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Record W3086716130

Examining the humor styles and positive aging in older adults and the role of cognitive functioning

2019· dissertation· en· W3086716130 on OpenAlexaboutno aff
Matthew Schurr

Bibliographic record

VenueLu Zone Ul (Laurentian University) · 2019
Typedissertation
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyCognitive agingSuccessful agingDevelopmental psychologyCognitionGerontologyCognitive skillClinical psychologyCognitive psychologyMedicinePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

The current study examines how humor use may relate to positive aging in older adults. In
\nparticular, it is proposed that the four different humor styles (self-enhancing, affiliative, selfdefeating, and aggressive humor) may be differentially associated with positive aging. The
\ncurrent study also suggests that level of cognitive functioning may play a role in this relationship.
\nAccordingly, it is proposed that older adults with intact cognitive functioning will use more
\npositive styles of humor and experience more positive aging than those with impaired cognitive
\nfunctioning. Twenty-four older adults from Northern Ontario communities completed self-report
\nmeasures pertaining to the four humor styles, positive aging, and self-esteem, as well as
\ncompleted a brief assessment of cognitive functioning. Significant differences were found
\nbetween intact and impaired cognitive functioning older adults on use of self-defeating humor.
\nAdditional exploratory analyses are further discussed. Limitations of the current study and
\nfuture directions are considered.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.543

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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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