Internet Use in the Parochial Realm
The disparity between those who use the internet and who do not and between those who are able to attain the internet “the haves” versus those who cannot “the have nots” is often discussed in both communication research and social commentary. The two studies by Hampton et al examine the impact that participation in neighborhood email lists has upon the networks of neighborhood members, both of those who do enroll in the neighborhood internet program and those who do not. Many researchers, such as Baym et al, have discussed effect that the internet can have upon long-distance social ties. However, Hampton takes an alternate approach, researching the influence that the internet can have upon neighborhood ties. Hampton’s two studies have many similar research concepts, particularly in the accessibility of neighbors, and some similarities in underlying methodology. Neighborhood members in both studies were given access to a neighborhood email list and were probed using surveys about their recognition of neighbors by name from a neighborhood roster and about their interactions with their neighbors. However, there are also a few key methodological differences between the two studies. One difference is the method in which the two studies asked participants to describe their closeness to their neighbors. The first study only asked residents to indicate whether they recognized, talked to or visited their neighbors, using this as a means of perceiving closeness. The later study instead asked people to identify how close they felt to neighbors, ranking them close, moderately close or not close, along with indicating whether they had in-person interactions, talked on the phone or exchanged email with them. This difference is interesting in that in the first study, the researchers used types of interaction between neighbors to infer how close neighbors were versus in the second study, they actually asked people to report how close they were to these people. Whether or not someone feels “close” to someone else depends greatly upon personal views and interpretation of the term, which is similar to the problem of the word “discuss” and “important matters” in McPherson et al’s research and of the term “significant” as relating to social interactions in Baym et al’s research. Therefore, the measure of closeness in these two studies differs because of self-reporting in the later study versus inferences by the researcher in terms of closeness in the first study.
Another methodological difference between his two studies lies in their samples. The 2003 study only examines one neighborhood in Toronto that was largely homogenous in socio-economic status (middle class), marital status (90% married), employment status (88% employed full time) and education (most had university degrees). This sample provides a limitation to the research, as this sample is not generalizable to the larger population due to its homogeneity on the variety of above characteristics. Also, since only one neighborhood was examined, and an unusual one at that due to its wired nature, the results cannot be generalized to the larger population of Canadians or Americans very much, if at all. However, Hampton et al’s second study somewhat corrects this limitation, in that while it uses much of the same methodology, the researchers examine not one, but four communities. Also, these four neighborhoods were carefully selected to represent different stages in the life cycle, which is a strength of the research, as its results are more applicable to the larger, more diverse population. Despite this strength of multiple, differing neighborhoods, there are also a few factors that function to bias the second study. Firstly, all four neighborhoods were in the Boston area, which presents a bias to the research because they are not representative of the entire country since they are all in close proximity in one location of the country. Also, since these neighborhoods are all near one of the biggest cities in America, their inhabitants probably differ from more rural neighborhoods. Also, the neighborhoods were primarily Caucasian, and the gated community had no racial variation whatsoever. This ethnic homogeneity also biases the results, since Caucasians have been shown to differ from minority populations significantly in many respects, which makes this survey have low representativeness to the rest of the country. Also, the response rate of the study was extremely low, with the response rate over three years estimated to be 26%, and only 34% of participants completed all three annual surveys. Though attrition is a common problem in longitudinal studies, this study’s attrition rate is rather high, which biases the results as people who respond and do not drop out are different from those who do not respond and drop out.
Servon and Pinkett’s paper discusses the digital divide and its impact upon society. They believe that although access to information technology is a main problem, it is not the only dimension of the digital divide issue, as concerns revolving around IT literacy, particularly as it relates to job skills, and content are also important factors in the digital divide. Though these additional dimensions are thought provoking, I do not really agree with their argument about how content contributes to the digital divide. The authors state that when disadvantaged groups access the internet, the kind of information that they are looking for, about their lives, cultures and communities “does not exist”. I think that this statement is overly strong and generalized, because it seems improbable that such information simply is not available at all with the millions of web pages on the internet. They also state that when it does exist, disadvantaged groups lack the skills to find it. The researchers assert that adult internet users seek information about housing and jobs in their communities and that few sites have this information and it is difficult to find. These statements seem unreasonable to me, since there are many sites devoted to job hunting, like Monster.com and CareerBuilder, and sites that help people find housing, such as Craigslist. Though these sites may perhaps have grown in number since the paper was written, I still don’t find this claim to be very accurate. Also, the researchers state that the internet is shaped and content is produced for and by white middle and upper income males, which also seems extreme and generalized, as much content on the internet is not created for or by this subset of the population. Also, much of their statements are not supported by empirical data, such as those stated above, relying instead upon assumptions, opinions or observations. The researchers state that it is “reasonable to assume” that computer technology centers promote the creation of weak ties among users. Though weak ties are much discussed in internet research, such as in both of Hampton’s neighborhood studies, the authors do not support their assumption with empirical evidence, merely using observations of CTC administrators to back up this assumption. The researchers also make other broad statements, such as about the impact of CTCs upon the development of job skills, which are also not supported with empirical research. In order to make their argument stronger, these researchers should study CTCs empirically to provide numerical evidence to back up their claims.
Questions:
Do CTCs really impact the social networks of users, and if so, how?
Do you think that studying neighborhoods in rural communities would have produced different results than those found with the urban/suburban areas?