MétaCan
Menu
Back to cohort
Record W3095976251 · doi:10.1017/s0144686x20001476

‘I've never given it a thought’: older men's experiences with and perceptions of ageism during interactions with physicians

2020· article· en· W3095976251 on OpenAlexaffabout
Hazel MacRae

Bibliographic record

VenueAgeing and Society · 2020
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsPerceptionPsychologyOlder peopleFace (sociological concept)Prejudice (legal term)GerontologySocial psychologyMedicineSociology

Abstract

fetched live from OpenAlex

Abstract The subjective experience of ageism among older men has received little research attention. This study examines older Canadian men's experiences with and perceptions of ageism during interactions with physicians. In-depth, face-to-face interviews were conducted with 21 men aged 55 years and over. The findings indicate a seeming lack of awareness of ageism among many, and many did not believe ageism was likely to occur during patient–physician interaction. Negative stereotyping of older patients was common. A large majority of the participants reported that they had not personally experienced ageism during a medical encounter, nor were they concerned about it. Numerous rationales were proffered as explanations of why a particular participant had not experienced ageism and who was more likely to be a target.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.263
Threshold uncertainty score0.522

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0020.001
Open science0.0010.002
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 head0.020
GPT teacher head0.321
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 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

Citations4
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueAgeing and SocietySame topicAging and Gerontology ResearchFrench-language works237,207