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Record W3111487153 · doi:10.1093/geroni/igaa057.1909

Ageist Communication Experienced by Middle-Aged and Older Adults

2020· article· en· W3111487153 on OpenAlexaff
Alison L. Chasteen, Sali A. Tagliamonte

Bibliographic record

VenueInnovation in Aging · 2020
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyOlder peopleGerontologySocial psychologyMedicine

Abstract

fetched live from OpenAlex

Abstract Despite the prevalence of ageism, relatively little is known about specific aspects of ageism experiences. In the present study, middle-aged and older adults described their experiences of ageism as part of an interview. Their descriptions were coded for the domain in which the ageist act occurred, the perpetrator of the act, and what type of ageist act occurred. A majority of participants indicated that they had been the target of an ageist act, with those acts occurring most commonly in the public sphere. Consistent with this finding, perpetrators of ageist acts were most often strangers. Ageist comments most often involved age-based social or physical assumptions about the target. Together, these findings suggest that there is a lack of norms prohibiting ageist communication in public spheres.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.368
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2020
Admission routes1
Has abstractyes

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