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Record W3174458667 · doi:10.3138/utq.90.2.03

Ageism and the Unrealizability of Old Age

2021· article· en· W3174458667 on OpenAlexvenueno aff
Chris Gilleard

Bibliographic record

VenueUniversity of Toronto Quarterly · 2021
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsnot available
Fundersnot available
KeywordsExistentialismSubject (documents)Object (grammar)TerminologySociologyAestheticsEpistemologyOpposition (politics)PsychologyPsychoanalysisPhilosophyLawPolitical scienceComputer scienceLinguistics

Abstract

fetched live from OpenAlex

This article addresses the topic of ageism through the lens provided by Simone de Beauvoir concerning the subjective “unrealizability” of age. In her book, Old Age, she adopted the terminology of existentialism to argue that old age was one of the “unrealizables”: phenomena that can be grasped only through their “otherness.” Old age, in her view, can only ever be understood as an object position, or rather a multiplicity of object positions, none of which aligns with the experiencing self. This inherent otherness of age provides a ready template for viewing agedness as an undesired, undesirable, and fundamentally alien characteristic. The outwardly ageing subject’s view of him- or herself remains always ageless, distinct from such otherness, experienced as more real than any self-reflected aged other. But while age’s unrealizability may sustain the individual’s subject position as ageless, it risks perpetuating the devaluation of the aged as always a collective other. Rather than demanding a resolution of such object and subject positions, I suggest that a more realizable goal may be to accept this inevitable opposition and focus instead upon improving the objective conditions of later life. Enriching the actual relations of care might constitute such an objectively “realizable” goal, one that is also in keeping with the social intent of de Beauvoir’s book.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.688
Threshold uncertainty score0.999

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 studies0.0000.001
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 head0.017
GPT teacher head0.277
Teacher spread0.260 · 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.

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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

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