NSF Conservative-Research Bias is grant cycles favor safe, incremental work over high-risk breakthroughs. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0190, within the Education Perverse Pattern family. The core principle: grant cycles favor safe, incremental work over high-risk breakthroughs. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
Scientific Definition
Grant cycles favor safe, incremental work over high-risk breakthroughs.
Plain-English Definition
Grant cycles favor safe, incremental work over high-risk breakthroughs.
Feynman Explanation
Pay only for sure things, and you'll pay for nothing new.
Core Principle
Grant cycles favor safe, incremental work over high-risk breakthroughs.
Mechanisms
Pending editorial review.
Grant cycles favor safe, incremental work over high-risk breakthroughs.
Pending editorial review.
Pending editorial review.
Funder risk preferences shape national R&D portfolios.
Pending editorial review.
Pending editorial review.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
Pay only for sure things, and you'll pay for nothing new.
Examples
- Mid-career scientists drifting toward predictable proposals.
- Funder risk preferences shape national R&D portfolios.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
The mistake with this element is treating it as irrationality. It is almost always a rational response to a payoff nobody wrote down. The mechanism underneath it is straightforward: grant cycles favor safe, incremental work over high-risk breakthroughs. You can recognize it in the field by its signature: pay only for sure things, and you'll pay for nothing new. Every element in the Incentives dimension changes the perceived payoff of an action before the action happens, which is exactly where incentive design has leverage.
How it gets exploited
Left undesigned, funder risk preferences shape national R&D portfolios. It is amplified whenever funder risk preferences shape national R&D portfolios. Inside organizations that shows up as funder risk preferences shape national R&D portfolios. The pattern is the same one Goodhart's Law describes: the measurable proxy attracts the effort, and the purpose behind it quietly loses funding.
How the Lab designs around it
The redesign move is to carve-outs for high-risk grants. Lottery-style allocation tranches. Design against it the way you would design against a known failure mode — assume it will appear, and price the exploit before someone finds it.
Famous Experiments
Pending editorial review.
Design Principles
- Carve-outs for high-risk grants. Lottery-style allocation tranches.
Measurement Approaches
Pending editorial review.
Evidence
Pending editorial review.
Pending editorial review.
The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Carve-outs for high-risk grants. Lottery-style allocation tranches.
Pending editorial review.
Pending editorial review.
Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
Tenure-track jobs replaced by low-paid adjuncts, lowering cost and quality.
Seat-time accountability rewards presence over engagement.
Employers screen by school name, rewarding admission rather than developed skill.
Schools optimize for ranking inputs (selectivity, spending) instead of student outcomes.
Tying institutional survival to graduate salaries forces schools to drop social-service programs.
Grade-driven admissions reward strategic course-picking over intellectual risk.
Professors rewarded by student evaluations have an incentive to inflate.
Schools judged on completion rates have an incentive to pass underprepared students.
More homework signals rigor to parents but often produces burnout, not understanding.
Universities optimize for ranking metrics rather than education quality.
A single test format constrains pedagogy and disadvantages diverse learners.
Easy federal lending lets colleges raise tuition without market discipline.
Where NSF Conservative-Research Bias is cited in the corpus
Essays, field guides, and diagnostics from The Incentives Lab that apply this element.
- Field guideIncentives: definition, types, examples
The parent field guide for this element.
- ReferenceThe laws of incentives
Goodhart, Campbell, and the Cobra Effect.
- EssayIncentives Under Crisis
How this element behaves under pressure.
- ReferenceThe Periodic Table of Human Behavior
The full 1,267-element map this page belongs to.
- CourseIncentives 101
The free ten-part primer on reading a payoff structure.
Questions about NSF Conservative-Research Bias
- What is NSF Conservative-Research Bias?
- NSF Conservative-Research Bias is grant cycles favor safe, incremental work over high-risk breakthroughs. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0190, within the Education Perverse Pattern family. The core principle: grant cycles favor safe, incremental work over high-risk breakthroughs. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
- What is an example of NSF Conservative-Research Bias?
- Funder risk preferences shape national R&D portfolios. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-INC-0190).
- How is NSF Conservative-Research Bias exploited?
- Funder risk preferences shape national R&D portfolios.
- How do you design around NSF Conservative-Research Bias?
- Carve-outs for high-risk grants. Lottery-style allocation tranches.
- Which behavioral dimension does NSF Conservative-Research Bias belong to?
- NSF Conservative-Research Bias is classified in the Incentives dimension (INC) of the Human Behavior Taxonomy™, family "Education Perverse Pattern", class "Perverse Incentive". Its permanent identifier is HBT-INC-0190 and its evidence grade is C.