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  1. O velho e novo problema da indução.Eros Carvalho - manuscript
    Neste texto inrodutório, apresento brevemente o que normalmente se entende pelo velho problema da indução e, em seguida, apresento um pouco mais detidamente, acentuando as diferenças e semelhanças, o novo enigma da indução.
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  2. Montague Reduction, Confirmation, and the Syntax-Semantics Relation.Stephan Hartmann & Kristina Liefke - manuscript
    Intertheoretic relations are an important topic in the philosophy of science. However, since their classical discussion by Ernest Nagel, such relations have mostly been restricted to relations between pairs of theories in the natural sciences. In this paper, we present a model of a new type of intertheoretic relation, called 'Montague Reduction', which is assumed in Montague's framework for the analysis and interpretation of natural language syntax. To motivate the adoption of our new model, we show that this model extends (...)
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  3. Fragmentation and Old Evidence.Will Fleisher - 2023 - Episteme 20 (3):542-567.
    Bayesian confirmation theory is our best formal framework for describing inductive reasoning. The problem of old evidence is a particularly difficult one for confirmation theory, because it suggests that this framework fails to account for central and important cases of inductive reasoning and scientific inference. I show that we can appeal to the fragmentation of doxastic states to solve this problem for confirmation theory. This fragmentation solution is independently well-motivated because of the success of fragmentation in solving other problems. I (...)
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  4. Confirmation, Coherence and the Strength of Arguments.Stephan Hartmann & Borut Trpin - 2023 - Proceedings of the Annual Meeting of the Cognitive Science Society 45:1473-1479.
    Alongside science and law, argumentation is also of central importance in everyday life. But what characterizes a good argument? This question has occupied philosophers and psychologists for centuries. The theory of Bayesian argumentation is particularly suitable for clarifying it, because it allows us to take into account in a natural way the role of uncertainty, which is central to much argumentation. Moreover, it offers the possibility of measuring the strength of an argument in probabilistic terms. One way to do this, (...)
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  5. (Almost) all evidence is higher-order evidence.Brian Hedden & Kevin Dorst - 2022 - Analysis 82 (3):417-425.
    Higher-order evidence is evidence about what is rational to think in light of your evidence. Many have argued that it is special – falling into its own evidential category, or leading to deviations from standard rational norms. But it is not. Given standard assumptions, almost all evidence is higher-order evidence.
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  6. What is the Statistical Inference? : An Invitation to Carnap's inductive Logic.Yusuke Kaneko - 2022 - The Basis : The Annual Bulletin of Research Center for Liberal Education 12:91-117.
    Although written in Japanese, what the statistical inference is philosophically investigated.
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  7. Is an Increase in Probability Always an Increase in Evidential Support?Artūrs Https://Orcidorg Logins - 2022 - Erkenntnis 87 (3):1231-1255.
    Peter Achinstein has argued at length and on many occasions that the view according to which evidential support is defined in terms of probability-raising faces serious counterexamples and, hence, should be abandoned. Proponents of the positive probabilistic relevance view have remained unconvinced. The debate seems to be in a deadlock. This paper is an attempt to move the debate forward and revisit some of the central claims within this debate. My conclusion here will be that while Achinstein may be right (...)
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  8. Other stars, other planets, and other life: a primer that goes two‑thirds of the way. [REVIEW]Marc Champagne - 2021 - Metascience 30 (1):153–156.
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  9. A Conflict between Indexical Credal Transparency and Relevance Confirmation.Joel Pust - 2021 - Philosophy of Science 88 (3):385-397.
    According to the probabilistic relevance account of confirmation, E confirms H relative to background knowledge K just in case P(H/K&E) > P(H/K). This requires an inequality between the rational degree of belief in H determined relative to two bodies of total knowledge which are such that one (K&E) includes the other (K) as a proper part. In this paper, I argue that it is quite plausible that there are no two possible bodies of total knowledge for ideally rational agents meeting (...)
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  10. On the Origins of Old Evidence.Benjamin Eva & Stephan Hartmann - 2020 - Australasian Journal of Philosophy 98 (3):481-494.
    The problem of old evidence, first described by Glymour [1980], is still widely regarded as one of the most pressing foundational challenges to the Bayesian account of scientific reasoning. Many solutions have been proposed, but all of them have drawbacks and none is considered to be definitive. Here, we introduce and defend a new kind of solution, according to which hypotheses are confirmed when we become more confident that they provide the only way of accounting for the known evidence.
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  11. The Problem of New Evidence: P-Hacking and Pre-Analysis Plans.Zoe Hitzig & Jacob Stegenga - 2020 - Diametros 17 (66):10-33.
    We provide a novel articulation of the epistemic peril of p-hacking using three resources from philosophy: predictivism, Bayesian confirmation theory, and model selection theory. We defend a nuanced position on p-hacking: p-hacking is sometimes, but not always, epistemically pernicious. Our argument requires a novel understanding of Bayesianism, since a standard criticism of Bayesian confirmation theory is that it cannot represent the influence of biased methods. We then turn to pre-analysis plans, a methodological device used to mitigate p-hacking. Some say that (...)
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  12. Channels’ Confirmation and Predictions’ Confirmation: From the Medical Test to the Raven Paradox.Chenguang Lu - 2020 - Entropy 22 (4):384.
    After long arguments between positivism and falsificationism, the verification of universal hypotheses was replaced with the confirmation of uncertain major premises. Unfortunately, Hemple proposed the Raven Paradox. Then, Carnap used the increment of logical probability as the confirmation measure. So far, many confirmation measures have been proposed. Measure F proposed by Kemeny and Oppenheim among them possesses symmetries and asymmetries proposed by Elles and Fitelson, monotonicity proposed by Greco et al., and normalizing property suggested by many researchers. Based on the (...)
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  13. Hypothesis Testing in Scientific Practice: An Empirical Study.Moti Mizrahi - 2020 - International Studies in the Philosophy of Science 33 (1):1-21.
    It is generally accepted among philosophers of science that hypothesis testing is a key methodological feature of science. As far as philosophical theories of confirmation are con...
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  14. The Pursuit of Knowledge and the Problem of the Unconceived Alternatives.Fabio Sterpetti & Marta Bertolaso - 2020 - Topoi 39 (4):881-892.
    In the process of scientific discovery, knowledge ampliation is pursued by means of non-deductive inferences. When ampliative reasoning is performed, probabilities cannot be assigned objectively. One of the reasons is that we face the problem of the unconceived alternatives: we are unable to explore the space of all the possible alternatives to a given hypothesis, because we do not know how this space is shaped. So, if we want to adequately account for the process of knowledge ampliation, we need to (...)
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  15. Discrimination-Conduciveness and Observation Selection Effects.William Roche & Elliott Sober - 2019 - Philosophers' Imprint 19:1-26.
    We conceptualize observation selection effects (OSEs) by considering how a shift from one process of observation to another affects discrimination-conduciveness, by which we mean the degree to which possible observations discriminate between hypotheses, given the observation process at work. OSEs in this sense come in degrees and are causal, where the cause is the shift in process, and the effect is a change in degree of discrimination-conduciveness. We contrast our understanding of OSEs with others that have appeared in the literature. (...)
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  16. Quine and the Incoherence of the Indispensability Argument.Michael J. Shaffer - 2019 - Logos and Episteme 10 (2):207-213.
    It is an under-appreciated fact that Quine's rejection of the analytic/synthetic distinction, when coupled with some other plausible and related views, implies that there are serious difficulties in demarcating empirical theories from pure mathematical theories within the Quinean framework. This is a serious problem because there seems to be a principled difference between the two disciplines that cannot apparently be captured in the orthodox Quienan framework. For the purpose of simplicity let us call this Quine's problem of demarcation. In this (...)
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  17. Statistical Inference and the Replication Crisis.Lincoln J. Colling & Dénes Szűcs - 2018 - Review of Philosophy and Psychology 12 (1):121-147.
    The replication crisis has prompted many to call for statistical reform within the psychological sciences. Here we examine issues within Frequentist statistics that may have led to the replication crisis, and we examine the alternative—Bayesian statistics—that many have suggested as a replacement. The Frequentist approach and the Bayesian approach offer radically different perspectives on evidence and inference with the Frequentist approach prioritising error control and the Bayesian approach offering a formal method for quantifying the relative strength of evidence for hypotheses. (...)
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  18. Sir John F. W. Herschel and Charles Darwin: Nineteenth-Century Science and Its Methodology.Charles H. Pence - 2018 - Hopos: The Journal of the International Society for the History of Philosophy of Science 8 (1):108-140.
    There are a bewildering variety of claims connecting Darwin to nineteenth-century philosophy of science—including to Herschel, Whewell, Lyell, German Romanticism, Comte, and others. I argue here that Herschel’s influence on Darwin is undeniable. The form of this influence, however, is often misunderstood. Darwin was not merely taking the concept of “analogy” from Herschel, nor was he combining such an analogy with a consilience as argued for by Whewell. On the contrary, Darwin’s Origin is written in precisely the manner that one (...)
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  19. Is there a place in Bayesian confirmation theory for the Reverse Matthew Effect?William Roche - 2018 - Synthese 195 (4):1631-1648.
    Bayesian confirmation theory is rife with confirmation measures. Many of them differ from each other in important respects. It turns out, though, that all the standard confirmation measures in the literature run counter to the so-called “Reverse Matthew Effect” (“RME” for short). Suppose, to illustrate, that H1 and H2 are equally successful in predicting E in that p(E | H1)/p(E) = p(E | H2)/p(E) > 1. Suppose, further, that initially H1 is less probable than H2 in that p(H1) < p(H2). (...)
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  20. Is evidence of evidence evidence? Screening-off vs. no-defeaters.Roche William - 2018 - Episteme 15 (4):451-462.
    I argue elsewhere (Roche 2014) that evidence of evidence is evidence under screening-off. Tal and Comesaña (2017) argue that my appeal to screening-off is subject to two objections. They then propose an evidence of evidence thesis involving the notion of a defeater. There is much to learn from their very careful discussion. I argue, though, that their objections fail and that their evidence of evidence thesis is open to counterexample.
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  21. How Explanation Guides Confirmation.Nevin Climenhaga - 2017 - Philosophy of Science 84 (2):359-68.
    Where E is the proposition that [If H and O were true, H would explain O], William Roche and Elliot Sober have argued that P(H|O&E) = P(H|O). In this paper I argue that not only is this equality not generally true, it is false in the very kinds of cases that Roche and Sober focus on, involving frequency data. In fact, in such cases O raises the probability of H only given that there is an explanatory connection between them.
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  22. A condition for transitivity in high probability.William Roche - 2017 - European Journal for Philosophy of Science 7 (3):435-444.
    There are many scientific and everyday cases where each of Pr and Pr is high and it seems that Pr is high. But high probability is not transitive and so it might be in such cases that each of Pr and Pr is high and in fact Pr is not high. There is no issue in the special case where the following condition, which I call “C1”, holds: H 1 entails H 2. This condition is sufficient for transitivity in high (...)
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  23. Confirmation, Increase in Probability, and the Likelihood Ratio Measure: a Reply to Glass and McCartney.William Roche - 2017 - Acta Analytica 32 (4):491-513.
    Bayesian confirmation theory is rife with confirmation measures. Zalabardo focuses on the probability difference measure, the probability ratio measure, the likelihood difference measure, and the likelihood ratio measure. He argues that the likelihood ratio measure is adequate, but each of the other three measures is not. He argues for this by setting out three adequacy conditions on confirmation measures and arguing in effect that all of them are met by the likelihood ratio measure but not by any of the other (...)
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  24. Is Explanatoriness a Guide to Confirmation? A Reply to Climenhaga.William Roche & Elliott Sober - 2017 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 48 (4):581-590.
    We argued that explanatoriness is evidentially irrelevant in the following sense: Let H be a hypothesis, O an observation, and E the proposition that H would explain O if H and O were true. Then our claim is that Pr = Pr. We defended this screening-off thesis by discussing an example concerning smoking and cancer. Climenhaga argues that SOT is mistaken because it delivers the wrong verdict about a slightly different smoking-and-cancer case. He also considers a variant of SOT, called (...)
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  25. Novelty versus Replicability: Virtues and Vices in the Reward System of Science.Felipe Romero - 2017 - Philosophy of Science 84 (5):1031-1043.
    The reward system of science is the priority rule. The first scientist making a new discovery is rewarded with prestige, while second runners get little or nothing. Michael Strevens, following Philip Kitcher, defends this reward system, arguing that it incentivizes an efficient division of cognitive labor. I argue that this assessment depends on strong implicit assumptions about the replicability of findings. I question these assumptions on the basis of metascientific evidence and argue that the priority rule systematically discourages replication. My (...)
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  26. Three Arguments for Absolute Outcome Measures.Jan Sprenger & Jacob Stegenga - 2017 - Philosophy of Science 84 (5):840-852.
    Data from medical research are typically summarized with various types of outcome measures. We present three arguments in favor of absolute over relative outcome measures. The first argument is from cognitive bias: relative measures promote the reference class fallacy and the overestimation of treatment effectiveness. The second argument is decision-theoretic: absolute measures are superior to relative measures for making a decision between interventions. The third argument is causal: interpreted as measures of causal strength, absolute measures satisfy a set of desirable (...)
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  27. Sober as a Judge: Elliott Sober: Ockham’s Razors: A user’s manual. Cambridge: Cambridge University Press, 322pp, $29.99 , $99.99.Gordon Belot - 2016 - Metascience 25 (3):387-392.
    In Ockham's Razors: A User's Guide, Elliott Sober argues that parsimony considerations are epistemically relevant on the grounds that certain methods of model selection, such as the Akaike Information Criterion, exhibit good asymptotic behaviour and take the number of adjustable parameters in a model into account. I raise some worries about this form of argument.
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  28. Model robustness as a confirmatory virtue: The case of climate science.Elisabeth A. Lloyd - 2015 - Studies in History and Philosophy of Science Part A 49:58-68.
    I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independentlysupported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present climate (...)
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  29. Confirmation versus Falsificationism.Ray Scott Percival - 2015 - In Robin L. Cautin & Scott O. Lilienfeld (eds.), Encyclopedia of Clinical Psychology.
    Confirmation and falsification are different strategies for testing theories and characterizing the outcomes of those tests. Roughly speaking, confirmation is the act of using evidence or reason to verify or certify that a statement is true, definite, or approximately true, whereas falsification is the act of classifying a statement as false in the light of observation reports. After expounding the intellectual history behind confirmation and falsificationism, reaching back to Plato and Aristotle, I survey some of the main controversial issues and (...)
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  30. Model tuning in engineering: uncovering the logic.Katie Steele & Charlotte Werndl - 2015 - Journal of Strain Analysis for Engineering Design 51 (1):63-71.
    In engineering, as in other scientific fields, researchers seek to confirm their models with real-world data. It is common practice to assess models in terms of the distance between the model outputs and the corresponding experimental observations. An important question that arises is whether the model should then be ‘tuned’, in the sense of estimating the values of free parameters to get a better fit with the data, and furthermore whether the tuned model can be confirmed with the same data (...)
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  31. Neuroeconomics and Confirmation Theory.Christopher Clarke - 2014 - Philosophy of Science 81 (2):195-215.
    Neuroeconomics is a research programme founded on the thesis that cognitive and neurobiological data constitute evidence for answering economic questions. I employ confirmation theory in order to reject arguments both for and against neuroeconomics. I also emphasize that some arguments for neuroeconomics will not convince the skeptics because these arguments make a contentious assumption: economics aims for predictions and deep explanations of choices in general. I then argue for neuroeconomics by appealing to a much more restrictive (and thereby skeptic-friendly) characterization (...)
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  32. Evidence, Hypothesis, and Grue.Alfred Schramm - 2014 - Erkenntnis 79 (3):571-591.
    Extant literature on Goodman’s ‘New Riddle of Induction’ deals mainly with two versions. I consider both of them, starting from the (‘epistemic’) version of Goodman’s classic of 1954. It turns out that it belongs to the realm of applications of inductive logic, and that it can be resolved by admitting only significant evidence (as I call it) for confirmations of hypotheses. Sect. 1 prepares some ground for the argument. As much of it depends on the notion of evidential significance, this (...)
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  33. A note on confirmation and Matthew properties.Roche William - 2014 - Logic and Philosophy of Science 12:91-101.
    There are numerous (Bayesian) confirmation measures in the literature. Festa provides a formal characterization of a certain class of such measures. He calls the members of this class “incremental measures”. Festa then introduces six rather interesting properties called “Matthew properties” and puts forward two theses, hereafter “T1” and “T2”, concerning which of the various extant incremental measures have which of the various Matthew properties. Festa’s discussion is potentially helpful with the problem of measure sensitivity. I argue, that, while Festa’s discussion (...)
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  34. Failure of Calibration is Typical.Gordon Belot - 2013 - Statistics and Probability Letters 83:2316--2318.
    Schervish (1985b) showed that every forecasting system is noncalibrated for uncountably many data sequences that it might see. This result is strengthened here: from a topological point of view, failure of calibration is typical and calibration rare. Meanwhile, Bayesian forecasters are certain that they are calibrated---this invites worries about the connection between Bayesianism and rationality.
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  35. The Problem of Measure Sensitivity Redux.Peter Brössel - 2013 - Philosophy of Science 80 (3):378-397.
