Exploring inductive risk : case studies of values in science

313 Pages·2017·2.282 MB·English

by  Elliott, Kevin C., Richards, Ted

Exploring Inductive Risk

Exploring
Inductive Risk
Case Studies of Values
in Science
Edited by
KEVIN C. ELLIOTT
TED RICHARDS
1
3
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Contents
Foreword  ix
Heather Douglas
Acknowledgments  xiii
List of Contributors  xv
1. Exploring Inductive Risk: An Introduction— Kevin C. Elliott
and Ted Richards 1
PART ONE: Weighing Inductive Risk
2. Drug Regulation and the Inductive
Risk Calculus— Jacob Stegenga  17
3. D ecisions, Decisions: Inductive Risk and the
Higgs Boson—K ent W. Staley  37
PART TWO: Evading Inductive Risk
4. Dual- Use Research and Inductive Risk—D avid B. Resnik  59
5. Making Uncertainties Explicit: The Jeffreyan Value- Free Ideal
and Its Limits—D avid M. Frank  79
6. Inductive Risk, Deferred Decisions, and Climate Science
Advising— Joyce C. Havstad  and Matthew J. Brown 101
viii Contents
PART THREE: The Breadth of Inductive Risk
7. Measuring Inequality: The Roles of Values and Inductive
Risk— Robin Andreasen  and Heather Doty 127
8. Safe or Sorry? Cancer Screening and Inductive
Risk— Anya Plutynski  149
9. Inductive Risk and Values in Composite Outcome
Measures— Roger Stanev  171
10. Inductive Risk and the Role of Values in Clinical
Trials— Robyn Bluhm  193
PART FOUR: Exploring the Limits of Inductive Risk
11. The Geography of Epistemic Risk— Justin B. Biddle
and Rebecca Kukla 215
12. The Inductive Risk of “Demasculinization”— Jack Powers  239
13. Exploring Inductive Risk: Future Questions— Kevin C. Elliott 
and Ted Richards 261
Index  279
Foreword
What is inductive risk? Inductive risk is the chance, the pervasive possi-
bility, of getting it wrong in an inductive context. Scientific inquiry always
takes place in an inductive context, even if sometimes deductive reasoning
is also useful. In general, decisions in science are not determined by the ev-
idence available. When you make a decision in science— about how to con-
duct a research project, how to characterize data, which background pieces
of information to accept as stable, whether the data sufficiently support the
study’s claim— you incur a risk that your decision is epistemically mistaken.
Scientists have lots of ways of managing this risk, but it is an endemic feature
of scientific practice.
I first came across the term when writing my dissertation. For that pro-
ject, I examined why experts disagreed in their interpretation of toxicological,
epidemiological, and biochemical studies of dioxins. I noted that different
experts seemed to have different concerns about which errors (e.g., false posi-
tives or false negatives) to more carefully avoid and thus different standards
for what counted as sufficient evidence for a claim of health risks from diox-
ins. In their own discussions of their work, experts’ different standards arose
from different concerns regarding overregulation or underregulation. My
fellow graduate student Erik Angner, in hearing about my work, suggested
I look at Carl Hempel’s 1960 essay “Science and Human Values” (republished
in his foundational collection of papers, Aspects of Scientific Explanation) for
a similar argument regarding values in science.
Hempel’s wide- ranging essay examines the complex relationship between
values and science, including how science can influence values and values can
influence science. Regarding the latter, Hempel noted that values can offer no
confirmatory weight to scientific claims. But he argued that values do have a
role to play in the acceptance of scientific claims. Values are important for the