Purpose. The Survey of Graduate Students and Postdoctorates in Science and Engineering (GSS) is an annual census of all academic institutions in the United States and its territories (Guam and Puerto Rico) granting research-based master’s degrees or doctorates in science, engineering, and selected health (SEH) fields as of the fall of the survey year. Sponsored by the National Center for Science and Engineering Statistics (NCSES) within the National Science Foundation (NSF) and by the National Institutes of Health (NIH), the GSS collects counts of graduate students, postdoctoral researchers (postdocs), and doctorate-holding nonfaculty researchers (NFRs) at these institutions by field, demographic characteristics, and other characteristics, such as source and mechanism of financial support. Results are used to assess shifts in graduate enrollment, shifts in postdoc and NFR appointments, and trends in financial support.

Data collection authority. The information collected by the GSS is solicited under the authority of the National Science Foundation Act of 1950, as amended, and the America COMPETES Reauthorization Act of 2010. The Office of Management and Budget (OMB) control number is 3145-0062 and expires on 31 August 2023.

Survey contractor. RTI International.

Survey sponsors. NCSES and NIH.

Frequency. Annual.

Initial survey year. 1966.

Reference period. Fall 2022.

Response unit. Organizational units (e.g., academic departments, degree-granting programs, university-affiliated research centers, and health care facilities) in academic institutions.

Sample or census. Census.

Population size. A total of 22,519 organizational units at 690 academic institutions.

Sample size. Not applicable.

Target population. The survey target population is all academic institutions in the United States and its territories (Guam and Puerto Rico) that grant research-based master’s or doctorate degrees in SEH fields. A research-based graduate degree program requires the training in, and conducting of, independent research as part of the curriculum. SEH fields are defined using the Integrated Postsecondary Education Data System (IPEDS) Classification of Instructional Programs (CIP) codes. This population includes branch campuses, affiliated research centers and health facilities, and separately organized components, such as medical or dental schools, schools of nursing, and schools of public health.

In 2022, the survey universe included 690 institutions with 775 schools and 22,519 organizational units. There were 502 schools and 20,698 units within 417 institutions awarding master’s or doctoral degrees and 273 schools and 1,821 units within 273 institutions that only award master’s degrees. Data were collected at the organizational-unit level. Detailed information on the changes to the survey universe and final number of institutions, schools, and units is provided in table A-1 through table A-5b.

Sampling frame. The total universe in 2022 included 22,519 units at 690 academic institutions in the United States that granted research-based master’s degrees or doctorates in SEH fields. Eligible academic institutions are identified primarily through IPEDS.

Sample design. The GSS is a census.

Data collection. The survey data are collected through coordinators at eligible institutions. Coordinators are assigned by their institution and are responsible for identifying all GSS-eligible units, collecting the requested data, and submitting the data to the survey contractor. GSS eligibility for SEH units is determined by the CIP code associated with the organizational unit. The GSS maintains a crosswalk between CIP codes and eligible SEH fields.

Coordinators query their institutional databases and report data through a file upload. Those unable to provide file uploads can manually enter data into the GSS Web survey. In cases where coordinators are unable to obtain the requested data, coordinators may enlist the aid of others (unit respondents) in their reporting activity. Unit respondents are most commonly used to report detailed financial support data. Institutions may assign multiple coordinators. For example, an institution may have one coordinator for each school within the institution or may have separate coordinators for graduate student data and for postdoc and NFR data. When a new coordinator is needed, the president’s office at the institution is asked to designate as coordinator the person most knowledgeable about the graduate student or postdoc data.

Once coordinators are confirmed, they are provided access to the GSS Web survey. On request, hard copies of the survey worksheets and GSS-eligible code lists are also e-mailed to each coordinator as reference. Data are collected at the organizational-unit level (e.g., departments, degree-granting programs, research centers, and health facilities) and include field of study, demographic characteristics, and funding information for graduate students and postdocs.

Mode. Electronic data interchange is the primary mode of data submission. Coordinators unable to use this method could manually enter their data in the GSS Web survey.

