Jonah N Schupbach
Biographic Data
| ID | 1116187 |
|---|---|
| NAME | Jonah N Schupbach |
| GIVEN NAMES | Jonah N |
| FAMILY NAME | Schupbach |
| SIGNATURE | SCHUPBACH J N |
| AFFILIATIONS | University of Ulster |
| ORCID | 0000-0002-6180-696X |
| VERIFIED | Yes |
| TOTAL WORKS | 19 |
| TOTAL CITATIONS | 139 |
| WORKS AS AUTHOR | 19 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1967 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 7 |
Information and Explanatory Goodness
I propose a qualitative Bayesian account of explanatory goodness that is analogous to the Bayesian account of incremental confirmation. This is achieved by means of a complexity criterion according to which an explanation h is good if the reduction in the complexity of the explanandum e brought about by h (the explanatory gain) is greater than the additional complexity introduced by h in the context of e (the explanatory cost). To illustrate the …
Conjunctive explanations
When is it explanatorily better to adopt a conjunction of explanatory hypotheses as opposed to committing to only some of them? Although conjunctive explanations are inevitably less probable than less committed alternatives, we argue that the answer is not ‘never’. This paper provides an account of the conditions under which explanatory considerations warrant a preference for less probable, conjunctive explanations. After setting out four formal …
How good is an explanation
How good is an explanation and when is one explanation better than another? In this paper, I address these questions by exploring probabilistic measures of explanatory power in order to defend a particular Bayesian account of explanatory goodness. Critical to this discussion is a distinction between weak and strong measures of explanatory power due to Good (Br J Philos Sci 19:123–143, 1968). In particular, I argue that if one is interested in the…
On the Logical Structure of Best Explanations
Standard articulations of Inference to the Best Explanation (IBE) imply the uniqueness claim that exactly one explanation should be inferred in response to an explanandum. This claim has been challenged as being both too strong (sometimes agnosticism between candidate explanatory hypotheses seems the rational conclusion) and too weak (in cases where multiple hypotheses might sensibly be conjointly inferred). I propose a novel interpretation of IB…
Conjunctive Explanations
Coherence, Explanation, and Hypothesis Selection
This article provides a new approach to inference to the best explanation (IBE) based on a new coherence measure for comparing how well hypotheses explain the evidence. It addresses a number of criticisms of the use of probabilistic measures in this context by Glymour ([2015]), including limitations of earlier work on IBE (Glass [2012]). Computer experiments are used to show that the new approach finds the truth with a high degree of accuracy in …
Robustness Analysis as Explanatory Reasoning
When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be ‘robust’. This article investigates the logic of such ‘robustness analysis’ (RA). The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal e…
Two-dimensional opinion dynamics in social networks with conflicting beliefs
Hypothesis Competition beyond Mutual Exclusivity
Competition between scientific hypotheses is not always a matter of mutual exclusivity. Consistent hypotheses can compete to varying degrees either directly or indirectly via a body of evidence. We motivate and defend a particular account of hypothesis competition by showing how it captures these features. Computer simulations of Bayesian inference are used to highlight the limitations of adopting mutual exclusivity as a simplifying assumption to…
Experimental Explication
Two recently popular metaphilosophical movements, formal philosophy and experimental philosophy, promote what seem to be conflicting methodologies. Nonetheless, I argue that the two can be mutually supportive. I propose an experimentally‐informed variation on explication, a powerful formal philosophical tool introduced by Carnap. The resulting method, which I call “experimental explication,” provides the formalist with a means of responding to ex…
Is the conjunction fallacy tied to probabilistic confirmation
Inference to the best explanation
Comparing Probabilistic Measures of Explanatory Power
Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the strength of a potential explanation. These candidate measures of “explanatory power” arguably have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people's actual explanatory judgments. Here I present my own…
The Logic of Explanatory Power
This article introduces and defends a probabilistic measure of the explanatory power that a particular explanans has over its explanandum. To this end, we propose several intuitive, formal conditions of adequacy for an account of explanatory power. Then, we show that these conditions are uniquely satisfied by one particular probabilistic function. We proceed to strengthen the case for this measure of explanatory power by proving several theorems,…
New Hope for Shogenji's Coherence Measure
I show that the two most devastating objections to Shogenji's formal account of coherence necessarily involve information sets of cardinality . Given this, I surmise that the problem with Shogenji's measure has more to do with his means of generalizing the measure than with the measure itself. I defend this claim by offering an alternative generalization of Shogenji's measure. This alternative retains the intuitive merits of the original measure …
Coherence measures and inference to the best explanation
Must the Scientific Realist be a Rationalist
On a Bayesian Analysis of the Virtue of Unification
