Corey Dethier
Biographic Data
| ID | 1084110 |
|---|---|
| NAME | Corey Dethier |
| GIVEN NAMES | Corey |
| FAMILY NAME | Dethier |
| SIGNATURE | DETHIER C |
| AFFILIATIONS | Leibniz University Hannover |
| ORCID | 0000-0002-1240-8391 |
| VERIFIED | Yes |
| TOTAL WORKS | 16 |
| TOTAL CITATIONS | 7 |
| AUTHOR COUNT | 16 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
What use the Realist for a Theory of Truth?
Recently, Hasok Chang has argued that we should adopt a pragmatic account of truth on which truth is constituted by practical success. Central to his argument is the claim that truth in this sense can be pursued and that other senses of truth can’t be. In this paper, I present a dilemma for Chang’s view. Either practical success constitutes truth in a way that implies infallibility—a conclusion that I’ll argue is untenable—or the argument from pu…
How do you assert a graph? Towards an account of depictions in scientific testimony
I extend the literature on norms of assertion to the ubiquitous use of graphs in scientific papers and presentations, which I term “graphical testimony.” On my account, the testimonial presentation of a graph involves commitment to both (a) the in‐context reliability of the graph's framing devices and (b) the perspective‐relative accuracy of the graph's content. Despite apparent disagreements between my account and traditional accounts of asserti…
Who’s Afraid of the Base-Rate Fallacy
This paper evaluates the back-and-forth between Mayo, Howson, and Achinstein over whether classical statistics commits the base-rate fallacy. I show that Mayo is correct to claim that Howson’s arguments rely on a misunderstanding of classical theory. I then argue that Achinstein’s refined version of the argument turns on largely undefended epistemic assumptions about “what we care about” when evaluating hypotheses. I end by suggesting that Mayo’s…
Stability, Robustness Reasoning, and Measuring the Human Contribution to Warming
In principle, inaccuracies in the representation of the climate’s internal variability could undermine the measurement of the human contribution to warming. Equally in principle, the success of the measurement practice could provide evidence that our assumptions about internal variability are correct. I argue that neither condition obtains: current measurement practices do not provide evidence for the accuracy of our assumptions precisely because…
The Unity of Robustness: Why Agreement Across Model Reports is Just as Valuable as Agreement Among Experiments
A number of philosophers of science have argued that there are important differences between robustness in modeling and experimental contexts, and—in particular—many of them have claimed that the former is non-confirmatory. In this paper, I argue for the opposite conclusion: robust hypotheses are confirmed under conditions that do not depend on the differences between and models and experiments—that is, the degree to which the robust hypothesis i…
Methodologies of Uncertainty: Philosophical Disagreement in the Economics of Climate Catastrophes
Interpreting the Probabilistic Language in IPCC Reports
The Intergovernmental Panel on Climate Change (IPCC) often qualifies its statements by use of probabilistic “likelihood” language. In this paper, I show that this language is not properly interpreted in either frequentist or Bayesian terms—simply put, the IPCC uses both kinds of statistics to calculate these likelihoods. I then offer a deflationist interpretation: the probabilistic language expresses nothing more than how compatible the evidence …
The Cooperative Origins of Epistemic Rationality
Against “Possibilist” Interpretations of Climate Models
Climate scientists frequently employ heavily idealized models. How should these models be interpreted? Some philosophers have advanced a possibilist interpretation: climate models stand in for possible scenarios that could occur but do not provide information about how probable those scenarios are. This article argues that possibilism is (1) undermotivated, (2) incompatible with successful practices in the science, and (3) unable to correct for k…
Supposition and (Statistical) Models
In a recent paper, Sprenger advances what he calls a “suppositional” answer to the question of why a Bayesian agent’s degrees of belief should align with the probabilities found in statistical models. I show that Sprenger’s account trades on an ambiguity between hypothetical and subjunctive suppositions and cannot succeed once we distinguish between the two
Accuracy, probabilism, and the insufficiency of the alethic
The best and most popular argument for probabilism is the accuracy-dominance argument, which purports to show that alethic considerations alone support the view that an agent’s degrees of belief should always obey the axioms of probability. I argue that extant versions of the accuracy-dominance argument face a problem. In order for the mathematics of the argument to function as advertised, we must assume that every omniscient credence function is…
When is an ensemble like a sample? “Model-based” inferences in climate modeling
Climate scientists often apply statistical tools to a set of different estimates generated by an “ensemble” of models. In this paper, I argue that the resulting inferences are justified in the same way as any other statistical inference: what must be demonstrated is that the statistical model that licenses the inferences accurately represents the probabilistic relationship between data and target. This view of statistical practice is appropriatel…
Science, assertion, and the common ground
I argue that the appropriateness of an assertion is sensitive to context—or, really, the “common ground”—in a way that hasn’t previously been emphasized by philosophers. This kind of context-sensitivity explains why some scientific conclusions seem to be appropriately asserted even though they are not known, believed, or justified on the available evidence. I then consider other recent attempts to account for this phenomenon and argue that if the…
Calibrating statistical tools: Improving the measure of Humanity's influence on the climate
Forces in a true and physical sense: From mathematical models to metaphysical conclusions
Climate Models and the Irrelevance of Chaos
Philosophy of science has witnessed substantial recent debate over the existence of a structural analogue of chaos, which is alleged to spell trouble for certain uses of climate models. The debate over the analogy can and should be separated from its alleged epistemic implications: chaos-like behavior is neither necessary nor sufficient for small dynamical misrepresentations to generate erroneous results. The kind of sensitivity that matters in e…
When is an ensemble like a sample? “Model-based” inferences in climate modeling
Climate scientists often apply statistical tools to a set of different estimates generated by an “ensemble” of models. In this paper, I argue that the resulting inferences are justified in the same way as any other statistical inference: what must be demonstrated is that the statistical model that licenses the inferences accurately represents the probabilistic relationship between data and target. This view of statistical practice is appropriatel…
