Analysis of Unobtrusive Data Collected by You

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Once you have identified the set of texts, physical traces, or artifacts that you would like to analyze, the next step is to figure out how you’ll analyze them. This step requires that you determine your procedures for coding, understand the difference between manifest and latent content, and understand how to identify patterns across your coded data. We’ll begin by discussing procedures for coding.

You might recall being introduced to coding procedures in "Interviews: Qualitative and Quantitative Approaches", where we discussed the coding of qualitative interview data. While the coding procedures used for written documents obtained unobtrusively may resemble those used to code interview data, many sources of unobtrusive data differ dramatically from written documents or transcripts. What if your data are sculptures or worn paths, or perhaps kitchen utensils, as in the previously discussed example? The idea of conducting open coding and focused coding on these sources as you would for a written document sounds a little silly, not to mention impossible. So how do we begin to identify patterns across the sculptures or worn paths or utensils we wish to analyze? One option is to take field notes as we observe our data and then code patterns in those notes. Let’s say, for example, that we’d like to analyze kitchen utensils. Taking field notes might be a useful approach were we conducting observations of people actually using utensils in a documentary or on a television program. (Remember, if we’re observing people in person then our method is no longer unobtrusive.)

If rather than observing people in documentaries or television shows our data include a collection of actual utensils, note taking may not be the most effective way to record our observations. Instead, we could create a code sheet to record details about the utensils in our sample. A code sheet, sometimes referred to as a tally sheet in quantitative coding, is the instrument an unobtrusive researcher uses to record observations.

In the example of kitchen utensils, perhaps we’re interested in how utensils have changed over time. If we had access to sales records for utensils over the past 50 years, we could analyze the top-selling utensil for each year. To do so, we’d want to make some notes about each of the 50 utensils included in our sample. For each top-rated utensil, we might note its name, its purpose, and perhaps its price in current dollar amounts. We might also want to make some assessment about how easy or difficult it is to use or some other qualitative assessment about the utensil and its use or purpose. To rate the difficulty of use we could use a 5-point scale, with 1 being very easy to use and 5 being very difficult to use. We could even record other notes or observations about the utensils that may not occur to us until we actually see the utensils. Our code sheet might look something like the sample shown in "Table 11.2" . Note that the sample sheet contains columns only for 10 years’ worth of utensils. If you were to conduct this project, obviously you’d need to create a code sheet that allows you to record observations for each of the 50 items in your sample.

As you can see, our code sheet will contain both qualitative and quantitative data. Our “ease of use” rating is a quantitative assessment; we can therefore conduct some statistical analysis of the patterns here, perhaps noting the mean value on ease of use for each decade we’ve observed. We could do the same thing with the data collected in the row labeled Price, which is also quantitative. The final row of our sample code sheet, containing notes about our impressions of the utensils we observe, will contain qualitative data. We may conduct open and focused coding on these notes to identify patterns across those notes. In both cases, whether the data being coded are quantitative or qualitative, the aim is to identify patterns across the coded data.

The Purpose row in our sample code sheet provides an opportunity for assessing both manifest and latent content. Manifest content is the content we observe that is most apparent; it is the surface content. This is in contrast to latent content, which is less obvious. Latent content refers to the underlying meaning of the surface content we observe. In the example of utensil purpose, we might say a utensil’s manifest content is the stated purpose of the utensil. The latent content would be our assessment of what it means that a utensil with a particular purpose is top rated. Perhaps after coding the manifest content in this category we see some patterns that tell us something about the meanings of utensil purpose. Perhaps we conclude, based on the meanings of top-rated utensils across five decades, that the shift from an emphasis on utensils designed to facilitate entertaining in the 1960s to those designed to maximize efficiency and minimize time spent in the kitchen in the 1980s reflects a shift in how (and how much) people spend time in their homes.

Kathleen Denny’s (2011) 1 recent study of scouting manuals offers another excellent example of the differences between manifest and latent content. Denny compared Boy Scout and Girl Scout handbooks to understand gender socializing among scouts. By counting activity types described in the manuals, Denny learned from this manifest content that boys are offered more individual-based and more scientific activities while girls are offered more group-based and more artistic activities. Denny also analyzed the latent meaning of the messages that scouting handbooks portray about gender; she found that girls were encouraged to become “up-to-date traditional women” while boys were urged to adopt “an assertive heteronormative masculinity” (p. 27).