Response rates. Response rates are calculated based on responses to the survey’s various data collection grids (graduate student and postdoc counts, by ethnicity and race; full-time graduate student and postdoc counts, by primary source or mechanism of support; counts of postdocs, by type of doctoral degree and primary mechanism of support; counts of postdocs, by type of doctoral degree and citizenship; counts of postdocs, by origin of doctoral degree; and counts of NFRs, by type of doctoral degree and sex).

• Unit response. In 2022, the GSS received complete responses from 19,112 of the 22,519 eligible organizational units (84.9%). An additional 3,115 organizational units (13.8%) were partial respondents. The remaining 292 organizational units (1.3%) were nonrespondents.
• School response. Of the 775 eligible schools, 742 schools (95.7%) were complete respondents, 4 schools (0.5%) were partial respondents, and 29 schools (3.7%) were nonrespondents.
• Institutional response. Institutional response rates were calculated using the same criteria for schools. Of the 690 eligible institutions, 660 institutions (95.7%) were complete respondents, 1 institution (0.1%) was a partial respondent, and 29 institutions (4.2%) were nonrespondents.

Data editing. Data quality is ensured by interactive edit checks built into the Web survey and by a comprehensive review after the coordinator submits the data. Data collection grids in the Web survey are prefilled with zeros. Respondents are asked to mark a checkbox if the unit does not have eligible data to report. If uploaded data for a unit only contain one type of student (e.g., the unit has master’s students but no doctoral students), the appropriate checkbox indicating no students to report is auto filled by the system for the relevant grid. Grids with a marked checkbox contributed to a complete response for the unit. Grids with unchanged, prefilled zeros and an unmarked checkbox disqualified the unit from complete response status.

The Web survey contains edit checks to verify that the data entered are internally consistent and within an expected range, often based on the respondent’s prior-year data. In 2017, aggregate school-level edit checks were introduced, replacing unit-level checks. Reported aggregate school-level data are compared to the previous year for part-time, full-time, and first-time, full-time students as well as for postdoc and NFR counts. The survey contractor reviews all data submitted by institutions to ensure that data fields are complete and internally consistent. The data collection team conducts a post-submission data review, whereby coordinators are asked to explain the discrepancy whenever counts differ substantially from those of the previous year. Follow-up with coordinators is also conducted when counts remain identical to the previous year and when there are notable changes to a school’s unit list, including unit additions and deletions, changes to the highest-degree-granted status, GSS code, or unit name.

On the basis of follow-up contacts, necessary revisions are made directly in the Web survey by the coordinator, unit respondents, or the survey contractor at the direction of the coordinator. See section “Survey Quality Measures” below for a discussion of the types of measurement error detected in the data review and follow-up process.

Imputation. The 2022 GSS collected 543 data items related to enrollment and financial support for master’s and doctoral full-time and part-time students, postdocs, and NFRs. Of the 543 data items collected in the GSS, the item imputation rates ranged from 1.23% to 5.74%. All missing data were imputed.

Different imputation techniques were used for units with and for those without comparable historical data. For units missing a key total (total full-time master’s, full-time doctoral, part-time master’s, and part-time doctoral students; total postdocs; or total NFRs) with at least 1 year of qualified historical data, a carry-forward imputation method was used. Inflation factors were calculated for the six key totals to account for year-to-year change. The previous year’s key totals were carried forward as the imputed values for the current year’s key totals and imputed according to the previous year’s proportions.

For units that reported totals but no details, details were imputed according to the prior distribution if qualified historical details were available. Otherwise, a nearest-neighbor imputation method was used. In this method, a donor unit that was “nearest” to the unit whose data were being imputed (imputee) was identified among all responding units having similar characteristics as the imputee (e.g., having the same GSS code for program fields and offering a doctoral degree).

