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Record W2945644192 · doi:10.1515/humor-2017-0098

A behavior genetic analysis of the relationship between humor styles and depression

2019· article· en· W2945644192 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

VenueHumor - International Journal of Humor Research · 2019
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyAffect (linguistics)Depression (economics)CorrelationClinical psychologyDizygotic twinMonozygotic twinTwin studyDevelopmental psychologyNegative correlationPositive correlationHeritabilityMedicineInternal medicineGenetics

Abstract

fetched live from OpenAlex

Abstract The present study examined the relationship between humor styles and depression using two methods of examination: (1) the mean humor style differences between individuals who reported that they had been diagnosed with depression versus those who did not report being depressed; and (2) the phenotypic, genetic, and environmental correlations between humor styles and a short scale assessing depressed affect created from preexisting measures in archival data. Participants were 1154 adult Australians, consisting of 339 monozygotic twin pairs and 238 dizygotic twin pairs. With respect to mean differences, depressed individuals were found to use self-defeating humor more and self-enhancing humor less than non-depressed adults. When the depressed affect scale score was analyzed, negative correlations were found with both affiliative and self-enhancing humor. A positive correlation was found between depressed affect and both aggressive and self-defeating humor. These phenotypic correlations were also found to have some significant genetic and environmental correlations.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.187
GPT teacher head0.504
Teacher spread0.318 · 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