December 07, 2021

Who Do You Want to Learn About?

Author photoBy Karen Sternheimer

One of the most basic question any social science researcher needs to consider is who we want to learn more about.

How about everyone? In most cases, that’s not practical. The U.S. Census, which by law must count everyone, is not really able to do that. With each decennial census, there is an undercount, or a shortfall in the ability to count every resident. A recent report from the Urban Institute predicted a .5 percent undercount of the total population (for more information, see the Population Resource Bureau’s (PRB) explanation of how undercounts and overcounts are calculated).

Learning about everyone is expensive. Estimates for the 2020 Census suggest that it cost $14.2 billion, which is actually less than the previous estimate of $15.6 billion. What about a nationally representative sample of much fewer people?

Even if you did want to sample a smaller portion of the population, it is often hard to reach people yourself through the mail or by phone (thanks, robo-spammers!). According to a 2019 Pew Research Center report, the response rate for phone surveys has fallen to 6 percent—meaning 94 percent won’t answer their phones or participate.

There are some exceptions to finding information about everyone, or at least, nearly everyone: use an existing data source. Federally collected data sources, like the U.S. Census, American Community Survey, Current Population Survey, and the Survey of Income and Program Participation, are just a few examples of survey data that are publicly available and widely used by think tanks and academic researchers.

Other countries’ governments may also have similar data available for analysis; the PRB and the United Nations’ databases are good places to start. Pew Research Center also conducts survey research around the world, as this video details.

While you might be able to get a lot of information from these sources, what if they didn’t gather information on the topics you are interested in learning more about? Or what if you want to gather information about a very specific group that is not delineated in one of these or another pre-existing dataset?

Well, you’re on your own then, but that isn’t necessarily a bad thing. While I have never used Amazon Mechanical Turk (often abbreviated as MTurk) myself, some colleagues of mine find it very useful. For relatively little money, users can get participants to complete surveys in far-flung places that they might not be able to access otherwise. The data gathered are not representative of the entire population, but instead relies on people who have internet access and are willing to be paid very little to take surveys.

This has raised ethical issues too. As technology writer and political scientist Alexandra Samuel wrote in 2018:

To my mind, it is this economic injustice—rather than methodological concerns—that should be of greatest concern to would-be MTurk researchers. Indeed, the exploitation of MTurk workers is already drawing scrutiny in a way that reflects poorly on the academic community. While academics may lament shrinking research funding and increased competition for grants, neither funding scarcity nor the importance of academic research are truly acceptable excuses for paying survey-takers rates that are often a tiny fraction of minimum wage.

So if you can’t find the people you want to learn more about in previously collected data, and you’re not comfortable using MTurk, what options do we have? For very specific or hard-to-reach groups, using convenience sampling might be a good option.

Do we want to learn more about people active in animal rights movements? Members of a small religious sect? People who identify as pansexual? Such specific interests mean you will probably need to look for someone in one of these categories and build upon a small number of connections to find participants. This won’t yield a representative sample that can be generalized to the entire population of people in this group, but that doesn’t negate the importance of what you might learn through your research.

Figuring out who you want to learn about will help you formulate a research question and choose an appropriate method. Knowing the “who” of research can make the rest of the process clearer.

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