Similarly, when postdoc or NFR details were imputed, the total number of postdocs or NFRs, respectively, was used to choose the nearest neighbor. If the postdoc or NFR total was missing, the graduate student totals were used to select the nearest neighbor to impute the postdoc or NFR variables. If either the postdoc or NFR key total (or both) was missing, other available key totals were used to select the nearest neighbor to impute the data. The same donor was then used to impute the details corresponding to the imputed key totals.

For institutions or schools that did not respond, all data at the unit level were imputed. For these institutions or schools, if prior unit-level data were available, counts were carried forward; if no prior data were available, then the nearest-neighbor imputation method was used.

Detailed information on the institutions, schools, units, fields, response rates, imputation rates, and a crosswalk between the 2022 CIP codes and the GSS codes are provided in 17 technical tables for the 2022 GSS, which include three tables with information on the taxonomy change.

Weighting. Not applicable.

Variance estimation. Not applicable.

Sampling error. Not applicable because the GSS is a census.

Coverage error. Due to the availability of comprehensive lists of the master’s- and doctorate-granting institutions in the United States and the high level of participation in the survey of the eligible institutions, coverage error is minimal. The universe of higher education institutions is reviewed annually to identify potentially eligible institutions. Sources for this review include IPEDS, the Carnegie Classification of Institutions of Higher Education, the Higher Education Directory, the NCSES Higher Education Research and Development Survey, and professional association membership lists.

Nonresponse error. The GSS typically has high response rates. In 2022, 98.7% of units provided complete or partial data and the overall institutional response rate was 95.8%. Of the 543 data items collected in the GSS, the item imputation rates ranged from 1.23% to 5.74%. All missing data are imputed.

Measurement error. The GSS is subject to measurement error that arises when variables of interest cannot be measured accurately or precisely. Review of the data, cognitive interviews, usability tests, pilot tests, site visits, and other methodological activities with the institutions have pointed to several possible sources of measurement error. The types of measurement errors listed below are believed to have a minimal impact on data quality.

• Double counting. Anecdotal evidence indicates some misreporting may occur when an institution has more than one coordinator or offers joint programs. To reduce double counting, facilitate communication, and allow sharing of reported data, a screen in the Web survey provides names and contact information for all coordinators at the institution. Interactive and post-submission checks are also used to confirm that similarly named units within institutions are distinct eligible units. The introduction of data uploads has minimized this type of measurement error. This issue is now flagged for fewer than 0.5% of units reported to the GSS annually.
• Inclusion of practitioner degrees. Graduate students working toward practitioner degrees, particularly in health fields with explicit exclusions, may sometimes be overreported. Starting with the 2007 survey cycle, survey materials indicated that students should be excluded from the counts if they are pursuing DDS or MD degrees or master’s and certain other degrees in specified fields. During the imputation process—and to be conservative in the absence of other information—new units that were suspected of having reported graduate students in excluded degree-field programs based on the GSS code were set to having zero graduate students. In the 2011 survey cycle, checks were built into the Web survey to remind respondents to exclude students pursuing practitioner-based degrees. The 2017 redesign included a requirement that coordinators confirm via a pop-up dialog that they excluded practitioner degrees from the data provided in their upload files. Prior to the introduction of this pop-up dialog, it was more common to mistakenly include graduate students earning practitioner degrees. However, since the redesign in 2017, fewer than 0.5% of units that report doctoral students mistakenly included students pursuing practitioner degrees.
• Difficulty in reporting source and mechanism of support. Feedback from respondents and methodological research indicates that financial support data are often difficult for respondents to report. The information may not be stored in one centralized database; financial support may not always be channeled through the institution (e.g., self-support); and foreign sources of support may not always be known. Respondents may also have difficulty categorizing financial information by field, such as when a student is enrolled in one unit but receives support from another. Therefore, these data may be more prone to measurement error than other survey data items. Finally, institutions define mechanisms of support differently (e.g., fellowships vs. traineeships) and may report individuals according to the institution’s definition rather than that provided by the GSS. Beginning with the 2010 survey, the postdoc grids include “unknown” categories. Nonresponse rates for source and mechanism of support items typically range between 1% to 7% for graduate students and 4% to 5% for postdocs.
• Difficulty in reporting postdocs and NFRs. Many respondents indicate in the Web survey that they are unable to provide data on their units’ postdocs or NFRs because they do not know all of the units that employ postdocs and NFRs. Starting with the 2010 survey cycle, schools were given the option of appointing a separate postdoc coordinator who may be more knowledgeable about a school’s postdocs or NFRs to provide these data. In 2018, coordinators were given the ability to indicate that they had postdocs or NFRs but were unable to report them. The percentage of coordinators that select this option is generally less than 2% for postdoc data and 3% for NFR data since the option was added in 2018.

