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Record W3198608594 · doi:10.1017/s0714980821000325

Imperfect Solutions to the Neoliberal Problem of Public Aging: A Critical Discourse Analysis of Public Narratives of Long-Term Residential Care

2021· article· en· W3198608594 on OpenAlexafffundabout

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2021
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of ManitobaYork University
FundersUniversity of Manitoba
KeywordsPrivilege (computing)Context (archaeology)Public discoursePerceptionDiscourse analysisCritical discourse analysisImperfectRelevance (law)Public healthNarrative

Abstract

fetched live from OpenAlex

Public representations of long-term residential care (LTRC) facilities have received limited focus in Canada, although literature from other countries indicates that public perceptions of LTRC tend to be negative, particularly in contexts that prioritize aging and dying in place. Using Manitoba as the study context, we investigate a question of broad relevance to the Canadian perspective; specifically, what are current public perceptions of the role and function of long-term care in the context of a changing health care system? Through critical discourse analysis, we identify four overarching discourses dominating public perceptions of LTRC: the problem of public aging, LTRC as an imperfect solution to the problem, LTRC as ambiguous social spaces, and LTRC as a last resort option. Building on prior theoretical work, we suggest that public perceptions of LTRC are informed by neoliberal discourses that privilege individual responsibility and problematize public care.

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)0.029
metaresearch head score (Gemma)0.036
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: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.705

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0270.057
Scholarly communication0.0160.012
Open science0.0040.011
Research integrity0.0040.007
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 head0.036
GPT teacher head0.338
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

Citations13
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicGeriatric Care and Nursing HomesFrench-language works237,207