    Fitelson (1999) demonstrates that the validity of various arguments within Bayesian confirmation theory depends on which confirmation measure is adopted. The present paper adds to the results set out in Fitelson (1999), expanding on them in two principal respects. First, it considers more confirmation measures. Second, it shows that there are important arguments within Bayesian confirmation theory and that there is no confirmation measure that renders them all valid. Finally, the paper reviews the ramifications that this "strengthened problem of measure (...)
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  36. A problem for the alternative difference measure of confirmation.Nevin Climenhaga - 2013 - Philosophical Studies 164 (3):643-651.
    Among Bayesian confirmation theorists, several quantitative measures of the degree to which an evidential proposition E confirms a hypothesis H have been proposed. According to one popular recent measure, s, the degree to which E confirms H is a function of the equation P(H|E) − P(H|~E). A consequence of s is that when we have two evidential propositions, E1 and E2, such that P(H|E1) = P(H|E2), and P(H|~E1) ≠ P(H|~E2), the confirmation afforded to H by E1 does not equal the (...)
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  37. An impossibility theorem for amalgamating evidence.Jacob Stegenga - 2013 - Synthese 190 (12):2391-2411.
    Amalgamating evidence of different kinds for the same hypothesis into an overall confirmation is analogous, I argue, to amalgamating individuals’ preferences into a group preference. The latter faces well-known impossibility theorems, most famously “Arrow’s Theorem”. Once the analogy between amalgamating evidence and amalgamating preferences is tight, it is obvious that amalgamating evidence might face a theorem similar to Arrow’s. I prove that this is so, and end by discussing the plausibility of the axioms required for the theorem.
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  38. Coherence and Confirmation through Causation.Gregory Wheeler & Richard Scheines - 2013 - Mind 122 (485):135-170.
    Coherentism maintains that coherent beliefs are more likely to be true than incoherent beliefs, and that coherent evidence provides more confirmation of a hypothesis when the evidence is made coherent by the explanation provided by that hypothesis. Although probabilistic models of credence ought to be well-suited to justifying such claims, negative results from Bayesian epistemology have suggested otherwise. In this essay we argue that the connection between coherence and confirmation should be understood as a relation mediated by the causal relationships (...)
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  39. A verisimilitudinarian analysis of the Linda paradox.Gustavo Cevolani, Vincenzo Crupi & Roberto Festa - 2012 - VII Conference of the Spanish Society for Logic, Methodology and Philosphy of Science.
    The Linda paradox is a key topic in current debates on the rationality of human reasoning and its limitations. We present a novel analysis of this paradox, based on the notion of verisimilitude as studied in the philosophy of science. The comparison with an alternative analysis based on probabilistic confirmation suggests how to overcome some problems of our account by introducing an adequately defined notion of verisimilitudinarian confirmation.
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  40. A More Fulfilling (and Frustrating) Take on Reflexive Predictions.Matthew Kopec - 2011 - Philosophy of Science 78 (5):1249-1259.
    Even though social scientists continue to discuss the problems posed by self-fulfilling and self-frustrating predictions, philosophers of science have ignored the topic since the 1970s. Back then, the prevailing view was that the methodological problems posed by reflexive predictions are either minor or easily avoided. I believe that this consensus was premature, ultimately relying on an overly narrow understanding of the phenomenon. I present an improved way to understand reflexive predictions (framed in probabilistic terms) and show that, once such predictions (...)
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  41. Experimentation versus Theory Choice: A Social-Epistemological Approach.Marcel Weber - 2011 - In Hans Bernhard Schmid, Daniel Sirtes & Marcel Weber (eds.), Collective Epistemology. Ontos. pp. 20--203.
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  42. Asymmetries in prior conviction reasoning: Truth suppression effects in child protection contexts.Michelle B. Cowley-Cunningham - 2010 - Psychology, Crime and Law 3 (16):211-231.
    In three empirical studies we examined how people reason about prior convictions in child abuse cases. We tested whether the disclosure of similar prior convictions prompts a mental representation or an additive probative value (Criminal Justice Act, 2003). Asymmetrical use of similar priors were observed in three studies. A pilot study showed that disclosure of a second prior did not contribute a weight equivalent to that of the first disclosure. Study 1 showed jurors did not see left-handed evidence (i.e. matching (...)
