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Record W2751100827 · doi:10.3390/soc7030021

Queering Aging Futures

2017· article· en· W2751100827 on OpenAlexaff
Linn Sandberg, Barbara Marshall

Bibliographic record

VenueSocieties · 2017
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsTrent University
Fundersnot available
KeywordsFutures contractHeteronormativityQueerDiversity (politics)SociologySuccessful agingGender studiesAestheticsSpace (punctuation)LinguisticsArtAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

This paper explores the potential for cultural gerontology to extend its ideas of diversity in aging experiences by opening space to rethink conceptions of successful aging futures. We propose a ‘queering’ of aging futures that disrupts the ways that expectations of a good later life and happy aging are seen to adhere to some bodies and subjectivities over others. Drawing on feminist, queer, and crip theories, we build on existing critiques of ‘successful aging’ to interrogate the assumptions of heteronormativity, able-bodiedness and able-mindedness that shape the dividing lines between success and failure in aging, and which inform attempts to ‘repair’ damaged futures. Conclusions suggest that recognizing diversity in successful aging futures is important in shaping responses to the challenges of aging societies, and presents an opportunity for critical cultural gerontology to join with its theoretical allies in imagining more inclusive alternatives.

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)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.045
Scholarly communication0.0070.015
Open science0.0010.009
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.071
GPT teacher head0.446
Teacher spread0.375 · 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 designTheoretical or conceptual
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

Citations154
Published2017
Admission routes1
Has abstractyes

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