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Record W1965531721 · doi:10.1080/14427591.2009.9686637

Shaping ideal places for retirement: Occupational possibilities within contemporary media

2009· article· en· W1965531721 on OpenAlexaffabout
Debbie Laliberté Rudman, Suzanne Huot, Silke Dennhardt

Bibliographic record

VenueJournal of Occupational Science · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsIdeal (ethics)NewspaperSociologyConsumption (sociology)PoliticsPublic relationsGender studiesPolitical scienceSocial scienceMedia studiesLaw

Abstract

fetched live from OpenAlex

This article presents a critical discourse analysis of 82 Canadian newspaper texts addressing ideal housing options for individuals preparing for and living in their retirement years. The analysis explored key aspects of ideal places for retirement and critically considered the occupational possibilities shaped within such texts. The texts analyzed urged pre‐retirees and early retirees to work towards being active, youthful and modern, through becoming proactive housing consumers. Ideal places were those that enabled older individuals to live with people who were similar in terms of age, class and interests, while ideal occupations involved consumption, physically active leisure and cultured activities. Building on research addressing the social and political implications of discourses regarding ideal places for retirement, the occupational implications of such places are considered both for those aging individuals who have the resources to consume such places, and for those who are excluded from them.

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)0.006
metaresearch head score (Gemma)0.010
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 score0.225
Threshold uncertainty score0.448

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0180.029
Scholarly communication0.0130.007
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.146
GPT teacher head0.408
Teacher spread0.262 · 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

Citations28
Published2009
Admission routes2
Has abstractyes

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