The Two Kinds of Science Framework
Distinguish between high-risk, hypothesis-driven science and low-risk, incremental 'crank-turning...
This framework presents a fundamental dichotomy in scientific research, articulated by a professor at the Salk Institute and echoed in the conversation. It categorizes all scientific inquiry into two distinct types based on risk, ambition, and potential reward. The first kind is bold, hypothesis-driven science that aims to test a transformative idea. It carries a high probability of failure but, if successful, can open entirely new fields or cure diseases. The second kind is incremental, 'crank-turning' science. It involves applying established methods to slightly new contexts (e.g., studying a different protein in a known pathway). This work is predictable, has a high probability of generating publishable papers, but is unlikely to produce paradigm-shifting discoveries.
The framework is crucial for understanding the incentive structures within academia and funding bodies. The current system, particularly through mechanisms like NIH study sections, overwhelmingly rewards the second kind of science because it minimizes risk to the funder and provides reliable outputs (papers, trained students) for the investigator. This creates a misalignment where the safest career path for a scientist is to pursue incremental work, even though the greatest societal benefits come from the high-risk, high-reward first kind. The framework forces an explicit conversation about what balance a lab, department, or funding agency wants to strike between these two modes of inquiry.
- Scientific work exists on a spectrum from high-risk/high-reward hypothesis testing to low-risk/incremental 'crank-turning.'
- The current academic funding system (e.g., NIH peer review) is structurally biased toward funding incremental, predictable science.
- Pursuing only incremental science leads to field-wide stagnation, even if individual labs remain 'productive' in terms of paper output.
- True scientific breakthroughs almost always come from the high-risk category, but these projects are the hardest to fund under the prevailing model.
- An individual scientist's career stage and security (pre-tenure vs. tenured) dramatically influences their ability to engage in high-risk science.
- Categorize Your Research AgendaHonestly assess your current and planned projects. Label each as either 'Type 1: Bold Hypothesis' (high risk of failure, transformative potential) or 'Type 2: Incremental/Crank-Turning' (low risk, adds to existing knowledge predictably).Pro tipBe ruthless. A project using a brand-new technique to ask a fundamental question is Type 1. A project using standard methods to characterize the next member of a known gene family is likely Type 2.WarningMost labs need a mix for survival, but you should know the ratio. A lab with 100% Type 2 projects is not an innovative lab, regardless of publication count.
- Align Projects with Funding SourcesMatch Type 1 projects to funding mechanisms designed for high-risk research (e.g., NIH Director's Pioneer Awards, NSF EAGER grants, private foundation 'blue sky' programs). Reserve Type 2 projects for standard RO1-style grants where preliminary data and a clear path to results are expected.Pro tipFor Type 1 grants, frame the proposal around the transformative potential and the field-altering question, not the volume of preliminary data.WarningSubmitting a truly Type 1 proposal to a standard study section is often a recipe for rejection, as reviewers are trained to look for 'sure bets.'
- Structure Lab Resources and MentorshipAllocate lab resources strategically. Use reliable funding from Type 2 projects to provide stability (salaries, core facilities). Dedicate a portion of time, personnel, and discretionary funds to pursue Type 1 ideas, even if unfunded initially.Pro tipEncourage graduate students and postdocs to have a 'side project' that is high-risk/high-reward, separate from their thesis/dissertation work which often must be more incremental to ensure completion.WarningWithout explicit protection, Type 1 projects will always be cannibalized by the immediate demands and deadlines of Type 2 work.
- Evaluate Career and Tenure TracksFor institutions and departments, explicitly define what mix of Type 1 and Type 2 work is valued for tenure and promotion. Does a candidate need a major breakthrough (Type 1), or is a steady stream of solid incremental papers (Type 2) sufficient? Make these criteria transparent.Pro tipConsider creating separate 'tracks' for innovators and consolidators, rewarding both but recognizing they contribute differently.WarningIf tenure is awarded primarily for securing large RO1 grants (which favor Type 2 work), you will systematically select for and promote incremental scientists, driving out innovators.
- Design Funding Portfolio BalanceFor funding agencies and program officers, consciously design your portfolio. Decide what percentage of the budget should be allocated to high-risk Type 1 proposals versus safer Type 2 proposals. Treat Type 1 funding like a venture capital portfolio, expecting many failures for a few huge wins.Pro tipUse tools like the Innovation Age Decay Analysis to monitor whether your portfolio's balance is shifting towards novelty or stagnation.WarningPolitically, it is difficult to defend funding failures, even if they are necessary for breakthroughs. Public communication about the portfolio strategy is essential.
The development of the Polymerase Chain Reaction (PCR) in the early 1980s is a classic example of Type 1 science. It was a novel, bold idea for amplifying DNA. A paper published in 1983 using PCR would have had a very low 'innovation age' as it was a brand-new concept.
The podcast describes a senior scientist bragging about having the same NIH RO1 grant renewed for 30 years. Applying the framework, this almost certainly represents a career built on Type 2 science. The initial discovery may have been novel, but decades of renewals suggest a long period of incremental 'crank-turning' on the same core idea.
The framework emerged from direct observation and critique within the scientific community, particularly among senior researchers who have witnessed the increasing conservatism of grant review panels. It was crystallized in a statement from a Salk Institute professor to Dr. Bhattacharya, who relayed it in the podcast. The origin is rooted in the lived experience of scientists who feel the tension between the desire to pursue groundbreaking ideas and the practical need to secure continuous funding to maintain their labs, support trainees, and achieve tenure. It is a direct response to the 'RO1 shell game,' where scientists propose work they have already largely completed to guarantee funding for the next cycle, inherently favoring incrementalism.