Changes in survey coverage and population.

• Eligibility and fields of study.

2020: Starting in GSS 2020, the list of GSS-eligible CIP codes was updated to align with the revised 2020 CIP list and NCSES Taxonomy of Disciplines (TOD). Since most coordinators report graduate student data using CIP, it was important that GSS update the taxonomy to include the new CIP codes on the same timeline as IPEDS. As part of this update, new CIP codes were added, some CIP codes were changed, and a small number of CIP codes were removed. Most of the changes in CIP eligibility were made to ensure that the implementation of the new CIP codes included programs that were GSS-eligible and likely were being reported (based on unit names). The GSS codes of data science and data analytics and of medical clinical sciences were added for reporting new CIP codes in these fields. Due to changes in the CIP and TOD, veterinary biomedical and clinical sciences were moved from other health to agricultural sciences (renamed agricultural and veterinary sciences). To improve alignment with the TOD, human development moved from social sciences to psychology.

In addition to the adjustments made due to the changes in CIP and TOD, the GSS made additional changes based on data reporting patterns that emerged due to the 2017 redesign. Generally, these changes created more detailed fields out of larger GSS codes or reorganized existing codes to align with current enrollment patterns. Broad fields were added to engineering for the first time. In some cases, GSS codes with a small number of graduate students were combined for reporting purposes. For more information on these changes, see GSS 2020: tables A-17, A-18a, and A-18b.

2017: The list of GSS-eligible disciplinary fields was updated in 2017 to align with the TOD. Among the major changes in the update: several fields became ineligible—architecture, communications, and public administration; portions of nutrition and of family and consumer sciences and human sciences also became ineligible. Several fields changed names. A new broad field titled natural resources and conservation was split from agricultural sciences. Computer sciences was split into three fields, and the biological and biomedical sciences field was reorganized. The taxonomy changes resulted in previously reported units being split across separate GSS codes or moving between codes or broad fields. For more information on the 2017 taxonomy updates, see GSS 2017: table A-1.

2014: The survey frame was updated following a comprehensive frame evaluation study. The study identified potentially eligible but not previously surveyed academic institutions in the United States with master’s- or doctorate-granting programs in SEH. Eligible units at 151 newly eligible institutions were added, and 2 private, for-profit institutions offering mostly practitioner-based graduate degrees were determined to be ineligible. An additional 4 institutions dropped out of the data collection in 2014 because they no longer grant graduate degrees in SEH fields, 2 merged with previously eligible institutions, and 1 began reporting data under another institution. As a result, the total number of institutions included in the GSS increased from 564 in 2013 to 706 in 2014. The total net increase in the number of GSS-eligible units was 826, rising to 14,845 in 2014 from 14,019 in 2013. See GSS 2014: table A-1.

For more information on the survey frame update, see the Special Report Assessing the Impact of Frame Changes on Trend Data from the Survey of Graduate Students and Postdoctorates in Science and Engineering.

• Eligibility and degree-granting status.

Institutions are classified as doctorate-granting if at least one GSS-eligible unit confers doctoral degrees. In 2022, seven institutions became ineligible for the GSS. The 2022 survey cycle also saw four institutions merge into a single institution, combining a Health Science Center campus with that of the university’s main campus. In addition, 12 institutions changed GSS degree-granting status: 2 from doctorate-granting to master’s-granting institutions, and 10 from master’s-granting to doctorate-granting institutions. As a result, the total number of institutions included in the GSS decreased from 699 in 2021 to 690 in 2022 (see table A-2 for details on institutional status and table A-3 for overall number of institution counts).

