even as these scientists are becoming increasingly prevalent in the research community. Recommendation 6.3 is very far removed from the current situation, but one that is vital to the continued success of the research enterprise.

Non-tenure-track scientists and physicians should be eligible—by both institutions and the NIH—to apply for grants, including the New Investigator R01, and the NIH should review such applications without prejudice regarding their “soft-money” status. One challenge will be to ensure that these applications really do represent an independent research project from the applicant and not merely an opportunity for an established investigator to extend his or her funding through a junior colleague.

Finally, to allow evaluation of the impact of such grants, NIH should monitor non-tenure-track applicants for R01 grants with respect to their funding rate and their success in future R01 applications—both new grants and competitive renewals.


As with postdoctoral and other researchers, NIH needs informative data on all segments of the scientific workforce, including tenure-track and non-tenure-track researchers.

6.4 NIH should develop enhanced data collection systems on all NIH-supported researchers, regardless of specific funding mechanism. This will allow NIH to track the effectiveness of its programs, make more informed programmatic decisions, and monitor the career progression of supported researchers.

These data should include information about position, responsibilities, and support on those receiving NIH support. For instance, what percentage of time do funded investigators spend on research? Teaching? Clinical responsibilities? Is salary support provided by the host institution or is some of it obtained through external grants? How does this distribution correlate with the position held by the investigator? Moreover, data should be disaggregated to detect different trends among different demographic and other groups.

In sum, creating a more stable environment for new investigators will encourage productivity and innovation early in their careers as they choose a long-term path. Great uncertainty is non-productive and can lead to risk-averse behavior, an anathema to good science.

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