The internet is an indispensable aspect of modern society. It facilitates long distance communication, access to information, health care interventions, as well as multiple opportunities for social participation. Despite increasing pervasiveness of this technology, persistent inequalities exist in who has access to the internet. In particular, older adults lag behind in having internet access, thus putting them at risk for social exclusion. In order to gain a better understanding about the determinants of this grey digital divide, the current study contrasts influencing factors of internet access, comparing samples from 2002 to 2014 across age groups (40 to 54 years, 55 to 69 years and 70 to 85 years) using data from the German Ageing Survey (DEAS). Logistic regression confirmed that the likelihood of having internet access was lower with higher age at both time points. However, the percentages of people with internet access grew primarily in the middle and older age groups between 2002 and 2014. Furthermore, being male and having a higher education were both associated with greater odds of internet access. However, gender and education differences in internet access were significantly less pronounced in 2014 in contrast to 2002. Finally, both greater income and cognitive ability were associated with greater odds of internet access, while providing care for a grandchild was significantly associated with internet access only among the oldest age group. In an attempt towards bridging the grey digital divide, the current study serves as a basis for identifying groups mostly affected by this increasingly important form of social inequality.
Contrasting influencing factors of internet access across age groups may only be a first step for uncovering potential routes to bridge the grey digital divide. As the diffusion model assumes, technologies slowly spread from homogenous groups of early users to adjacent subgroups in the population (Peres et al. 2010). Thus, examining whether or not factors influencing internet access have changed in importance over time may facilitate a greater understanding of mechanisms underlying the spread of internet access. For example, existing social disparities are reflected and possibly reinforced within the digital divide (Robinson et al. 2015). In this sense, previous research has found a generational explanation of the digital divide, in which different birth cohorts were exposed to the internet at different points in their life course, which may have an even more important influence on the adoption of this technology than the exclusive effects of age itself (Gilleard and Higgs 2008). Furthermore, as argued above, old age can be considered a time of elevated risk, in which pre-existing socio-demographic differences exacerbate the grey divide in access to the internet. Thus, it is important to examine historical differences in socio-demographic factors of internet access in different age groups. A specific emphasis in this regard will be placed on the influence of financial factors. Overall, the longer technologies are in use, and they tend to decrease in cost as prices usually show a diffusion-based pattern of firstly increasing and then decreasing over a longer time span (Mahajan et al. 1993). Thus, it seems important to investigate whether or not the limiting factor of financial assets has been decreasing in recent years. There have been a number of initiatives working towards increasing the user friendliness of various technologies used to access the internet (de Jong and Lentz 2006; Jiang et al. 2000; Nykanen 2008; Wimmer and Holler 2002). Therefore, cognitive ability may become less important for internet access at later time points.
Generally, as previously mentioned, the digital divide can be defined on various levels; starting with internet access and general use marking a first digital divide as investigated in the current study, but going further into subsequent divides such as specific types or reasons for internet use dependent on skills and digital literacy. The current study solely refers to the first-level digital divide by examining internet access. Although our study found that this divide still exists, it also shows that societal differences in internet access have become smaller over time. As the first digital divide continues to shrink, future research examining specific types of internet use as well as related skills becomes indispensable. Looking at current developments such as e-government (Gasova and Stofkova 2017), the increasing popularity of extracting health information from the internet (Hong and Cho 2016) or making use of online consulting (Marshall et al. 2018), the internet becomes a necessity in order to stay an engaged, informed and a self-determined citizen. Accordingly, inclusiveness by bridging the digital divide is one of the main goals adopted by the Connect 2020 Agenda of the International Telecommunication Union (ITU), the United Nations specialized agency for ICTs (United Nations 2014). Nevertheless, some other forms of internet use such as entertainment may be of less interest in terms of social participation but still very important for overall well-being. Thus, identifying who uses the internet and for what specific purposes is important in order to target the overcoming of social disparities.
In summary, even though there is room for further research on determinants and remedies of the grey digital divide, the current study determined groups mostly affected by this divide. These findings might serve as a starting point towards further identifying possible resources for interventions tailored for specific vulnerable subgroups.
To download a copy using Internet Explorer, right click on the link. Left click on Save target as... in the dialog box. A Save As window will appear. Save the file to the directory and folder of your choice.
When an export target is set to Unreal Engine or Maya and you click the Export button, if an open instance of either of them is running, the MetaHuman assets you've previously downloaded will be sent directly to that instance. A pop-up message will indicate the status of the export process. The example below shows a successful export to an open and running instance of Unreal Engine.
Standard, easily accessible, test targets have long served the field of color imaging as a foundation for comparison of the performance of various imaging systems and algorithms and the open and meaningful exchange of research results. This website details the creation and application of a new digital color test target useful for research and development of color imaging systems. The target has several advantages over previous types of targets that include spatial resolution, dynamic range, spectral resolution, metameric properties, lack of noise, and continuous tonal variations. All these features can be important for visual assessment, computational analysis, and colorimetric evaluation. This target, known as METACOW, is freely available to all performing research in color imaging.
METACOW is basically a very large (4200 x 6000 pixel) full-spectral image. It is rendered at 5nm increments, between 380 to 760...and is thus about 3gigs in size. It is designed such that both halves of each "cow" appear to match when illuminated with CIE D65, and viewed with the CIE 1931 Standard Observer. This is the example shown above. Each half of the cow is actually maximally metameric with itself. The left half of each cow has the spectral reflectance of the GretagMacbeth Color Checker, while the right half is a Metameric black that has been specially calculated to maximize color difference under Illuminant A. This type of target is designed to test both illumination and spectral responsivities for digital imaging solutions. Examples of illuminant (left) and observer (right) metamerism are shown below.
The image on the top was rendered under Illuminant A with the CIE 2 degree Observer, and then converted to display sRGB using the CIECAT02 chromatic adaptation transform. The image on the bottom was rendered under D65 with actual digital camera spectral sensitivities. The metameric nature of the METACOW target should be readily apparent from these examples.
The METACOW test target available for download, for use in imaging system design and evaluation. We ask only that you credit the Munsell Color Science Laboratory in any publications. Note that it is a large image; make sure you are on a decent internet connection for the download. Included in the files are: many GB of fullsize METACOW Glory, Smaller and Easier to Manage MINIMETACOW, Matlab Source Code for Reading and Rendering METACOW, and Much More. Or you can download a smaller version (420x600x77).Small METACOW ImagesLarge METACOW Images (500MB file!) 2b1af7f3a8