Chapter 3: Big Participant Samples
This chapter covers the problems with current norms in the participants we recruit for psychology experiments, and how to solve some of these problems by taking a Big Data approach. Specifically, many psychology experiments use very restricted and similar samples – such as American college students. However, this sample differs greatly from the global adult population, in many ways described here. The chapter then discusses how we can move toward more representative groups using Big Data, while also highlighting caveats that we will never be able to make a perfect sample, and sometimes we may want to intentionally restrict the people we recruit. The chapter finishes with a look at the big ethical questions surrounding participant recruitment, and discussion on imbalances in the demographics of psychology researchers themselves.
- Demographic statistic resources
- How balanced are gender citations?
- The Ganzflicker effect
The United States Census makes a lot of demographic data publicly available.
The World Bank also makes a lot of world statistics publicly available.
Finally, Wikipedia is a great resource for collections of statistics for different countries.
You can use these tools to see the proportions of genders of the authors of the papers you cite. First, get the DOIs for the papers in your reference list using this website. Then, run the DOIs through the Gender Citation Balance Index tool.
This is an online experiment where what you see in the "Ganzflicker" will vary based on the population you belong to (your level of visual imagery). What do you see in the Ganzflicker?