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Record W2919004388 · doi:10.1111/soc4.12673

“Old age” as a social location: Theorizing institutional processes, cultural expectations, and interactional practices

2019· article· en· W2919004388 on OpenAlexafffund
Rachel Barken

Bibliographic record

VenueSociology Compass · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsWomen's Health In Women's HandsYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSociologyInequalityEthnic groupPower (physics)Gender studiesSocial inequalityRace (biology)Constraint (computer-aided design)Social relationSocial psychologySocial sciencePsychologyAnthropology

Abstract

fetched live from OpenAlex

Abstract The graying of societies and growing inequality call for increased attention to age relations and their implications for power, status, and constraint in late life. In this paper, I argue old age is a distinct—and devalued—social location that exists amid intersecting relations of inequality. Using an integrative approach, I synthesize selected sociological research on the institutional processes, cultural expectations, and interactional practices underlying the social construction of old age. I then review research in the areas of family care work and employment to illustrate some empirical contexts where age relations intersect with gender, class, race, and ethnicity to structure divergent opportunities and constraints among older people. This paper maps out significant theoretical and substantive signposts in the sociology of old age to build connections across levels of analysis, and to provide a nuanced, comprehensive approach to patterned inequalities in late life.

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)0.004
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.026
Scholarly communication0.0050.005
Open science0.0010.004
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 head0.203
GPT teacher head0.473
Teacher spread0.270 · 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

Citations21
Published2019
Admission routes2
Has abstractyes

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