Justifying the Norms of Inductive Inference
Bibliographic Data
| ID | 8396708 |
|---|---|
| Authors | Olav Benjamin Vassend (0000-0002-5964-8835, Nanyang Technological University, corresponding author) |
| Year | 2022 |
| Volume | 73 |
| Issue | 1 |
| Pages | 135-160 |
| Publication date | 2022-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The British Journal for the Philosophy of Science (JOURNAL) |
| Journal identifiers | ISSN: 0007-0882 • E-ISSN: 1464-3537 |
| Publisher | Oxford University Press (PUBLISHER • GB) |
| DOI | 10.1093/bjps/axz041 |
| OpenAlex | W2915833575 |
| Language | EN |
| Citations received | 2 |
| References cited | 25 |
Bayesian inference is limited in scope because it cannot be applied in idealized contexts where none of the hypotheses under consideration is true and because it is committed to always using the likelihood as a measure of evidential favouring, even when that is inappropriate. The purpose of this article is to study inductive inference in a very general setting where finding the truth is not necessarily the goal and where the measure of evidential favouring is not necessarily the likelihood. I use an accuracy argument to argue for probabilism and I develop a new kind of argument to argue for two general updating rules, both of which are reasonable in different contexts. One of the updating rules has standard Bayesian updating, Bissiri et al.’s ([2016]) general Bayesian updating, Douven’s ([2016]) IBE-based updating, and my (Vassend ([forthcoming]) quasi-Bayesian updating as special cases. The other updating rule is novel.
Argument (complex analysis) · Bayes' theorem · Bayesian inference · Bayesian probability · Data mining · Econometrics · Epistemology · Frequentist inference · Inductive reasoning · Inference · Machine learning · Mathematical economics · Measure (data warehouse) · Scope (computer science) · Artificial Intelligence · Computer Science · Decision-Making and Behavioral Economics · Epistemology, Ethics, and Metaphysics · Mathematics · Philosophy · Psychology of Moral and Emotional Judgment
Accuracy and the Laws of Credence
Ockham's Razors
Philosophy and the practice of Bayesian statistics
Justifying Conditionalization
Strictly Proper Scoring Rules, Prediction, and Estimation
A Nonpragmatic Vindication of Probabilism
Leitgeb and Pettigrew on Accuracy and Updating
New Semantics for Bayesian Inference
An Objective Justification of Bayesianism II
On the Evidential Import of Unification
Bayesian Confirmation of Theories That Incorporate Idealizations
Bayes and Bust
How to Tell When Simpler, More Unified, or Less Ad Hoc Theories will Provide More Accurate Predictions
Robustness Analysis as Explanatory Reasoning
The No Alternatives Argument
Inference to the Best Explanation versus Bayes’s Rule in a Social Setting
| Unique citing works | 2 |
|---|---|
| Citations per year | 1 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |