News from the Front #95:
How Government Destroyed Science in Columbia River
Dam Decisionmaking
Remarks
at the First Annual Northwest Water Law Symposium, Lewis & Clark Law
School
Before I begin discussing the use of science
in
What is science? Since this is a law school, I will cite the
Supreme Court’s Daubert case, which
determined how federal courts should decide whether to accept scientific expert
testimony. In that case, the Court
actually managed at one point to stumble right on it: “‘Scientific methodology today is based on
generating hypotheses and testing them to see if they can be falsified;
indeed, this methodology is what distinguishes science from other fields of
human inquiry.’ . . .”
I will argue that the essence of science is
that there are things that are out there that are true, and while we can all
speculate about the truth is, we can test our speculation against the
truth. This is usually done by taking
measurements in an experiment. And when
our hypothesis is falsified, that is,
contrary to the truth as revealed by the evidence we gather, we have to discard
or refine that hypothesis.
I would also argue that measurement or
quantification is another very important aspect of science. As a famous physicist, Lord Kelvin once
observed,
“When
you can measure what you are speaking about, and express it in numbers, you
know something about it; but when you cannot measure it, when you cannot
express it in numbers, your knowledge is of a meager and unsatisfactory kind:
it may be the beginning of knowledge, but you have scarcely, in your thoughts,
advanced to the stage of science.”
What Lord Kelvin did not say is that if you really have a scientific understanding
of something, you can also use that scientific knowledge to predict what will happen under a certain
set of initial conditions (at least outside the quantum context).
Since this is a law school, you might think
that the courts are on the job policing the matter and making sure governmental
policy has some relationship to science.
Unfortunately, that is false.
There are a number of what I would call vectors of decay in modern law
that decisively falsify that idea.
1. Federal courts will not decide the truth
in scientific questions. Indeed, they
are fundamentally disinterested in whether government decisions are true or
not; the standard of review is “arbitrary and capricious,” not right or
wrong. A corollary of the this rule, by
the way, is that the Daubert test for
reliability of expert scientific evidence is completely inapplicable in the
context of judicial review of agency action.
2. Federal courts will not require the
government to release its files containing scientific information if the
government wants to keep them secret.
The Federal courts have invented a presumption that the quality of
administrative decisionmaking will be improved if citizens are not able to see
anything going on during the decisionmaking process, which might “chill” the
process or “embarrass” the participants.
3. Federal courts will not permit people who
disagree with government science and file law suits about it to get any
discovery of the scientists involved, or their papers. As a practical matter, judicial review is
limited to the record that the government gets to assemble to justify whatever
decision it has made. And so if
something doesn’t help, and the Justice Department has assigned what we might
call effective lawyers to the case,
well, they just leave it out of the record.
4. Federal courts will not even permit people
who disagree with the government decisions to question to the government’s
scientific witnesses in court, even when they rely on their affidavit testimony
to make decisions. Cross-examination has
been called the greatest engine for the discovery of truth ever invented, but
it is almost never used in cases concerning government scientists.
So
other than the occasional activist judge who ignores administrative law, the
judicial branch has abandoned any effort to discern scientific truth. Indeed, one usually hears a pitiful sort of
whining from the judges along the lines of “it’s not my job” or “it’s too
hard”.
So
we are left with the integrity of the individual scientists themselves. How is that working for us? Unfortunately, it is a very rare kind of
integrity that is required; it takes real open-mindedness to hold a hypothesis,
and when it has been falsified, to modify or discard the hypothesis, and try
again. People who call themselves scientists often pretend to have this
openmindedness, but they are just people after all, and those who have studied
the history of science can see that nearly all scientists can’t achieve this
state of mind.
Our
other panelist, Dr. Haeseker, just suggested that a test of “endurance” for
scientific truth, but falsity is pretty durable too. Michael Crichton gave a horrible example in a speech a few
years ago at
Caltech:
“In past centuries, the
greatest killer of women was fever following childbirth . One woman in six died
of this fever. In 1795, Alexander Gordon of
And we can see this thing over and over in
science: most of the scientists just
don’t care enough about the truth to listen to a minority, or a single skeptic,
who has good evidence inconsistent with what they believe.
People
like to believe what everyone else around them believes, even if is plainly
wrong. Indeed, consensus is the enemy of
science, because consensus is invoked to maintain the conventional view. And maintaining the conventional view means
we do not advance our understanding. So
when you hear politicians say they are ensuring good science through peer
review, it is a lie like nearly everything else politicians say, because peer
review is the enforcement of consensus.
Just
to try and liven things up here, I’d like to give an example, that Dr. Haeseker
has just talked about. You may recall he
showed a slide with some people in a inner tube drinking beer and floating down
the river. And he said that because of
the dams, the Lower Granite to Bonneville float time, which he equated with
fish travel time, has gone from 1.7 days to 18.7 days. But it is easy to falsify the hypothesis that
within the wide range of river flows we observe now, that fish travel time
changes much at all.
Now
it is a basic fact about the
And you can see that during the 1970s, when
they first gathered the data, there seemed to be a relationship between river
flow and salmon survival. Now later on,
it turned out that there was something wrong with these two data points (1973
and 1977), and the data got a lot flatter, even in 2001, but we don’t have time
to go into that.
The
important point is that from these fairly rudimentary observations, an enduring
policy prescription has emerged for helping salmon. It’s a simple syllogism really: (1) we can move the river faster, (2) that
moves the salmon faster, and (3) if they move faster, they spend less time in
the reservoir death zone and their survival will be higher.
Each
of these statements can be tested for truth.
