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Record W3162507335 · doi:10.29173/spectrum81

Make-Believe Spelunking

2021· article· en· W3162507335 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSpectrum · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy and Literary Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNormativeCriticismSociologyEpistemologyAestheticsPhilosophyLiteratureArt

Abstract

fetched live from OpenAlex

To what extent, and in what ways, is it possible for works of fiction to influence their readers’ ethical development? In this essay, I explore different answers to this descriptive question in philosophy and literary studies. I dub a view shared by Iris Murdoch and Martha Nussbaum as the attention account: that great works of fiction can influence their reader’s ethical development by compelling them to cultivate ethically charged attention. I then evaluate Joshua Landy’s criticism of this account and his alternative, which I dub the clarification account: that works of fiction can influence their reader’s ethical development by helping them clarify their core ethical commitments. I argue that neither the attention account nor the invitation account describes the one and only way in which works of fiction can influence their readers’ ethical development. I then ask a normative question: what ways in which works of fiction can influence our ethical development should we embrace? Drawing on Kendall Walton’s make-believe model of fictional experience, I develop an account of a third way in which works of fiction can influence their readers’ ethical development, which I call the invitation account: works of fiction can influence their readers’ ethical development by inviting them to unseat and positively revise their ethical commitments. I make the case for the invitation account by using it to analyze two contemporary novels, Rachel Cusk’s Outline and Marilynne Robinson’s Gilead. I argue that the process described by the invitation account—that is, the way of invitation—is one we should embrace.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.001

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.

Opus teacher head0.022
GPT teacher head0.206
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it