Bibliographic record
Abstract
Abstract Some works of literature are compromised because their authors get the facts wrong. In other works deviations from the facts don't seem to matter, and authors quite legitimately make things up. This paper gives an account of the various ways in which matters of fact can make a difference to the aesthetic value of works of literature. It concludes by showing how this account can be applied in determining when a concern with matters of fact is an important part of literary criticism and when it is merely pedantic. Keywords: fictionliteratureauthorshiphermeneuticsaesthetics Acknowledgement Thanks to Zena Hitz, Tom Mole and Chris Noble for extremely helpful discussions on many of these issues. Notes 1 'Literature and the Matter of Fact', in C. Ricks, Essays in Appreciation (Oxford: Oxford University Press, 1996), pp. 280–310. 2 M. W. Rowe, 'Lamarque and Olsen on Truth in Literature', Philosophical Quarterly, 34 (188) (1997), pp. 322–341. 3 P. Lamarque, The Philosophy of Literature (Oxford: Blackwell, 2008). 4 Sir Philip Sidney, A Defence of Poetry, ed. J. A. Van Dorsten (Oxford: Oxford University Press, 1966), p. 52. 5 See, for example, F. E. Sparshott, 'Truth in Fiction', Journal of Aesthetics and Art Criticism, 26 (1) (Autumn 1967), pp. 3–7. 6 At any rate, they can't be true. Whether you think that they can be false will depend on your view of how semantics behaves in the face of reference failure. 7 One might insist that they aren't orthogonal at all – that a proper answer to the question, 'How does aesthetic evaluation relate to moral evaluation?' will throw light on the question 'How does aesthetic evaluation relate to factual evaluation?' and vice versa. One might think, for example, that aesthetic evaluation is sui generis and fully autonomous from these other modes of evaluation. It's certainly a tempting view. I think that it's a seriously mistaken one, and that considerations of the sort raised in this article show it to be so. 8 In fact Lucky Jim, is an example that could be used to illustrate the point that plausibility and accuracy, and not truth simpliciter, are what matter. Those points of the novel at which we know that Amis was drawing closely from life are certainly no better than those at which Amis was making up the details, but was nonetheless accurately depicting a certain social scene. Indeed, Amis sometimes draws from life (specifically, from Philip Larkin's life) too closely for comfort. At these times literal truth might actually be an aesthetic failure. 9 George Orwell, 'In Defence of P. G. Wodehouse', reprinted in The Penguin Essays of George Orwell (Harmondsworth: Penguin, 1984), p. 296. 10 In Harry Potter and the Prisoner of Azkaban Hermione's enthusiasm for study is aided when she is given a device that enables her to travel back in time in order to attend two simultaneous classes. J. K. Rowling would have done well to restrict its use to matters of academic scheduling. The struggle against the rise of Lord Voldemort becomes far too easy if spatial bi‐location can be used in that endeavour. 11 This point is one emphasized by Alexander Nehamas in his 'The Place of Beauty and the Role of Value in the World of Art', Critical Quarterly, 42 (3) (2000), pp. 1–14 and elsewhere.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".