Evidence, Explanation, and Realism: Essays in Philosophy of Science

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Evidence, Explanation, and Realism: Essays in Philosophy of Science The essays in this volume address three fundamental questions in the philosophy of science: What is required for some fact to be evidence for a scientific hypothesis? What does it mean to say that a scientist or a theory explains a phenomenon? Should scie. An ad hoc hypothesis then is one formed to address a specific problem—such as the problem of immunizing a particular theory from falsification by anomalous data and thereby accommodating that data.

Consequently what makes a hypothesis ad hoc, in the ordinary English sense of the term, has nothing to do with the content of the hypothesis but simply with the motivation of the scientist who proposes it—and it is unclear why there would be anything suspicious about such a motivation. In the case of an ad hoc theory modification introduced to resolve an anomaly for a theory, the modified theory had no testable consequences other than those of the original theory.

Popper offered two explications of why ad hoc hypotheses were suspect. One was that if we offer T as an explanation of f , but then cite f as the only reason we have to believe T , Popper claims that we have engaged in reasoning that is suspicious for reasons of circularity Popper —3. But in the above example, while f is offered as evidence for T , T is offered as an explanation of not as evidence for f —and thus there is no circular reasoning Bamford Ad hoc hypotheses, for Popper, suffer from a lack of independent testability and thus reduce or at least fail to increase the testability of the theories they modify cf.

Zahar argued that a hypothesis was ad hoc 1 if it had no novel consequences as compared with its predecessor i. Another approach proposes that a hypothesis H introduced into a theory T in response to an experimental result E is ad hoc if it is generally unsupported and appears to be a superficial attempt to paper over deep problems with a theory that is actually in need of substantive revision.


Thus to level the charge of ad hocness against a hypothesis was actually to direct serious skepticism toward the theory the hypothesis was meant to rescue. Confirmations should count only if they are the result of risky predictions; that is to say, if, unenlightened by the theory in question, we should have expected an event which was incompatible with the theory in question, we should have expected an event which was incompatible with the theory—an event which would have refuted the theory.

Popper and subsequently Lakatos thereby endorsed a temporal condition of novelty—a prediction counts as novel is if it is not known to be true or is expected to prove false at the time the theory is constructed. But it was fairly obvious that this made important questions of confirmation turn implausibly on the time at which certain facts were known. In subsequent literature, the so-called heuristic conception of novelty has been identified with use-novelty—it was further articulated in Worrall and Another approach argues that a novel consequence of a theory is one that was not known to the theorist at the time she formulated the theory—this seems like a version of the temporal conception, but this point appeals implicitly to the heuristic conception: if a theorist knew of a result prior to constructing a theory which explains it, it may be difficult to determine whether that theorist somehow tailored the theory to fit the fact e.

A knowledge-based conception is thus the best that we can do to handle this difficulty Gardner The heuristic conception is, however, deeply controversial—because it makes the epistemic assessment of theories curiously dependent on the mental life of their constructors, specifically on the knowledge and intentions of the theorist to build a theory that accommodated certain data rather than others.

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For similar comments see Gardner 6; Thomason ; Schlesinger 33; Achinstein —; and Collins Another approach notes that scientists operate with competing theories and that the role of novel confirmations is to decide between them. Operating in a Lakatosian framework, Frankel claims a consequence was novel with respect to a theory and its research programme if it is not similar to a fact which already has been used by members of the same research program to support a theory designed to solve the same problems as the theory in question Also in a Lakatosian framework, Nunan claims that a consequence is novel if it has not already been used to support, or cannot readily be explained in terms of, a theory entertained in some rival research program Global predictivism holds that predictions are always superior to accommodations, while local predictivism holds that this only holds in certain cases.

Strong predictivism asserts that prediction is intrinsically superior to accommodation, whereas weak predictivism holds that predictive success is epistemically relevant because it is symptomatic of other features that have epistemic import. The distinction between strong and weak predictivism cross classifies with the distinctions between different types of novelty.

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For example, one could maintain that temporal predictions are intrinsically superior to temporal accommodations strong temporal predictivism or that temporal predictions were symptomatic of some other good-making feature of theories weak temporal predictivism; Hitchcock and Sober 3—5. These distinctions will be further illustrated below. A version of global strong heuristic predictivism is the null support thesis that holds that theories never receive confirmation from evidence they were built to fit—precisely because of how they were built. This thesis has been attributed to Bacon and Descartes Howson Popper and Lakatos also subscribe to this thesis, though it is important to remember that they do not recognize any form of confirmational support—even from successful predictions.

But others who maintained that successful predictions do confirm theories nonetheless endorsed the null support hypothesis. Giere provides the following argument:. If the known facts were used in constructing the model and were thus built into the resulting hypothesis…then the fit between these facts and the hypothesis provides no evidence that the hypothesis is true [since] these facts had no chance of refuting the hypothesis.

