The gig economy has gotten a lot of attention from researchers in government, academia, think tanks, and the private sector. No single dataset, though, provides a comprehensive picture of today's workforce. The largest and most reliable studies ask limited questions; definitions used vary greatly; and some datasets are tailored to researchers' specific interests.
On this site, we attempt to reconcile many studies—some of which appear contradictory—in order to generate insights about the gig economy and work today. We rely most heavily on data that meet certain standards, outlined below. We also believe that we can learn from exploratory and non-representative research that explores critical questions and areas that have not been covered by other sources, and draw from this research when we lack more rigorous data.
In applying these criteria, we do not use a singular definition of “gig work.” Instead, we use it as a general term and then look deeply at how others describe and define it (often using terms such as gig work, alternative work arrangements, independent contracting, or 1099 work).
| Criteria for Study Inclusion | |
|---|---|
| Content |
We are interested in research that directly addresses gig or non-standard workers. This includes attempts to measure the number of gig/non-standard workers and/or to describe their experiences. Research must present original data (survey, interviews, employment records, etc.) or contain original analysis of public datasets (CPS, GSS, tax data, etc.). |
| Definition | Research must include a clear, internally consistent definition of non-standard or gig work. |
| Measures | All measures must be clearly identified and correspond to the definition used. |
| Methods |
Research must state sampling and recruitment methods, and present number of responses and response rate, where applicable. In synthesizing estimates of the non-traditional workforce, we prioritize data that relies on a probability sample and documents attempts to increase representativeness. Methods of analysis must be clear and replicable. |
| Sponsorship | Funding source(s) of study must be identified. |