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Record W2013630128 · doi:10.1075/ssol.4.2.01bis

Do fiction writers have superior perspective taking ability?

2014· article· en· W2013630128 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.

Bibliographic record

VenueScientific Study of Literature · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPerspective (graphical)PsychologyReading (process)Fiction theoryQuality (philosophy)Literary fictionNon-fictionSocial psychologyOutcome (game theory)Control (management)LiteratureArtLinguisticsLiterary criticismEpistemologyComputer sciencePhilosophyVisual arts

Abstract

fetched live from OpenAlex

In investigating the relationship between fiction writing and perspective taking, beliefs about the ability of fiction writers to correctly infer the mental states of others were assessed via survey, in comparison to other professions. Next, two groups of fiction writers (established and intermediate) and a control group were compared across different measures of perspective taking. Possible moderating variables such as age, verbal intelligence, depressive symptoms, and fiction reading were measured. Participants provided writing samples, which were scored for quality. Analyses revealed that the general public believes fiction writers demonstrate above-average perspective-taking ability; however, empirical tests revealed no significant between-group differences on the outcome measures, nor any relationship between fiction writing quality and any outcome measures. The results of the suggest that fiction writers are no better than similar individuals who do not write fiction in terms of their ability to infer others’ mental states or take their perspectives.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.041
GPT teacher head0.301
Teacher spread0.260 · 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