The idea is that the way the theory was built provided an illegitimate protection against falsification by the facts—hence the facts cannot support the theory.

  1. 2. Ad Hoc Hypotheses.
  2. William H. Miller III Department of Philosophy?
  3. Theories of Explanation;
  4. Giere has confused what is in effect a random variable the experimental setup or data source E together with its set of distinct possible outcomes with one of its values the outcome e …Moreover, it makes perfectly good sense to say that E might well have produced an outcome other than the one, e , it did as a matter of fact produce.

    Howson ; see also Collins Howson argued in a series of papers , , that the null support thesis is falsified using simple examples, such as the following:. An urn contains an unknown number of black and white tickets, where the proportion p of black tickets is also unknown. This hypothesis is, according to standard statistical lore, very well supported by the data from which it is clearly constructed. In this case there is, Howson notes, a background theory that supplies a model of the experiment it is a sequence of Bernoulli trials, viz.

    As long as we have good reason to believe that this model applies, our inference to the high probability of the hypothesis is a matter of standard statistical methodology, and the null support thesis is refuted. It has been argued that one of the limitations of Bayesianism is that it is fatally committed to the clearly false null support thesis Glymour Thus followed an extensive literature on the old evidence problem which will not be summarized here see, e. Patrick Maher , , presented a seminal thought experiment and a Bayesian analysis of its predictivist implications.

    The thought experiment contained two scenarios: in the first scenario, a subject the accommodator is presented with E , a sequence of 99 coin flips. E forms an apparently random sequence of heads and tails. The accommodator is then instructed to tell us the outcome of the first flips—he responds by reciting E and then adding the prediction that the th toss will be heads—the conjunction of E and this last toss is T.

    In the other scenario, another subject the predictor is asked to predict the first flip outcomes without witnessing any outcomes—the predictor endorses theory T. The question is in which of these two scenarios is T better confirmed.

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    Maher [] shows that this assumption can be surrendered and a continuum of degrees of reliability of scientific methods assumed; the predictivist result is still generated. In qualitative terms, where M generates T and thus predicts E without input of evidence E , we should infer that it is much more likely that the method that generated E is reliable than that E just happened to turn out true though R was no better than a random method.

    In other words, we judge that we are much more likely to stumble on a subject using a reliable method M of coin flip prediction than we are to stumble on a sequence of 99 true flip predictions that were merely lucky guesses—because. Maher has articulated a weak heuristic predictivism because he claims that predictive success is symptomatic of the use of a reliable discovery method. It was noted above that ad hoc hypotheses stand under suspicion for various reasons, one of which was that a hypothesis that was proposed to resolve a particular difficulty may not cohere well with the theory it purports to save or relevant background beliefs.

    For example, the phlogiston theory claimed that substances emitted phlogiston while burning. However, it was established that some substances actually gained weight while burning. Some argue, however that scientists are imperfect judges of such coherence—a scientist who accommodates some datum may think his accommodation is fully coherent, while his peers may have a more accurate and objective view that it is not. Lange offers an alternate interpretation of the coin flip example that claims that the process of accommodation unlike prediction tends to generate theories that are not strongly supported by confirming data.

    Again we imagine a predictor who correctly predicts 99 outcomes in advance and an accommodator who witnesses them. Both the predictor and the accommodator predict that the th outcome will be tails. Now there is little or no difference in our assessed probability that the subject will correctly predicted the th outcome. Lange But the success of the predictor in predicting the initial 99 outcomes strongly implies that the sequence is not an arbitrary conjunction after all:.

    Having judged it not to be an arbitrary conjunction, we are now prepared to recognize the first 99 outcomes as strongly confirming the prediction in the th case. What accounts for the difference between the two scenarios, in other words, is not primarily whether E was predicted or accommodated, but whether we judge H to be an arbitrary conjunction, and thus whether E provides support for the remaining portion of H. Lange goes on to suggest that in actual science the practice of constructing a hypothesis by way of accommodating known evidence has a tendency to generate arbitrary conjunctions.

    When evidence is predicted by a theory, by contrast, this is typically because the theory is not an arbitrary conjunction. The evidential significance of prediction and accommodation for Lange is that they tend to be correlated negatively and positively with the construction of theories that are arbitrary conjunctions. Deborah Mayo has argued particularly in Mayo , , and that the intuition that predictivism is true derives from a premium on severe tests of hypotheses.

    A test of a hypothesis H is severe to the extent that H is unlikely to pass that test if H is false. Here novelty and severity appear to coincide—but Mayo observes that there are cases in which they come apart. Giere , affirms that evidence H was built to fit cannot support H because, given how H was built, it was destined to fit that evidence. Mayo summarizes his reasoning as follows:.

    However, 1 is false when so interpreted. Mayo illustrates this with a simple example: let the evidence e be a list of SAT scores from students in a particular class. Now of course h has been use-constructed from e.