In three recent papers, Wayne Myrvold (1996, 2003) and Timothy McGrew (2003) have developed Bayesian accounts of the virtue of unification. In his account, McGrew demonstrates that, ceteris paribus, a hypothesis that unifies its evidence will have a higher posterior probability than a hypothesis that does not. Myrvold, on the other hand, offers a specific measure of unification that can be applied to individual hypotheses. He argues that one must…
Amobarbital Sodium and the Effects of Reward and Nonreward in the Amsel Double Runway
Rats received 60 trials (Condition I) with 6 pellets reward at the second goal of a double runway and either 6 ( n = 12) or 0 ( n = 12) at the first goal, followed by, for all Ss, 24 trials (Condition II) with 0 reward at the first goal, then 36 trials (Condition III) with 50% reward at the first goal. Half of each reward group received amobarbital sodium (20 mg/kg, IP) and half saline prior to the 6 daily trials. Neither excitatory nor inhibitor…
The Logic of Explanatory Power
This article introduces and defends a probabilistic measure of the explanatory power that a particular explanans has over its explanandum. To this end, we propose several intuitive, formal conditions of adequacy for an account of explanatory power. Then, we show that these conditions are uniquely satisfied by one particular probabilistic function. We proceed to strengthen the case for this measure of explanatory power by proving several theorems,…
Robustness Analysis as Explanatory Reasoning
When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be ‘robust’. This article investigates the logic of such ‘robustness analysis’ (RA). The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal e…
New Hope for Shogenji's Coherence Measure
I show that the two most devastating objections to Shogenji's formal account of coherence necessarily involve information sets of cardinality . Given this, I surmise that the problem with Shogenji's measure has more to do with his means of generalizing the measure than with the measure itself. I defend this claim by offering an alternative generalization of Shogenji's measure. This alternative retains the intuitive merits of the original measure …
Experimental Explication
Two recently popular metaphilosophical movements, formal philosophy and experimental philosophy, promote what seem to be conflicting methodologies. Nonetheless, I argue that the two can be mutually supportive. I propose an experimentally‐informed variation on explication, a powerful formal philosophical tool introduced by Carnap. The resulting method, which I call “experimental explication,” provides the formalist with a means of responding to ex…
Comparing Probabilistic Measures of Explanatory Power
Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the strength of a potential explanation. These candidate measures of “explanatory power” arguably have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people's actual explanatory judgments. Here I present my own…
Coherence measures and inference to the best explanation
On a Bayesian Analysis of the Virtue of Unification
In three recent papers, Wayne Myrvold (1996, 2003) and Timothy McGrew (2003) have developed Bayesian accounts of the virtue of unification. In his account, McGrew demonstrates that, ceteris paribus, a hypothesis that unifies its evidence will have a higher posterior probability than a hypothesis that does not. Myrvold, on the other hand, offers a specific measure of unification that can be applied to individual hypotheses. He argues that one must…
Inference to the best explanation
Hypothesis Competition beyond Mutual Exclusivity
Competition between scientific hypotheses is not always a matter of mutual exclusivity. Consistent hypotheses can compete to varying degrees either directly or indirectly via a body of evidence. We motivate and defend a particular account of hypothesis competition by showing how it captures these features. Computer simulations of Bayesian inference are used to highlight the limitations of adopting mutual exclusivity as a simplifying assumption to…
Is the conjunction fallacy tied to probabilistic confirmation
How good is an explanation
How good is an explanation and when is one explanation better than another? In this paper, I address these questions by exploring probabilistic measures of explanatory power in order to defend a particular Bayesian account of explanatory goodness. Critical to this discussion is a distinction between weak and strong measures of explanatory power due to Good (Br J Philos Sci 19:123–143, 1968). In particular, I argue that if one is interested in the…
Coherence, Explanation, and Hypothesis Selection
This article provides a new approach to inference to the best explanation (IBE) based on a new coherence measure for comparing how well hypotheses explain the evidence. It addresses a number of criticisms of the use of probabilistic measures in this context by Glymour ([2015]), including limitations of earlier work on IBE (Glass [2012]). Computer experiments are used to show that the new approach finds the truth with a high degree of accuracy in …
Must the Scientific Realist be a Rationalist
Amobarbital Sodium and the Effects of Reward and Nonreward in the Amsel Double Runway
Rats received 60 trials (Condition I) with 6 pellets reward at the second goal of a double runway and either 6 ( n = 12) or 0 ( n = 12) at the first goal, followed by, for all Ss, 24 trials (Condition II) with 0 reward at the first goal, then 36 trials (Condition III) with 50% reward at the first goal. Half of each reward group received amobarbital sodium (20 mg/kg, IP) and half saline prior to the 6 daily trials. Neither excitatory nor inhibitor…
On a Bayesian Analysis of the Virtue of Unification
