While the citizenship/immigrant status of students or others in Science, Technology, Engineering and Mathematics (STEM) workforce development projects/programs may not be obvious to evaluators, it is an important part of context and may have an impact on the quality of the evaluation. Citizenship status may have an impact on access to employment, schooling, and -- for people with disabilities -- access to accommodations and services.1 If a participant or a family member does not have a legal citizenship status, the impact may be more severe- deportation or incarceration.
Asking citizenship status may cause some participants to refuse to provide data and others to provide inaccurate data. If citizenship status is asked, the evaluator should make it very clear why the information is being requested, how it will be used, and who will have access to it. For the protection of human subjects, Institutional Review Boards (IRBs) may request additional security for the protection of the confidentiality of that information.
Citizenship status can be complex. For example, the federal definition of tribal citizenship for Native Americans often differs from the definitions that certain tribes have for citizenship. In a time of changing immigration policies, citizenship status can even be uncertain. Asking about citizenship status can be very sensitive, especially when a participant or a family member may have uncertain or questionable status.
Citizenship status may have an impact on tracking data as well. Participants who themselves have uncertain or questionable citizenship status or who have family members with such a status may not be willing to provide accurate contact information for follow-up. However, questionable or uncertain citizenship status may also pressure participants to participate in an evaluation and give the “right” responses. Evaluators need to do their best to make sure that participant involvement in the evaluation is truly voluntary and that their responses are free from pressure.
Citizenship status can interact with other demographic variables including gender, race, and ethnicity. These variables, as appropriate, need to be included in the data analysis.
For more about the role of context in evaluation, click here