Hempel Notes:
1. Problem with Francesco Sizi’s objection to Galileo: His “rule of seven” is not a valid
scientific explanation.
2. Two requirements for scientific laws:
a. Explanatory Relevance: explanatory information adduced provides good grounds for
believing that the phenomenon to be explained did, or does, indeed occur. This must
be met if we are to be entitled to say that it is explained.
b. Testability: the statements constituting a scientific explanation must be capable of
empirical test.
3. Explanatory relevance:
a. Why is the number of holes in the head not relevant to the number of planets?
i. It may have been relevant in the paradigm of the day.
1. Explanandum could be logically deduced from the explanans.
2. Hempel wants to exclude the rule of seven as false immediately.
3. Putnam’s schema III: have theory, have auxiliary hypothesese, trying
to figure out what they will predict. If you make an error here you
might have an explanation that is irrelevant to the explanandum.
4. Sansom: relevance is typically going to be a minor issue. People will
seldom propose explanations that are irrelevant by their own standards.
ii. Is relevance always relative to a paradigm?
1. A law is accepted as truth based on the paradigm of the time.
2. We might be able to say: given what we know now, is it relevant or
not?
iii. Why is it not relevant today?
1. No causal mechanism.
2. It was seen as “just the way the world was.”
3. Today we take explanation to reveal causal connections between
things, not just “the way the world is.”
4. The search for causal connections was a change in
5. We’ve rejected the rule of seven. Sometimes things are eight.
4. Are there examples of scientific statements or laws that cannot be tested?
a. Undeniable forces of the Newtonian paradigm?
b. Does not necessarily make them untestable. You can test them based on whether they
predict phenomena that you find in nature. Of course, if your predictions come out
false, you can adjust your auxiliary hypotheses.
i. Kuhnian view: Good Newtonians might come up with new explanations, but
they will still be testable. Paradigm lasts despite particular evidence, but
particular explanations are given up.
c. Some fundamental laws are “inexplicable”: are these laws testable?
i. Schlick: some fundamental laws are needed to test other assumptions.
ii. We don’t test things in isolation; we need a theory. Is it hierarchical, in that
we always need the most fundamental theory (and can’t test it), or is the
reticulated model (Laudan) enough to allow us to test these basic theories?
iii. Newtonian gravity makes no predictions in isolation, but it will once you have
auxiliary hypotheses. You could in principle falsify the set of theory plus
auxiliary hypotheses. If, faced with that choice, you always choose (or are
logically forced to choose) the auxiliary hypotheses, then the hierarchical
model is correct.
iv. Einstein vs. Newton: stars moving behind the sun. We were able to test those
because everyone agreed on the relevant auxiliary hypotheses, and they used
those to test the viability of the theories. So there might be examples of
auxiliary hypotheses that everyone agrees on which can adjudicate theories.
v. Test of the fundamental laws might only be possible if there’s an articulated
rival theory which allows you to test those laws.
1. It is a logical possibility that scientists’ best theory is bad (rubbish!).
Might not always be a “best” theory. Is the best theory always without
anomaly to the extent that people consider it true?
2. In physiology: yes, there is usually a best theory, and people proceed
on the assumption that the theory is true. You test little bits of the
theory and slowly build it further.
3. It does seem like you need to assume the truth of your theory to
proceed.
vi. If a theory is quite successful as a whole, this is an indirect test of the theory’s
assumptions. Even if the theory is not directly tested, the success of the
theory lends it support.
5. Scientific honesty:
a. Referees are not responsible for catching scientists in lying. They’re concerned with
methodology, the inferences drawn from the data, etc.
b. When scientists lie, we might expect that the research based on that lie will flounder,
and when it does, scientists will go back to that research in an attempt to falsify it.
6. Hempel’s “laws” might be considered “theories” in Putnam’s sense. Schema II examples
will be Hempel explanations, but any of the schemas (I-III) will be acceptable to Hempel.
7. Deductive-nomological explanation:
a. Universal laws: whenever and wherever conditions of a specific kind occur,
conditions of another kind necessarily occur.
b. Accidental generalizations: Universal statement that is true, but didn’t need to be true.
It is true by accident.
c. Reason for this distinction (depends in part on the scientific laws of the time): What
we think about the laws of nature and accidental generalization is contingent on our
theories.
d. On the Humean view, all laws of nature will just be accidental generalizations.
Causation cannot be observed and cannot be deduced. We assume the world is causal
in a certain way, and whenever we see the same thing happen after another thing, we
assume it is a law.
i. The problem is that it’s very unclear why a Humean doesn’t think he can’t
jump over a building. If he hasn’t tried to jump over a building before, he
doesn’t know he can’t.
ii. There’s nothing which stops the world from just completely changing.
iii. There’s nothing in the world making the world follow those rules. No
necessity to it.
iv. Everyone is by nature a realist. We don’t just think there are causal processes.
We think there is a part of the world making it have to go that way. When
you try to describe what that entity is, it seems impossible. We just imagine
that there is something that makes electrons avoid other electrons.
v. We can’t directly perceive the causation, but it’s just how we function. We
assume it’s just a causally orderly place.
8. Probabilistic explanation (probabilistic laws):
a. Explanandum is highly probable given the explanans.
b. Old view: in order to accurately calculate probabilities of different events, the events
must be equiprobable and statistically independent.
c. Hempel’s view: [probabilities are the] “ideal values that the actual frequencies tend to
assume as they become increasingly stable” (310). What you would get the more
tests you run!
d. In the case where there are equiprobable alternatives, a principle of sufficient reason
might explain it: there is no reason why a die would roll a “1” 1/6 times.
e. Hempel takes probability to mean a long term propensity, and nothing else.
f. Is probabilistic explanation merely shorthand for a more thoroughly mechanical
(deductive-nomological) explanation?
i. Statistics and probability theory is abundant in science. It is highly useful.
Sansom bets that all of those probabilities are not due to quantum phenomena.
They may usually be due to a lack of information.
ii. Hempel: due to this, you should always look for the most specific class you
can that has as many of the relevant variables as possible. You want the
highest probability of the outcome possible. You want to get as close to
deductive-nomological explanations.