Bibliographic record
Abstract
Abstract This book develops original accounts of the logical, psychological, and normative aspects of belief, grounded in ontological views that put the believer at the heart of the story. Hunter argues that to believe something is to be in position to do, think, and feel things in light of a possibility whose obtaining would make one right. The logical aspect is that being right depends only on whether that possibility obtains. The psychological one concerns how that possibility can rationalize what one does, thinks, and feels. But, Hunter argues, beliefs are not causes, capacities, or dispositions. Rather, believing rationalizes because possibilities are potential reasons. Hunter also denies that believing is a form of representing. The objects of belief are possibilities, not representations, and belief states are not themselves true or false. Hunter defends this modal view against familiar objections and explores how objective and subjective limits to belief generate credal illusions and ground credal necessities. Developing a novel account of the normativity of belief, he argues that voluntary acts of inference make us responsible for our beliefs. While denying that believing is intrinsically normative, Hunter grounds the ethics of belief in attributive goodness. Believing something is to our credit when it shows us to be good in some way, and what we ought to believe depends on what we ought to know, and not on the evidence we have. The ethics of belief, Hunter argues, concern how a believer ought to be positioned in a world of possibilities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.019 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".