Summary: The number of distinct locations of immigrant-serving organizations per 10,000 non-citizen immigrants.
Data Source(s): GuideStar Pro Database; U.S. Census Bureau, 2019 American Community Survey 5-year Summary File.
Universe: All 501(c)(3) Form 990 and 990EZ organizations in California identified as serving immigrants (numerator) and all non-citizen immigrants (denominator).
Methods: The methodology we implemented in 2022 departs from our original (2019) methodology due to two major reasons. First, the data product that we used in the original methodology (GuideStar Research Fundamentals PLUS) was discontinued. For the 2022 update, we relied on the GuideStar Pro Plus database which has a significantly different data structure. Second, we updated our methodology to incorporate a broader definition of immigrant-serving organization that is more in line with current scholarly thinking.
Our original approach implemented in 2019 was top-down and involved filtering down to immigrant-serving organizations in California from a complete 2016 dataset of all nonprofit organizations in the U.S. that filed Form 990. Due to changes in GuideStar’s data product, our new bottom-up approach uses keywords and search criteria to build up a dataset of immigrant-serving organizations in California. One important difference to note is that the GuideStar Pro Database allows users to search for Form 990-EZ nonprofits (annual gross receipts between $50,000 and $200,000) in addition to Form 990 nonprofits (annual gross receipts more than $200,000). As a result, we were able to capture significantly more small-to-mid size nonprofit organizations during the update.
To build up our dataset, we used a series of search criteria to find potential immigrant serving organizations. Our basic search setting limited the search geography to California and excluded nonprofit organizations with revoked status in 2021. For the initial step, we used two keywords, refugee and immigrant, and found 1,806 organizations. Next, we added 662 organizations with their subject area labeled as immigrant service to the dataset. Current scholarly research on immigrant-serving organizations uses an expansive understanding of immigrant serving. Even though an organization might not necessarily describe or advertise itself as immigrant serving (e.g., a nonprofit hospital), an organization can still be considered as immigrant serving if it has a substantial number of immigrant clients. To adapt this idea into our methodology, we added organizations that served ethnic groups to our dataset. We included all ethnic groups (Middle Eastern, Latin American, European, Asian, African, and multiracial) except for Indigenous groups (Native American, Native Hawaiian, Alaska Natives, etc.). This added 1,633 organization to the dataset. After removing duplicate records that appeared during the searches, we built a dataset containing 2,716 potential immigrant-serving organizations in California.
We then qualitatively reviewed and evaluated the organizations to ensure that all organizations in the final dataset were actually immigrant serving. Our qualitative criteria included mission statement, program description, service offered, language offered, and scope of work. For mission statement, program description, and service offered, we looked for indications that an organization provided services (e.g., legal service) to immigrants. Additionally, following the expansive understanding of immigrant serving, we also included organization that performed arts, culture, and advocacy-based work related to immigrants. Lastly, we included local, faith-based organizations to highlight the important role that religion plays in immigrant communities. For scope of work, we excluded all organizations that focused on international work with the one exception of organizations that worked in the Tijuana, Mexico region. These organizations work to serve encamped migrants and refugees looking to enter the U.S. As noted in our original methodology, one major shortcoming of the GuideStar data is the one-to-one organization-location match even if it an organization has multiple offices. To account for the shortcoming, we conducted internet searches on each Form 990 organization (as they tend to be larger and more likely to operate in multiple locations) and recorded the number of different locations along with their respective addresses. In the end, our final dataset contained 2,675 records and 1,633 unique immigrant-serving nonprofit organizations.
To aggregate the data to the various levels of geography for which data are reported, we first geocoded all addresses using Google API and a Google Apps script. Then, we used ArcGIS Pro and spatially joined the geocoded locations into CIDP geographies (state, county, sub-county, and city or place). We then matched in data from the 2019 American Community Survey 5-year Summary File on the number of non-citizen immigrants to calculate the number of immigrant-serving organizations per 10,000 non-citizen immigrants. Lastly, we set the measure to missing for geographies with fewer than 1,500 non-citizen immigrants and fewer than 2 organizations. This filter reduces large spikes in the data caused by a small denominator that can lead to inconsistent geographic comparisons.