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Record W3095818238 · doi:10.3390/bs10110165

No Laughing Matter: How Humor Styles Relate to Feelings of Loneliness and Not Mattering

2020· article· en· W3095818238 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

VenueBehavioral Sciences · 2020
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsLonelinessPsychologyFeelingUCLA Loneliness ScaleInterpersonal communicationScale (ratio)Interpersonal relationshipConfirmatory factor analysisSocial psychologyDevelopmental psychologyStructural equation modeling

Abstract

fetched live from OpenAlex

Loneliness and feeling that one does not matter are closely linked, but further investigation is needed to determine differentiating features. The relationship between not mattering to others (anti-mattering) and loneliness was explored by assessing how the two constructs correlated with an interpersonal dimension, specifically four humor styles (affiliative, self-enhancing, self-defeating, and aggressive). One hundred and fifty-eight women and 96 men completed a three-item loneliness scale, a new measure of anti-mattering, and a humor styles questionnaire. Confirmatory factor analysis results indicated that the new anti-mattering measure is a unidimensional scale. Loneliness and anti-mattering were strongly correlated, and each correlated in the same direction with approximately the same magnitude as the four humor styles. The discussion concludes that anti-mattering and loneliness are strongly linked, a finding which may be important in psychological treatment. Humor styles also play a role in psychological well-being and present a unique pathway to mental health.

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)0.000
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 score0.311
Threshold uncertainty score0.307

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 head0.109
GPT teacher head0.382
Teacher spread0.273 · 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