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Putting Age into Place

2015· article· en· W4301438008 on OpenAlexaboutno aff
Ulla Kriebernegg

Bibliographic record

VenueAge Culture Humanities An Interdisciplinary Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSubversionNarrativeOppressionGender studiesAgency (philosophy)SociologyStereotype (UML)Space (punctuation)AestheticsPolitical sciencePsychologySocial scienceSocial psychologyArtLiteratureLawPoliticsLinguistics

Abstract

fetched live from OpenAlex

This paper addresses cultural constructions of old age in two contemporary Canadian care home narratives. While John Mighton’s play Half Life (2005) is set in a prison-like long-term care facility that is represented as a site of homogenization, oppression, and infantilization, Joan Barfoot’s novel Exit Lines (2008) plays in a hotel-like retirement lodge for wealthy customers that, despite its authoritarian manager, functions as a site of meaningful identity development and intragenerational relationships. What both texts have in common, however, is that they focus on residents’ individual resistance, subversion, and agency, thus opposing the ageist stereotype of decline and deconstructing prevailing norms and negative images of old age as merely physical decrepitude and disease. How is the space of the care home narrated in these two contemporary Canadian texts, and what role do aspects of space and place play for the narrative construction of old age? In this paper, I argue that the spatiality of aging is a category that needs to be incorporated into both an analysis of literary representations of the “fourth age” and an exploration of critical issues of space and place. The juxtaposition of two caregiving institutions in recent Canadian fction contributes to revealing how old age is imagined at the beginning of the twenty-frst century.

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)0.002
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.693
Threshold uncertainty score0.617

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0200.046
Scholarly communication0.0070.006
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.064
GPT teacher head0.365
Teacher spread0.302 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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Same venueAge Culture Humanities An Interdisciplinary JournalSame topicMigration, Aging, and Tourism StudiesFrench-language works237,207