Changes in survey content.

• Sex.

2010: Began collecting ethnicity, race, and citizenship data on postdocs by sex and began collecting type of doctoral degree data on NFRs by sex.

2008: Began collecting the number of first-time, full-time male graduate students by ethnicity and race; full-time male graduate students by source of support; male postdocs by source of support; and male NFRs. Previously, the number of men was inferred by subtracting the number of women from the total.

• Ethnicity and race.

2010: Began collecting ethnicity and race data for postdocs who are U.S. citizens and permanent residents using the same categories as used for graduate students.

2008: Revised ethnicity and race categories to correspond to IPEDS by combining “Hispanic/Latino, one race only” and “Hispanic/Latino, more than one race” categories into “Hispanic or Latino (one or more races).”

• Citizenship.

2010: Began collecting citizenship data on postdocs using the same categories that are used for graduate students. In previous years, only counts of postdocs who are foreign nationals holding temporary visas were collected.

2008: Clarification made for “non-U.S. citizens” to exclude non-U.S. citizens residing outside of the United States who are enrolled in an online degree program at a U.S. institution.

• Financial support.

2010: Began collecting data on the largest source of financial support and on the largest mechanism of support separately for postdocs. For mechanism of support, “nonfederal sources” was replaced with “other support.”

2008: Graduate student data no longer collected for NIH teaching assistantships because NIH does not offer financial support for students through this mechanism.

2008: Began collecting the number of full-time graduate students whose largest source of support came from a non-U.S. source via teaching assistantship.

• Degree level.

2017: Began separate collection of demographic and financial data by master’s and doctoral students.

• Doctoral degree.

2010: Began collecting more detailed information on postdocs’ and NFRs’ doctoral degree type. Categories were added for those holding a doctoral degree (e.g., PhD, ScD, DEng), a professional degree (e.g., MD, DVM, DO, DDS), and dual degrees (e.g., MD-PhD, DVM-PhD) as well as for those whom type of degree was unknown. In previous years, the GSS collected degree-type information by asking respondents to indicate how many of the total number of postdocs (or NFRs) had MD, DO, DDS, or DVM degrees. This number was used to estimate the number of postdocs (or NFRs) with medical degrees; the number with research degrees was estimated as the difference between the total counts and the counts of those with medical degrees.

2010: Began collecting postdocs’ doctoral degree type by citizenship and by country of origin (United States, foreign, unknown) of doctoral degrees. Also began collecting NFRs’ doctoral degree type by sex.

Changes in survey procedures.

2017: Coordinators were asked to report master’s and doctoral student data separately and to use CIP codes to categorize their organizational units when reporting student data. Coordinators could report organizational units with postdocs and NFRs using either CIP or GSS codes. Two alternative methods for uploading GSS data were expected of coordinators in 2017. The first option enabled coordinators to utilize an Excel template file to construct a de-identified, individual-level data file. This file could then be uploaded directly into the Web survey. The second option enabled the coordinator to aggregate the individual-level data to the unit level using an Excel macro provided in the template file rather than transmit any individual-level data. A manual data entry option was available to those unable to provide an uploaded file. Coordinators had access to data file templates, a sample SQL SELECT statement containing all GSS-eligible CIP codes that could be used to query their information systems, online training videos, and additional support from the survey contractor on the new data collection changes. Coordinators could continue to use unit respondents to provide part or all of the data request. Organizational units that reported using CIP codes were automatically re-coded to the updated GSS taxonomy by the Web instrument. Coordinators reporting data using GSS rather than CIP codes were asked to re-code their organizational units to the updated GSS taxonomy.

