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Record W4407276969 · doi:10.1080/14927713.2025.2461770

The cultural omnivore hypothesis applied to reading habits: a test of novelty-seeking and intrinsic motivation as explanatory factors

2025· article· en· W4407276969 on OpenAlexaffvenueabout
Alex T. Silver, Steven E. Mock

Bibliographic record

VenueLeisure/Loisir · 2025
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNoveltyOmnivorePsychologyTest (biology)Reading (process)Explanatory powerExplanatory modelIntrinsic motivationSocial psychologyMathematicsStatisticsEpistemologyEcologyPhilosophyBiologyLinguistics

Abstract

fetched live from OpenAlex

According to the cultural omnivore hypothesis, higher class individuals possess a broader palette of tastes and preferences when it comes to leisure consumption. Although potential explanations of this pattern have been suggested, little research done to explore potential explanatory factors for this relationship. We set out to test the often-speculated explanatory factor openness to experience and drew on other class-focused theory. Namely, the notion of class as culture was used to test an additional explanatory factor, intrinsic motivation. For the present analyses, we examined the relationship between socio-economic status (SES), and breadth of book genre readership using Canadian secondary data, specifically the Survey of Reading and Buying Books 2005. The results from a linear regression analysis between SES and number of book genres read supported the cultural omnivore hypothesis. Additionally, both openness and intrinsic motivation were shown to help mediate this relationship, suggesting they may help explain the cultural omnivore.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.495

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)0.0000.000

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 head0.057
GPT teacher head0.316
Teacher spread0.259 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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