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Record W3173826093 · doi:10.3138/utq.90.2.02

Dr. Robert Butler’s Legacy in Defining and Fighting Ageism

2021· article· en· W3173826093 on OpenAlexvenueno aff
W. Andrew Achenbaum

Bibliographic record

VenueUniversity of Toronto Quarterly · 2021
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsnot available
Fundersnot available
KeywordsGerontologySociologyGeriatricsPersonal accountPolitical sciencePsychologyMedicineArtPsychiatry

Abstract

fetched live from OpenAlex

Robert N. Butler, MD (1927–2010), coined the term “ageism” in 1969 to define an age-driven bigotry that disengaged older persons from virtually all sectors of American life. As founding director of the National Institute of Aging, as head of the first geriatrics department in a US medical school, and as a trailblazing idea broker, Dr. Butler continually sought to make Americans aware about the insidious effects of ageism. He accomplished much in promoting education and research, but Dr. Butler’s personal and professional campaign to extirpate ageism remains his greatest legacy.

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)0.013
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.014
Scholarly communication0.0070.008
Open science0.0010.004
Research integrity0.0060.024
Insufficient payload (model declined to judge)0.0040.002

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 head0.018
GPT teacher head0.282
Teacher spread0.264 · 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 designNot applicable
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

Citations6
Published2021
Admission routes1
Has abstractyes

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Same venueUniversity of Toronto QuarterlySame topicAging and Gerontology ResearchFrench-language works237,207