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Record W2024025092 · doi:10.1075/ssol.2.1.02dji

Genre or artistic merit?

2012· article· en· W2024025092 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 · 2012
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsReading (process)PersonalityTraitBig Five personality traitsPsychologyAffect (linguistics)Transformative learningSocial psychologyCognitive psychologyLinguisticsDevelopmental psychologyComputer sciencePhilosophyCommunication

Abstract

fetched live from OpenAlex

We tested whether the genre of a literary text (essay as compared with short story) or its artistic merit would be primarily responsible for the variability in the self-perceived personality traits that individuals experience when they read. One hundred participants were randomly assigned to read either one of eight essays or one of eight short stories, matched for length, reading difficulty, and interest. The Big-Five personality traits were measured before and after reading. Genre did not affect variability in personality. Rather, participants who judged the text they read to be more artistic reported a greater variability in their personality trait profile after reading, independently of whether the text was an essay or a short story. Artistic merit appears to be associated with literature’s transformative effects through the instability in the self-perceived experience of the reader’s personality.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.074
GPT teacher head0.412
Teacher spread0.338 · 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