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Record W1986246067 · doi:10.1177/0164027502238341

Stereotypes of Elderly Persons in Narrative Jokes

2003· article· en· W1986246067 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

VenueResearch on Aging · 2003
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsLakehead University
Fundersnot available
KeywordsInnocenceNarrativePsychologyStereotype (UML)ConcordanceDevelopmental psychologyPsychoanalytic theoryNarrative inquiryCognitionSocial psychologyPsychoanalysisLiteratureMedicineArt

Abstract

fetched live from OpenAlex

The chief objective of this study was to describe and review stereotypes of elderly persons found in adult narrative jokes, based on a conceptual framework drawing from psychoanalytic and cognitive theories of humor. Approximately 4,200 jokes were examined, of which 102 were judged to employ a single predominant stereotype of the elderly. A content analysis by the researcher established eight stereotypes: the impotent male, the unattractive female, the vain/virile male, the disinterested female, the innocence of second childhood, the insatiable female, the forgetful old person, and the infirm old person. The jokes were sorted using these categories by two independent judges. High levels of concordance were found for all stereotypes excepting the innocence of second childhood. Some implications for gerontological education of ageist stereotyping in narrative jokes are reviewed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.193
GPT teacher head0.514
Teacher spread0.320 · 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