Lecture 19 Class Notes

Positive vs Normative questions

  • Positive: Describe and explain causal mechanisms: “Is” and “How”
  • Normative: Value judgments, desire, obligation: “Ought”
  • Science asks positive questions

What’s science?

  • NOT a body of factual knowledge
  • NOT a privileged elite group, more entitled to rule
  • A process, method, to advance positive knowledge

How does it work?

  • Method: guesses (hypotheses), implications for what you should see (testable), then look
  • Mechanisms: Peer review (anonymous), replication of results – public, collective, impersonal
  • Norms: Rules of argument, presumed motives (truth, not winning) – yours and others
  • Strong presumption against novel claims – high standard of demonstration


  • Powerful method to advance knowledge, exploit beneficial applications
  • No certainty, no proof: all results provisional. Science never proves anything
  • Still, we accept many points as “settled fact” – and reasonably so

Do social/political factors influence? Sure, to some extent

  • Paradigms pretty strong – shape what’s “interesting”, “plausible”, give stability to disciplines
  • But strong “social construction” claims hard to support for content of scientific knowledge

There are more permissive rules of argument in policy compared to science

What science CAN do
1. Answer positive questions about the world:

  • When these are (for whatever reason) deemed policy‐relevant
  • And scientific knowledge is well‐established

2. Describe, project consequences of proposed actions

  • In terms people care about …
  • On which cost and benefit estimates can be formed (by whom?)
  • But science doesn’t do the valuation

3. Describe current knowledge, uncertainty, controversy

  • Even when knowledge not fully settled
  • To support risk‐management, decisions under uncertainty
  • And help identify priorities for decision‐relevant research

4. Ideal: Cleanly separate risk assessment, risk management

5. Map onto basic Benefit‐cost framework: Science can help …

  • Step 1: Identify available choices (a little)
  • Step 2: Identify and describe consequences (more)

Science informing policy:
Plenty of difficulties (even without politics)
1. Scientific uncertainty …

  • Comes as divergent results and disagreements, not probability distributions
  • Describing in decision‐relevant terms: hard, contentious (both how to do it, and whether it’s permissible to do it!)
  • E.g., What’s the probability distribution of climate sensitivity, or the carcinogenicity of dioxin?

2. What makes a “policy‐relevant” scientific question?

  • Science (alone) can’t say
  • Policy‐makers’ questions may be ill‐posed, normative, tendentious
  • Need close interaction even to define useful questions

3. Ignorance and “trans‐science”

  • Scientifically posed questions that science cannot answer (Weinberg)
  • Now, in time for needed decision, or maybe ever …
  • E.g., precise projections of climate‐change harms to my district

Scientific assessment processes: Examples
1. Some assessment bodies address specific questions under existing legal authorities: May be empowered to recommend decisions

  • Endangered Species Act: endangerment determinations, critical habitat
  • Carcinogenicity determinations
  • Fishery allowable catches …

2. Many long for a clean science/policy boundary, but it’s not possible

  • Can’t define criteria precisely enough to avoid giving science bodies policy influence, constructive authority

3. Scientific assumptions, methods of inference, treatment of uncertainty:

  • E.g., definition of “endangerment”; low‐dose extrapolation from observed exposures; setting “sustainable” catch under uncertainty; etc.
  • Unavoidably confounded with normative judgments, attitudes to risk, policy preferences
  • AND therefore disputed, based on foreseeable effects on policy

4. Successful bodies: Continually (and implicitly) negotiate workable boundary between authority of “scientific” and subsequent “decision‐making” bodies