Calibrating statistical tools: Improving the measure of Humanity's influence on the climate
Forces in a true and physical sense: From mathematical models to metaphysical conclusions
Forces in a true and physical sense: From mathematical models to metaphysical conclusions
Climate Models and the Irrelevance of Chaos
Philosophy of science has witnessed substantial recent debate over the existence of a structural analogue of chaos, which is alleged to spell trouble for certain uses of climate models. The debate over the analogy can and should be separated from its alleged epistemic implications: chaos-like behavior is neither necessary nor sufficient for small dynamical misrepresentations to generate erroneous results. The kind of sensitivity that matters in e…
Accuracy, probabilism, and the insufficiency of the alethic
The best and most popular argument for probabilism is the accuracy-dominance argument, which purports to show that alethic considerations alone support the view that an agent’s degrees of belief should always obey the axioms of probability. I argue that extant versions of the accuracy-dominance argument face a problem. In order for the mathematics of the argument to function as advertised, we must assume that every omniscient credence function is…
When is an ensemble like a sample? “Model-based” inferences in climate modeling
Climate scientists often apply statistical tools to a set of different estimates generated by an “ensemble” of models. In this paper, I argue that the resulting inferences are justified in the same way as any other statistical inference: what must be demonstrated is that the statistical model that licenses the inferences accurately represents the probabilistic relationship between data and target. This view of statistical practice is appropriatel…
Science, assertion, and the common ground
I argue that the appropriateness of an assertion is sensitive to context—or, really, the “common ground”—in a way that hasn’t previously been emphasized by philosophers. This kind of context-sensitivity explains why some scientific conclusions seem to be appropriately asserted even though they are not known, believed, or justified on the available evidence. I then consider other recent attempts to account for this phenomenon and argue that if the…
Calibrating statistical tools: Improving the measure of Humanity's influence on the climate
Interpreting the Probabilistic Language in IPCC Reports
The Intergovernmental Panel on Climate Change (IPCC) often qualifies its statements by use of probabilistic “likelihood” language. In this paper, I show that this language is not properly interpreted in either frequentist or Bayesian terms—simply put, the IPCC uses both kinds of statistics to calculate these likelihoods. I then offer a deflationist interpretation: the probabilistic language expresses nothing more than how compatible the evidence …
The Cooperative Origins of Epistemic Rationality
Against “Possibilist” Interpretations of Climate Models
Climate scientists frequently employ heavily idealized models. How should these models be interpreted? Some philosophers have advanced a possibilist interpretation: climate models stand in for possible scenarios that could occur but do not provide information about how probable those scenarios are. This article argues that possibilism is (1) undermotivated, (2) incompatible with successful practices in the science, and (3) unable to correct for k…
Supposition and (Statistical) Models
In a recent paper, Sprenger advances what he calls a “suppositional” answer to the question of why a Bayesian agent’s degrees of belief should align with the probabilities found in statistical models. I show that Sprenger’s account trades on an ambiguity between hypothetical and subjunctive suppositions and cannot succeed once we distinguish between the two
The Unity of Robustness: Why Agreement Across Model Reports is Just as Valuable as Agreement Among Experiments
A number of philosophers of science have argued that there are important differences between robustness in modeling and experimental contexts, and—in particular—many of them have claimed that the former is non-confirmatory. In this paper, I argue for the opposite conclusion: robust hypotheses are confirmed under conditions that do not depend on the differences between and models and experiments—that is, the degree to which the robust hypothesis i…
Methodologies of Uncertainty: Philosophical Disagreement in the Economics of Climate Catastrophes
How do you assert a graph? Towards an account of depictions in scientific testimony
I extend the literature on norms of assertion to the ubiquitous use of graphs in scientific papers and presentations, which I term “graphical testimony.” On my account, the testimonial presentation of a graph involves commitment to both (a) the in‐context reliability of the graph's framing devices and (b) the perspective‐relative accuracy of the graph's content. Despite apparent disagreements between my account and traditional accounts of asserti…
Who’s Afraid of the Base-Rate Fallacy
This paper evaluates the back-and-forth between Mayo, Howson, and Achinstein over whether classical statistics commits the base-rate fallacy. I show that Mayo is correct to claim that Howson’s arguments rely on a misunderstanding of classical theory. I then argue that Achinstein’s refined version of the argument turns on largely undefended epistemic assumptions about “what we care about” when evaluating hypotheses. I end by suggesting that Mayo’s…
Stability, Robustness Reasoning, and Measuring the Human Contribution to Warming
In principle, inaccuracies in the representation of the climate’s internal variability could undermine the measurement of the human contribution to warming. Equally in principle, the success of the measurement practice could provide evidence that our assumptions about internal variability are correct. I argue that neither condition obtains: current measurement practices do not provide evidence for the accuracy of our assumptions precisely because…
What use the Realist for a Theory of Truth?
Recently, Hasok Chang has argued that we should adopt a pragmatic account of truth on which truth is constituted by practical success. Central to his argument is the claim that truth in this sense can be pursued and that other senses of truth can’t be. In this paper, I present a dilemma for Chang’s view. Either practical success constitutes truth in a way that implies infallibility—a conclusion that I’ll argue is untenable—or the argument from pu…
Epistemology (13 works) · Philosophy (12 works) · Computer Science (11 works) · Philosophy and History of Science (7 works) · Epistemology, Ethics, and Metaphysics (6 works) · Mathematics (6 works) · Psychology (6 works) · Science and Climate Studies (5 works) · Econometrics (4 works) · Metaphysics (4 works)