Fragment from Chapter 4, The Deepening Divide
(p. 48-52)

Types and Places of Material Access

In this chapter, I make the following distinctions concerning material access. First, material access is differentiated as physical access and conditional access. Physical access is the entry to hardware, operational software, and services of computers, networks, and other digital technologies. Conditional access is the provisory entry to particular applications, programs, or contents of computers and networks. Increasingly, physical access is not enough. For particular applications, programs, and contents, not only special software and data carriers on CD or DVD are needed but also user names and passwords. The conditions are payment or a particular position, membership, or allowance. Conditional access becomes ever more important for material access. A currently popular marketing model of the computer, network, and peripheral equipment industries is to sell the equipment and connections as cheaply as possible so that the relatively expensive software, applications, and content may serve as the main sources of profit. Game computers and printers are cheap, but games and ink cartridges are expensive. So-called free Internet connections actually are e-commerce vehicles, advertising showers, and privacy sellers. On the Internet, customer relationship marketing is practiced by the “free” distribution of public domain software, freeware, and share ware with advertising, advanced services, and content with special value as the main sources of return.

In this book, the definition of physical access to digital technologies is mainly confined, for the sake of simplicity, to possessing or having entry to PCs and Internet connections. These can be realized at the following points of access:

Work

School

Public places: public institutions, such as libraries and community access centers, and commercial outlets, such as Internet cafés, hotel lobbies, and airport lounges.

Someone else’s house

Home

In transit: laptops, PDAs, mobile Internet

These points have been arranged according to the known diffusion of computers and networks in society. The evolution of this diffusion is a shift from work and school as the primary access points to home access. In the meantime, public places and the homes of neighbors, relatives, and friends have served as provisions for the disadvantaged. The last stage of this evolution is ubiquitous computing at work, at school, at home, and all public and mobile places. However, developing countries are still in the first stages of limited access at work and schools and the predominance of access in public places. For instance, the access points in Peru in 2001 were 83% Internet cafés (cabinas publicas), 18% workplaces, 17% schools, and only 11% homes. In the United States in 2001, primary access points were 43.6% at home, 19.6% at work, 11.9% at school, 5.8% at someone else’s house, 5.4% at libraries, and 0.6% at community centers (NTIA, 2002).

The next important distinction regarding physical access is the type of computer and the type of network connection. It goes without saying that access to a traditional home or game computer, an old PC, or a small computer in a PDA or other handheld device is not the same as access to a powerful, advanced, multimedia machine. The same goes for a 28 or 56 KB modem dial-up link to the Internet as compared to a broadband “always on” connection via cable, satellite, or DSL.

All these details about physical and conditional access, among them access conditions, access points, and types of hardware, software, and services available for particular users make a tremendous difference to the potential applications and to the level of inequality between users. I will refer to them repeatedly in the following description and analysis.

Widening and Narrowing Physical Access Gaps

In the last 10 years, we have been overwhelmed by statistics revealing large differences of physical access to computers and the Internet among different parts of the population and among different countries. Frequently, statistics show the differences between people in relation to their income, education, employment status, occupation, (geographical) place of residence, age, sex, and race or ethnicity. Most gaps have been wide, and increasingly so, between 1985 and 2000, as can be observed in the “gap pictures” of Figure 4.1, which summarizes trend data from the United States and the Netherlands. When these pictures were drawn, the point change over time, not the expansion rate, of the categorical values was taken as the point of departure. Arguing that the digital divide is shrinking, as the lowest categorical values are expanding at a higher rate than the highest values, is misleading (Martin, 2003). This happened in, among others, the latest NTIA reports (NTIA, 2002) I will give an example of how this is not true. When a developing country increases its Internet access rate from 0.1% to 2% while a developed country climbs from 20% to 40%, the expansion rate of the developing country is 10 times as high as that of the developed country. However, it is much more telling in this case that the point change of the developed country is much larger: Many more new Internet users have been added.

FIGURE 4.1 Gaps of Income, Education, Employment, Age and Ethnicity, USA 1984-2000.
Source: Computed from US Census Bureau data 1984, 1989, 1993, 1997, 1998, 2000, data also contained in NTIA, Falling Through the Net III, IV (1999, 2000).

Gaps of Income, Education, Employment and Age, The Netherlands 1985-1998.

Source: SCP, 2000.

Illustratie Gap of Income Netherlands 1985-1998Illustratie Gap of Income USA 1984-2000

Illustratie Gap of Education USA 1984-2000Illustratie Gap of Education Netherlands 1985-1998

Illustratie Gap of Employment Netherlands 1985-1998Illustratie Gap of Employment USA 1984-1997

Illustratie Gap of Age Netherlands 1985-1998Illustratie Gap of Age USA 1984-1998

Illustratie Gap of Ethnicity USA 1984-2000

To prevent misleading statistical presentations, the so-called odds ratios—that is, the chances of both the groups of users and nonusers gaining access—can be calculated on an equal basis. Recalculating the NTIA 2002 data to find these odds ratios, Martin showed that between 1998 and 2001, the decrease of American nonuse was largest for the richest households and that the poorest income category adopted the Internet more slowly than individuals from the richest income category (Martin, 2003, p. 5). This is the opposite of the claims made in A Nation Online (NTIA, 2002).

The question arises as to which factor is the most important in determining physical access. Income is mentioned most, although it strongly correlates with education, employment status, and occupation. The occasional multivariate analyses reveal that income is indeed the most important factor for physical access. For example, in a large-scale telephone survey of the Netherlands in 1998, it appeared that household income was the most important factor explaining possession of ICTs (computers, Internet connections, mobile phones, and other digital equipment), closely followed by education and with a remarkably high correlation with age and gender, all of them as separate (controlled) factors (de Haan, 2003; van Dijk & Hacker, 2003; van Dijk et al., 2000).

Most likely, income, as an explanatory factor for physical access, is more important for those living in poor countries and less important for inhabitants of rich countries. In poor, developing countries, it is a luxury to individually own expensive digital equipment. Here, physical access is mainly realized in public places or at work or school. Worldwide, income seems to be the most important factor explaining the possession of digital equipment (see the International Telecommunications Union [ITU] World Telecommunication Development Reports, notably ITU, 2002). In a survey conducted in 2000, income still appeared to be the most important factor in digital mobile telephone access and use in rich countries such as the United States; however, with Internet access and use, income came second after education (Katz & Rice, 2002).