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  43. Toward a Grammar of Bayesian Confirmation.Vincenzo Crupi, Roberto Festa & Carlo Buttasi - 2010 - In M. Suàrez, M. Dorato & M. Redéi (eds.), EPSA Epistemology and Methodology of Science: Launch of the European Philosophy of Science Association. Springer. pp. 73--93.
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  44. The Undetectable Difference: An Experimental Look at the ‘Problem’ of p-Values.William M. Goodman - 2010 - Statistical Literacy Website/Papers: Www.Statlit.Org/Pdf/2010GoodmanASA.Pdf.
    In the face of continuing assumptions by many scientists and journal editors that p-values provide a gold standard for inference, counter warnings are published periodically. But the core problem is not with p-values, per se. A finding that “p-value is less than α” could merely signal that a critical value has been exceeded. The question is why, when estimating a parameter, we provide a range (a confidence interval), but when testing a hypothesis about a parameter (e.g. µ = x) we (...)
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  45. Assessing theories, Bayes style.Franz Huber - 2008 - Synthese 161 (1):89-118.
    The problem addressed in this paper is “the main epistemic problem concerning science”, viz. “the explication of how we compare and evaluate theories [...] in the light of the available evidence” (van Fraassen, BC, 1983, Theory comparison and relevant Evidence. In J. Earman (Ed.), Testing scientific theories (pp. 27–42). Minneapolis: University of Minnesota Press). Sections 1– 3 contain the general plausibility-informativeness theory of theory assessment. In a nutshell, the message is (1) that there are two values a theory should exhibit: (...)
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  46. Hempel’s logic of confirmation.Franz Huber - 2008 - Philosophical Studies 139 (2):181-189.
    This paper presents a new analysis of C.G. Hempel’s conditions of adequacy for any relation of confirmation [Hempel C. G. (1945). Aspects of scientific explanation and other essays in the philosophy of science. New York: The Free Press, pp. 3–51.], differing from the one Carnap gave in §87 of his [1962. Logical foundations of probability (2nd ed.). Chicago: University of Chicago Press.]. Hempel, it is argued, felt the need for two concepts of confirmation: one aiming at true hypotheses and another (...)
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  47. Reply to Crupi et al.’s ‘Confirmation by Uncertain Evidence’.Franz Huber - 2008 - British Journal for the Philosophy of Science 59 (2):213-215.
    Crupi et al. propose a generalization of Bayesian confirmation theory that they claim to adequately deal with confirmation by uncertain evidence. Consider a series of points of time t0, . . . , ti, . . . , tn such that the agent’s subjective probability for an atomic proposition E changes from Pr0 at t0 to . . . to Pri at ti to . . . to Prn at tn. It is understood that the agent’s subjective probabilities change for (...)
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  48. Theories of Violence and the Explanation of Ultra-violent Behavior.Michael J. Shaffer & Patricia Turrisi - 2008 - In T. Levin (ed.), Violence: Mercurial Gestalt.
    Theorists in various scientific disciplines offer radically different accounts of the origin of violent behavior in humans, but it is not clear how the study of violence is to be scientifically grounded. This problem is made more complicated because both what sorts of acts constitute violence and what needs to be appealed to in explaining violence differs according to social scientists, biologists, anthropologists and neurophysiologists, and this generates serious problems with respect to even attempting to ascertain the differential bona fides (...)
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  49. On coherent sets and the transmission of confirmation.Franz Dietrich & Luca Moretti - 2005 - Philosophy of Science 72 (3):403-424.
    In this paper, we identify a new and mathematically well-defined sense in which the coherence of a set of hypotheses can be truth-conducive. Our focus is not, as usual, on the probability but on the confirmation of a coherent set and its members. We show that, if evidence confirms a hypothesis, confirmation is “transmitted” to any hypotheses that are sufficiently coherent with the former hypothesis, according to some appropriate probabilistic coherence measure such as Olsson’s or Fitelson’s measure. Our findings have (...)
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  50. The Logic of Confirmation.Franz Huber - 2005 - In O. Neumaier, C. Sedmak & M. Zichy (eds.), Philosophische Perspektiven. Beiträge zum VII. Internationalen Kongress der ÖGP. Ontos.
    The paper presents a new analysis of Hempel’s conditions of adequacy, differing from the one in Carnap. Hempel, so it is argued, felt the need for two concepts of confirmation: one aiming at true theories, and another aiming at informative theories. However, so the analysis continues, he also realized that these two concepts were conflicting, and so he gave up the concept of confirmation aiming at informative theories. It is then shown that one can have the cake and eat it: (...)
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