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Record W4400835299 · doi:10.54254/2753-7064/2/20220433

Personality and Film Genre Preferences: An Analysis Based on the Big Five Model

2023· article· en· W4400835299 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

VenueCommunications in Humanities Research · 2023
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPersonalityPsychologyFilm genreSocial psychologyArtVisual artsMovie theater

Abstract

fetched live from OpenAlex

Studies have investigated the factors that affect entertainment preferences, including what we listen to, watch, and read. Only a few studies focused on the film genres and current findings are still insufficient. To explore the relationship between personality and film genre preferences, this study uses the self-reported questionnaire to collect data and test the correlations between the two variables. The personality traits are analyzed based on the Big Five Model, which consisted of Extraversion, Conscientiousness, Agreeableness, Emotional Stability, and Openness to Experiences. The results indicate 1) there are positive correlations between the Big Five personality traits and film genre preferences, 2) the incorporation of Conscientiousness and Openness to Experiences could predict the film genre preferences, 3) the gender differences should be considered in the analysis of personality and film genre preferences as well.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.673
GPT teacher head0.530
Teacher spread0.143 · 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