What Kind of Research Do You Do?

In “A Science Funding System Beyond the Linear Model” (Issues, Spring 2026), Heather Douglas asks funders to move past the distinction between “basic” and “applied” research. She proposes six categories: mission-directed research, engaged public research, private-interest research, regulatory research, Big Science infrastructure, and curiosity-based research. Each would have its own funding structure and standards of evaluation, rather than being judged by publications, citations, future grants, and claims about eventual public benefit.

The author’s proposal is the rare critique that is as actionable as it is creative. It requires no radical politics; it should have bipartisan appeal; and it is crafted specifically to fit the vagaries of the modern scientific enterprise.

The proposed taxonomy also makes it easier to see how funding decisions become career pressures: The more a project depends on collaboration, public accountability, or long timelines, the less likely it is to fit the metrics that still govern hiring, tenure, and promotion. Early-career researchers are often asked to pursue ambitious work while also producing steady publications and winning grants. Interdisciplinary researchers face similar pressure when their work does not fit a department’s expectations. Community-engaged researchers take on the additional labor of building relationships, maintaining trust, and producing outcomes outside the university, even when those activities are not fully counted as scholarship.

Importantly, Douglas’s proposal extends beyond funding agencies. If different kinds of research require different forms of accountability, then hiring, tenure, and promotion systems need to recognize those differences. Otherwise, the categories change for funders but not for careers.

Engaged public research is the clearest example. Douglas notes that this work often requires interdisciplinary teams, long timelines, and sustained communication with public partners. It may produce slower publication cycles, and its success may depend on whether the relevant community judges the work to be responsive and useful. If tenure committees continue to treat journal articles and grant totals as the main evidence of achievement, then engaged public research will remain professionally risky, even with a dedicated funding category.

The same issue appears elsewhere. Regulatory research should be judged by independence, transparency, and usefulness for public decisionmaking, not by whether it produces commercially attractive results. Big Science infrastructure raises questions about contribution, credit, governance, and opportunity cost that individual publication counts cannot capture. Mission-directed research may involve redirection or termination when a project no longer serves its mission, which can look like failure if academic evaluation ignores the structure of
the work.

Curiosity-based research, especially under a lottery system, raises another problem. A lottery may reduce conservatism, bias, and the Matthew effect that disproportionately rewards eminent or famous scientists, but it also makes explicit what is already true: Funding outcomes contain uncertainty. If universities continue to use external funding as a proxy for quality, then early-career scientists could remain exposed to a familiar danger: no grant money, no prestige, no career advancement.

Douglas’s funding ontology should therefore be paired with reforms in academic evaluation. Departments should consider what kind of research a scholar is doing before evaluating productivity. Without such an alignment, funding reform may reduce some institutional risks while leaving the professional ones intact.