2010: Significant effort was made to ensure that appropriate personnel were providing postdoc and NFR data. As a result, it is unclear how much of the increase reported in 2010 represented actual growth in postdocs and how much resulted from improved data collection. For information on the improved data collection and changes in postdoc data, see Counts of Postdoctoral Appointees in Science, Engineering, and Health Rise with Reporting Improvements; for changes in NFR data, see Examining the Reporting of Nonfaculty Doctorate Researchers in the Survey of Graduate Students and Postdoctorates in Science and Engineering.

Historical changes. Changes have been made over the years to the coverage and content of the GSS to keep it relevant to the needs of data users. Such changes impact analysis of trend data, so data comparisons across years should be made with caution. This is especially true for counts; however, proportions or shares are typically robust enough to allow for such comparisons.

In 2017, due to the taxonomy and data collection changes (described above), a set of bridge estimates was created to permit comparisons to previous years and for trend analyses. These estimates are labeled 2017old and are available at the broad field level for all combined graduate student variables as well as postdoc variables. Due to a large increase in counts attributable to prior underreporting, 2017old estimates are not available for NFR data. The data reported as 2017new use the updated GSS taxonomy and are comparable to 2018–21 data but are not comparable to data from prior years. Please note that in tables that compare data from 2017 to the present that 2017new data are used.

Due to the survey frame update, the data comparisons between 2014 and earlier years should use the 2014old data, and those between 2014 and 2016 should use the 2014new data. The impact of frame updates can be evaluated using the 2014old and 2014new data. For more information on the survey frame update, see the Special Report Assessing the Impact of Frame Changes on Trend Data from the Survey of Graduate Students and Postdoctorates in Science and Engineering. For more information on the changes prior to 2010, see Graduate Students and Postdoctorates in Science and Engineering: Fall 2009: ​“Technical​ Notes” section. For specific changes from the major survey redesign in 2007, see the 2007 report: “Technical Notes.”

Degree level.

• Master’s degree. A post-baccalaureate, research-focused degree; includes MA, MS, MASc, and PSM in GSS-eligible disciplines.
• PhD or PhD equivalent degree. An advanced, research-focused academic degree—typically, the highest degree granted in a particular field; includes doctorates such as PhD, ScD, DSc, and DEng.

Enrollment status.

• Full time and part time. Coordinators were instructed to use their institution’s definitions.
• First time, full time. Students enrolled for credit in a graduate degree program in an organizational unit for the first time in the fall semester of the survey year. This may include graduate students previously enrolled in another graduate degree program at the institution or at another institution and students who already hold another graduate or professional degree.

Ethnicity and race. The GSS uses definitions of ethnicity and race that are based on the OMB’s Standards for the Classification of Federal Data on Race and Ethnicity.

• Hispanic or Latino ethnicity (one or more races).^{​The OMB standards designate Hispanics as an ethnic group rather than a racial group. Following these standards, Hispanic is not counted as a race in GSS. Cognitive interviews with respondents showed this was a source of considerable confusion. For example, prior to 2008 Black Hispanics and White Hispanics could be counted as “Hispanic, More than one race” rather than “Only one race, Hispanic.” The ethnicity and race categories were aligned to IPEDS by combining the “Hispanic/Latino, More than one race” and “Hispanic/Latino, One race only” categories. In 2008, these two Hispanic categories were collapsed into one: “Hispanic or Latino ethnicity (one or more races).”The OMB standards designate Hispanics as an ethnic group rather than a racial group. Following these standards, Hispanic is not counted as a race in GSS. Cognitive interviews with respondents showed this was a source of considerable confusion. For example, prior to 2008 Black Hispanics and White Hispanics could be counted as “Hispanic, More than one race” rather than “Only one race, Hispanic.” The ethnicity and race categories were aligned to IPEDS by combining the “Hispanic/Latino, More than one race” and “Hispanic/Latino, One race only” categories. In 2008, these two Hispanic categories were collapsed into one: “Hispanic or Latino ethnicity (one or more races).”The OMB standards designate Hispanics as an ethnic group rather than a racial group. Following these standards, Hispanic is not counted as a race in GSS. Cognitive interviews with respondents showed this was a source of considerable confusion. For example, prior to 2008 Black Hispanics and White Hispanics could be counted as “Hispanic, More than one race” rather than “Only one race, Hispanic.” The ethnicity and race categories were aligned to IPEDS by combining the “Hispanic/Latino, More than one race” and “Hispanic/Latino, One race only” categories. In 2008, these two Hispanic categories were collapsed into one: “Hispanic or Latino ethnicity (one or more races).”} All individuals of Cuban, Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin, regardless of race. This category includes individuals who are Hispanic or Latino and any other race.
• Not Hispanic or Latino. Individuals who are not of Hispanic or Latino descent, regardless of race.
• American Indian or Alaska Native. A person of only one race having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.
• Asian. A person of only one race having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent—for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.
• Black or African American. A person of only one race having origins in any of the Black racial groups of Africa.
• Native Hawaiian or Other Pacific Islander. A person of only one race having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific islands.
• White. A person of only one race having origins in any of the original peoples of Europe, the Middle East, or North Africa.
• More than one race. A person of two or more of the race categories listed above.
• Unknown ethnicity or race. A person whose ethnicity or race is unknown or not stated.

