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Автор: Franz-Peter Griesmaier
Издательство: John Wiley & Sons Limited
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Жанр произведения: Математика
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isbn: 9781119758006
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of science who is trying to find the universal norms that govern science, can be learned from how scientists discover their hypotheses.

      However, the context of justification is a different matter. Once we have an explanation, in the form of a hypothesis or a more encompassing theory, we can legitimately ask whether or not we are justified in accepting that hypothesis or theory. On most accounts, a theory is rationally acceptable if it gets the data right for which it was invented, and also new data that hasn’t been observed so far. In other words, we see what predictions the theory makes about the world and then check whether those predictions come to pass. If they do, good; if not, bad. How to spell out “good” and “bad” in this context is the subject of the next main section on theory confirmation.

      However, this selection of what is worth observing by referring to our already accepted stock of theories has a somewhat surprising consequence. If it is true that what we deem worthy of observing today is constrained by theories we accept, and if those theories were based on observations deemed worthy of making, which in turn were constrained by prior theories, and so on, all the back to the “beginning of science,” it becomes quickly clear that our current theories are constrained by early observations through the historical trajectory of theories initiated by those observations. In other words, we have to acknowledge the possibility that what seems scientifically interesting today has been strongly shaped by the “starting point” of science. Had humanity been noticing things other than what it did notice, the scientific trajectory may have looked very different with the result that our current science might be different as well.

      3.2 Theory Appraisal

      Suppose you found a theory which you consider to be pretty convincing. Others don’t agree. What can you do? One thing to do is of course to show that the theory accounts for all the data – evidence – that are relevant to it. In particular, you are in good shape if you can show that your theory correctly predicts data that have not been collected yet. For example, suppose that a theory explains reductions in the Earth’s temperature in terms of periods of volcanic activity during which emitted material reflects solar energy. Suppose further that in 1979, a scientist predicted that after an eruption of 0.5 to 1.0 cubic miles of ejecta, global temperatures would drop by 0.1 degrees Celsius. And then came the eruption of Mount St. Helens which spewed 0.7 cubic miles of material into the atmosphere – and the Earth cooled by 0.1 degrees. Well, the theory would be looking pretty good! How exactly does this process work – what is its logic, as it were?

      3.2.1 Confirmation through Predictive Success

      One influential proposal for how to understand this process is Carl Gustav Hempel’s model of theory confirmation. It basically reduces confirmation to a two-step process. First, a scientist generates testable predictions from a theory. Second, the researcher determines whether or not those predictions are borne out by appropriate observations, which of course include measurement results and experimental outcomes. For Hempel, the first step was a matter of deductive logic. Here’s an example.

      Suppose that you want to defend the theory that the earth is spherical. The ancient philosopher Aristotle was one of the first to describe a test for this theory. The idea behind his attempt at confirmation is very simple. If the earth were spherical, we’d expect to see a ship that leaves the harbor to not only look smaller and smaller as it sails away, but to also disappear nonuniformly over the horizon. At the appropriate distance, we might be able to still make out the masts and the sails without seeing the hull of the ship anymore. So, the theory “The earth is spherical” predicts a partial disappearance of the ship. If you go to the harbor, you can actually make this observation – the ship disappears from the bottom-up, and the theory has been confirmed by this observation.

      Hempel summarized and generalized this example, and others, into the following model of theory confirmation:

      Theory predicts Observation

       Observation is made

      The first thing to notice here is that confirmation is different from proof. If a theory entails an observation and the observation is made, it doesn’t logically follow that the theory is true. To think otherwise would be to commit a logical fallacy. To see this, consider: “If it rains, the streets are wet. The streets are wet. Thus, it is raining.” But the conclusion doesn’t follow from the premises, because someone could have hosed down the streets, and that’s why they are wet. However, if the prediction is borne out, we can say that the theory has been confirmed to a certain degree. This in turn means that we have some reason for believing the theory.

      Here’s another example following the same pattern. Suppose I want to confirm the hypothesis that all ravens are black. How would I do this? Following Hempel’s advice, I infer a prediction from my hypothesis and then determine whether it is true or not. What follows from the claim that all ravens are black? One thing that comes to mind immediately is that the next raven I see will be black. Thus,

      Raven Theory predicts “Next raven is black”

       Observation “Next raven is black” is made

       Raven Theory is (better) confirmed

      What’s important about this second example is that the theory talks about all ravens – past, present, and future, and everywhere they exist. Suppose I have seen 200 ravens, and all of them have been black. Thus, I inductively infer my Black Raven theory. Now I want to confirm it by using Hempel’s procedure, as we have just done. But, seriously, how much of a confirmation can that one black raven provide? Remember, my theory talks about all ravens.

      3.2.2 Falsification to the Rescue