ ).
Time and Traffic: - Mobile phones account for $56.9\%$ of an individual's time spent online. - Mobile phones account for $61.6\%$ of all global web traffic.

Political and Governmental Inequalities

Political control over digital media significantly impacts user access.
Forms of control include: - Repressive legislation: Cited in Saudi Arabia and Zimbabwe. - Public ownership, licensing, and regulation: Cited in China, Syria, and Morocco. - Collusion: Private media owners collaborating with governments, cited in Latin America.
Content Filtering: Nations such as China, Syria, and Russia use internet service providers (ISPs) to filter out dissident or critical websites (Curran, $2012$ ).
Internet Shutdowns: Countries like Egypt, Iran, and Libya have overtly shut down the internet to halt social media use during citizen protests (e.g., the $2011$ Arab Spring).

Educational and Economic Correlations

There is a high correlation between digital connectedness and levels of income/education (McKinsey and Company, $2014$ ).
These are not binary variables; they exist on a continuum of degree.
Barriers related to education: - Lack of formal education results in a lack of skills required for digital navigation. - Low language literacy (reading and writing difficulties) poses a major barrier to internet use.

Multilevel Digital Divides

First-Level Disparities: Defined as basic access to the internet. - In the United States ( $2014$ ), $14\%$ of adults did not use the internet. - In $2024$ , $96\%$ of US adults use the internet, but $15\%$ are "smartphone only" users (Pew $2024$ ). - Smartphone dependence is higher among those with lower household incomes and lower formal education levels.
Second-Level Inequalities: Refers to disparities in skills, participation, and efficacy among those who are technically "users." - Disadvantaged groups may use the internet less intensively than advantaged groups. - Determinants of proficiency include race/ethnicity (Mesch & Talmud, $2011$ ), gender (Ono & Zavodny, $2008$ ), and SES (Witte & Mannon, $2010$ ).
Third-Level Digital Divide: Refers to the outcome of internet use. - Focuses on the distinction between using the internet for information seeking/productivity versus purely for entertainment. - Privileged individuals tend to engage in "capital-enhancing activities" (Bonfadelli, $2002$ ; Eynon, $2009$ ).

Digital Inequality Over the Life Course

Childhood: - Parental behaviors like "sharenting" or child influencers may have damaging effects on children. - While often called "digital natives," children show high variation in access and skills based on economic background. - Economic disadvantage forces some youth to "ration" screen time, depriving them of skill-building opportunities (Robinson, $2012$ , $2011$ ).
Midlife: The "sandwich generation" (Chisholm, $1999$ ) uses digital resources to manage care for both children and elderly parents, yet they may also be burdened by the need to facilitate digital access for others.
Senior Years: - Older age groups risk losing digital benefits due to lack of education or economic resources. - Tech-savvy seniors (often younger, wealthier, more educated) find their lives enriched by connectedness (Cotten, Ford, Ford, & Hale, $2014$ ).

Gender Disparities in the Digital Sphere

Early waves of research (Ono and Zavodny, $2003$ ) found women were significantly less likely than men to be online in the mid- $1990\text{s}$ , but this gap closed by $2000$ .
Intensity and Autonomy: While the access gap closed in advanced economies, women often remain less frequent or intense users and may have lower autonomy or social support for use (DiMaggio et al. $2004$ ; Hargittai $2008$ ).
The Self-Efficacy Gap: Women tend to rate their online skills lower than men even when their actual observed skills are equal (Hargittai and Shafer, $2006$ ).
Household dynamics: Women's higher share of household and child-rearing duties leaves less leisure time for web browsing.
Developing Countries (Global South): - The OECD ( $2018$ ) reports a widening gender gap in less developed countries. - UNICEF ( $2023$ ) found that in low-income countries, $90\%$ of adolescent girls and young women (ages $15$ - $24$ ) are offline. - Skill disparity: For every $100$ male youth with digital skills, only $65$ females possess them across $32$ analyzed countries. - Ownership: Female youth are nearly $13\%$ less likely to own a mobile phone.

The Digital Inequality Stack

Developed by Robinson et al. ( $2020$ ), the "stack" illustrates how multiple layers of deficiency impact overall capacity.
Layers include: Connectivity/infrastructure, hardware/software, literacies/skills, and production/programming.
Hypothetical Case Study of "Alex": - Setting: Rural area, developed economy. - Education: Minimal, no digital skills taught in school. - Employment: Customer associate in retail; no digital resources or training on the job. - Economic state: Low wages make broadband and personal devices unaffordable. - Result: Alex depends on an outdated smartphone with spotty reception, using it only for free social media/entertainment. Alex’s social network reinforces this disadvantage.
Key Principle: Disruption to one layer of the stack may damage the whole; foundational layers (access) often translate to inequalities in higher layers (skill building).

Conclusion and Broader Context

Digital inequalities are more complex than the original simple concept of the "digital divide."
These inequalities stack within and across various contexts.
Offline identities (gender, sexuality, rurality, ethnicity, SES) heavily dictate online capabilities and outcomes.
Current status: Early techno-utopian visions of equality have been replaced by the reality that offline status matters significantly in the digital world.