In three recent papers, Wayne Myrvold (1996, 2003) and Timothy McGrew (2003) have developed Bayesian accounts of the virtue of unification. In his account, McGrew demonstrates that, ceteris paribus, a hypothesis that unifies its evidence will have a higher posterior probability than a hypothesis that does not. Myrvold, on the other hand, offers a specific measure of unification that can be applied to individual hypotheses. He argues that one must…
Coherence measures and inference to the best explanation
Must the Scientific Realist be a Rationalist
Comparing Probabilistic Measures of Explanatory Power
Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the strength of a potential explanation. These candidate measures of “explanatory power” arguably have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people's actual explanatory judgments. Here I present my own…
The Logic of Explanatory Power
This article introduces and defends a probabilistic measure of the explanatory power that a particular explanans has over its explanandum. To this end, we propose several intuitive, formal conditions of adequacy for an account of explanatory power. Then, we show that these conditions are uniquely satisfied by one particular probabilistic function. We proceed to strengthen the case for this measure of explanatory power by proving several theorems,…
New Hope for Shogenji's Coherence Measure
I show that the two most devastating objections to Shogenji's formal account of coherence necessarily involve information sets of cardinality . Given this, I surmise that the problem with Shogenji's measure has more to do with his means of generalizing the measure than with the measure itself. I defend this claim by offering an alternative generalization of Shogenji's measure. This alternative retains the intuitive merits of the original measure …
Is the conjunction fallacy tied to probabilistic confirmation
Inference to the best explanation
Experimental Explication
Two recently popular metaphilosophical movements, formal philosophy and experimental philosophy, promote what seem to be conflicting methodologies. Nonetheless, I argue that the two can be mutually supportive. I propose an experimentally‐informed variation on explication, a powerful formal philosophical tool introduced by Carnap. The resulting method, which I call “experimental explication,” provides the formalist with a means of responding to ex…
Two-dimensional opinion dynamics in social networks with conflicting beliefs
Hypothesis Competition beyond Mutual Exclusivity
Competition between scientific hypotheses is not always a matter of mutual exclusivity. Consistent hypotheses can compete to varying degrees either directly or indirectly via a body of evidence. We motivate and defend a particular account of hypothesis competition by showing how it captures these features. Computer simulations of Bayesian inference are used to highlight the limitations of adopting mutual exclusivity as a simplifying assumption to…
Robustness Analysis as Explanatory Reasoning
When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be ‘robust’. This article investigates the logic of such ‘robustness analysis’ (RA). The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal e…
Coherence, Explanation, and Hypothesis Selection
This article provides a new approach to inference to the best explanation (IBE) based on a new coherence measure for comparing how well hypotheses explain the evidence. It addresses a number of criticisms of the use of probabilistic measures in this context by Glymour ([2015]), including limitations of earlier work on IBE (Glass [2012]). Computer experiments are used to show that the new approach finds the truth with a high degree of accuracy in …
How good is an explanation
How good is an explanation and when is one explanation better than another? In this paper, I address these questions by exploring probabilistic measures of explanatory power in order to defend a particular Bayesian account of explanatory goodness. Critical to this discussion is a distinction between weak and strong measures of explanatory power due to Good (Br J Philos Sci 19:123–143, 1968). In particular, I argue that if one is interested in the…
On the Logical Structure of Best Explanations
Standard articulations of Inference to the Best Explanation (IBE) imply the uniqueness claim that exactly one explanation should be inferred in response to an explanandum. This claim has been challenged as being both too strong (sometimes agnosticism between candidate explanatory hypotheses seems the rational conclusion) and too weak (in cases where multiple hypotheses might sensibly be conjointly inferred). I propose a novel interpretation of IB…
Conjunctive Explanations
Conjunctive explanations
When is it explanatorily better to adopt a conjunction of explanatory hypotheses as opposed to committing to only some of them? Although conjunctive explanations are inevitably less probable than less committed alternatives, we argue that the answer is not ‘never’. This paper provides an account of the conditions under which explanatory considerations warrant a preference for less probable, conjunctive explanations. After setting out four formal …
Information and Explanatory Goodness
I propose a qualitative Bayesian account of explanatory goodness that is analogous to the Bayesian account of incremental confirmation. This is achieved by means of a complexity criterion according to which an explanation h is good if the reduction in the complexity of the explanandum e brought about by h (the explanatory gain) is greater than the additional complexity introduced by h in the context of e (the explanatory cost). To illustrate the …
Epistemology (16 works) · Philosophy (16 works) · Computer Science (14 works) · Philosophy and History of Science (13 works) · Mathematics (12 works) · Epistemology, Ethics, and Metaphysics (9 works) · Artificial Intelligence (7 works) · Philosophy of science (7 works) · Probabilistic logic (7 works) · Inference (6 works)