Purpose: To examine patterns of NCI training and educational awards (T32 & R25) by indicators of research capacity and student diversity. Methods: FY2019 data from the US Department of Education and NIH Exporter were used to examine student diversity and NCI funding by research capacity as defined by Carnegie Classification of Institutes of Higher Education. Results: In FY2019, the Carnegie Classification for Doctoral Universities (n = 412) included 131 “R1”_ and 135 “R2”_ research-intensive universities, and 146 other doctoral and professional universities ("DPU"_).At all Carnegie Institutions, >45% students were White. By Carnegie classes, compared to R2 and DPUs, R1s had the lowest proportions of African American, American Indian/Alaskan Native, Native Hawaiian and Other Pacific Islander, and female students, at both college and graduate levels. Proportions of Hispanic undergraduates were similar across Carnegie classes, and generally higher than those for Hispanic graduate students, which were lowest among R1s relative to R2s and DPUs. Asian American and nonresident alien students (undergraduate and graduate) comprised higher proportions of R1 students than those at R2s and DPUs.Schools varied by Minority Serving Institution status. For instance, numbers of Hispanic Serving Institutions were similar for R1s (16), R2s (16), and DPUs (18), but 11 R2s were Predominantly Black Institutions and only one R1 was and no DPUs. In contrast, 71 R1s were Asian American Serving Institutions, far higher than the 16 R2s and 19 DPUs with that status.Of >2,000 “NCI R01 and equivalent awards”_ in FY2019, >90% were awarded to R1s, with <10% at R2s and <1% at DPUs. Patterns by Carnegie class were similar for NCI Fellowship (F), Career Development (K), and Training Program awards (T). Conclusion: Both low student diversity at research resource-rich schools and higher diversity at schools with fewer research awards may contribute to and perpetuate few individuals from underrepresented racial and ethnic groups working in cancer research. To address this long-standing problem requires understanding how many factors and systems interact at multiple levels (e.g., individual, institutional, funding agency) to drive and block access to training and career advancement in cancer research.
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