Graduate student mechanisms of financial support.

• Fellowship. A competitive award (often from a national competition) given to a graduate student that requires no work by the recipient.
• Traineeship. A financial award given to a graduate student selected by the institution.
• Research assistantship. A financial award given to a graduate student for which most of the student’s responsibilities are devoted primarily to research.
• Teaching assistantship. A financial award given to a graduate student for which most of the student’s responsibilities are devoted primarily to teaching assistant activities.
• Other support. All other mechanisms of support for graduate students.

Graduate student sources of financial support.

• Federal sources. Financial support provided by U.S. federal agencies. Excludes federally guaranteed student loans.
• Nonfederal sources. Financial support from state and local governments; support from the institution, such as tuition waivers and stipends; support from foreign sources, such as foreign governments, foreign firms, and agencies of the United Nations; and other U.S. sources, such as support from nonprofit institutions, private industry, and all other nonfederal U.S. sources.
• Self-support. Loans (including federal loans) or personal or family financial contributions.

Historically Black colleges and universities (HBCUs). Institutions of higher education that were established prior to 1964 and whose principal mission was, and is, the education of Black Americans. The list of HBCUs is maintained by the White House Initiative on HBCUs (https://sites.ed.gov/whhbcu/).

Nonfaculty researchers (NFRs). All doctorate-holding researchers who (1) are not considered either postdocs or members of the faculty and (2) are involved principally in SEH research activities. Also referred to as Other doctorate-holding NFRs.

Postdoctoral researchers (postdocs). The definition of a postdoc varies by institution. Respondents were instructed to use their institution’s definition. NCSES defines a postdoc as meeting both of the following qualifications: (1) holds a recent doctoral degree, generally awarded within the past 5–7 years, such as PhD or equivalent (e.g., ScD, DEng), or first-professional degree in a medical or related field (e.g., MD, DDS, DO, DVM), or foreign degree equivalent to a U.S. doctoral degree; and (2) has a limited-term appointment, generally no more than 5–7 years, primarily for training in research or scholarship, and working under the supervision of a senior scholar in a unit affiliated with the institution.

Postdoc mechanisms of financial support.

• Traineeship. A financial award given to a postdoc selected by the institution.
• Research grant. A financial assistance award given to an organization or an individual postdoc that supports specific research goals.
• Other support. All other mechanisms of support for postdocs.

Postdoc sources of financial support.

• Federal sources. Financial support provided by U.S. federal agencies.
• Nonfederal sources. Financial support from state and local governments; support from the institution; support from foreign sources, such as foreign governments, foreign firms, and agencies of the United Nations; and other U.S. sources, such as support from nonprofit institutions, private industry, and all other nonfederal U.S. sources.
• Personal resources. Personal and family financial resources, including federal and other loans.
• Unknown or not stated. Sources of financial support for the postdoc are unknown or cannot be determined.