Starting with the third one, by 1993, when the first accurate
measurements of salmon survival in reservoirs were obtained, the results were
so utterly contrary to the death zone theory that the experiments had to be
done over and over and over and over again before biologists would believe
them. The reservoirs were not death
zones at all. Young salmon die at higher
rates both above the dams and below them.
But
this had absolutely no effect on salmon policy.
You have probably heard the old expression there are lies, damned lies,
and statistics. The modern version of
that probably ought to go: there are
lies, there are damned lies, there are statistics, and then . . . there are
computer models. And we began to see
what has become an epidemic of fraudulent computer models on this issue and
many others.
Now fraud is a serious charge, and I do not make it lightly. One important feature of computer models is what factors are taken into consideration in the model. Here is a graph of salmon survival versus flow over hundreds of observations.
If I may digress again, imagine that salmon
scientists were engineers selling you a car, and if we press on the accelerator
(analogizing to more flow), this haze of dots would represent that with this
salmon engineer car, sometimes it goes backwards, and sometimes forwards.
What
I want to focus on is these few points down here with low flow and low
survival. They all are represented by
circles, and all come from the low flow year of 2001. And they all have one thing in common: high river temperatures. And young salmon die a lot more rapidly with
higher river temperatures, because the things in the river are cold blooded things,
and when the water warms up, they get hungrier and eat more salmon.
But if you build computer models, and just leave temperature out of them, you can take the effects that arise from temperature, and pretend that they arise from flow. So some scientists built models with temperature, and some without. Models with temperature have an interesting characteristic: they actually fit reality; they have predictive power. Here for example is a model developed by Professor Anderson, who labored in this field for about a decade, figured it out, published his model.
The model was ignored, just like Oliver
Wendell Holmes and all the other doctors, and Dr. Anderson has moved on on to
other things, but it is a remarkable achievement.
Models
that just use flow have a harder time, since there is very little correlation
between flow and survival. The cloud of
dots slide I just showed you pretty much proves that; here is some additional
data disaggregated by year, and you can see sometimes flow is positively
associated with survival, and sometimes negatively
associated.
So no matter what kind of model we run this
data through, there is really nothing there.
Now
let’s look at another premise of the “more flow” theory: we can make fish move down the river faster
by making the river move faster. Nature
runs that experiment for us every year with natural flow variations, and the
remarkable thing is that over enormous flow variations, the fish tend to arrive
down at the bottom of the river at the same time every year.
Here
is a chart that the State of
The 50% column represents the date half the
fish get to the bottom of the River. You
can see that in the year 2001, with less than half the flow of most years, the
fish were only about 0.6 days later (the median passage date). Yet on the very same page,
Over
the years I have seen the government scientists use fudge factors with negative
survival to try and make their models fit the actual data. By now, though, the whole idea of testing the
models against reality just got shoved under the rug. Policy is made by having the person with the
most power hold up something they call science, whether or not it fits reality. And the disconnect between reality and policy
grows stronger and stronger.
I
want to speculate a little bit about how so many people can be so blind, and I
think the root of the problem, like the root of so many other public problems,
is the federal government. You may have
heard that our federal government is a government of limited powers, but that
is no longer true, because the same federal courts that refuse to address the
problem of truth in government decisionmaking also decided, notwithstanding
that quaint idea of a Constitution, that the federal government has the powers
to (1) print paper money; and (2) spend that paper on whatever it wants.
And
after WWII, the Cold Warriors
decided, that “science is the responsibility of government because new
scientific knowledge vitally affects our health, our jobs, and our national
security”. And so rivers of federal
money flowed out of
One
version of the Golden Rule, the non-Biblical one, is that he who has the gold,
rules. And that is true in science. When those in charge of the purse strings are
funding science, they can shape that science to support their political
positions.
This
is not just a problem with salmon science; there is a lot of literature in the
area of medical research, for example, showing how NIH committees wind up
funding the same wrong ideas over and over and over again.
And
the people involved just seem to lose their capacity to discern scientific
truth. Again, this is not a particularly
unusual phenomenon. Upton Sinclair once
remarked: "It is difficult to get a
man to understand something when his salary depends on
his not understanding it." And here
in the Northwest, we have literally billions of dollars in salaries going out
to an army of scientists who just can’t seem to understand ecological problems
and solve them, because if they understood them, they’d have to find new work.
And
there is really only one antidote for this.
We have to recover their ability to distinguish between facts and
opinions. When people stand up in front
of you like Dr. Haesker, and wave a bottle of vodka and a hot dog around to show
how big the fish tags were in Dr. Welch’s study [presented by a previous
panelist, John McKern], this is not science.
This is an attempt to distract you from the science. Because Dr. Welch compared fish in the
Years
ago, Thomas Jefferson said: “The general
spread of the light of science has already laid open to every view the palpable
truth, that the mass of mankind has not been born with saddles on their back,
nor a favored few, booted and spurred, ready to ride them.” You all are going to have to work a lot
harder to figure out what the truth is, and hold your leaders to pursue things
that are true, or your future is going to get darker and darker because the
light of science is not spreading any more.
It is dimming.
© James Buchal, January 31,
2009
The presentation was not a success. Though Dr. Haeseker had called Dr. Welch’s
research “shameful”, and moved another panelist to describe his presentation as
a violation of American Fisheries Society and federal ethical standards, most
of the students just nodded numbly for him.
I was regarded as not operating in the “reality-based community”. Of course fish need more water. With that, the
proceedings moved on to a presentation by Gore acolyte Bill Bradbury on the
threat of climate change, a highly-polished presentation that carefully omits
any proof whatsoever that anything that mankind does has any measurable effect
on the climate.
You have permission to reprint this article, and are encouraged to do so. The sooner people figure out what's going on, the quicker we'll have more fish in the rivers.
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