The scope and nature of non-standard work in the United States has attracted considerable attention from researchers in government, academia, the social sector, and the private sector. No single dataset, though, provides a comprehensive picture of the contemporary workforce. The largest and most reliable studies often cover only a limited set of questions; the language and definitions used across studies vary greatly, yielding widely different results; and the unique interests of some surveyors don’t lead to the most universally useful data.
On this site, we attempt to reconcile many studies—some of which appear contradictory—in order to generate insights about non-standard work. We rely most heavily on data that meet certain standards, outlined below. We also believe, though, 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 non-standard workers. This includes attempts to measure the size and composition of the non-standard workforce and/or to describe the experiences of non-traditional workers. 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. Where applicable, Data Hub authors must have access to survey instrument or interview schedule language, either through public availability or by request. |
| 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. |