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Record W2048271753 · doi:10.1080/14427591.2012.735613

Moving Beyond ‘Aging In Place’ to Understand Migration and Aging: Place Making and the Centrality Of Occupation

2012· article· en· W2048271753 on OpenAlexaff
Karin Johansson, Debbie Laliberté Rudman, Margarita Mondaca, Melissa Park, Mark Luborsky, Staffan Josephsson, Eric Asaba

Bibliographic record

VenueJournal of Occupational Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsMcGill UniversityWestern University
FundersNational Institute on AgingToyota Foundation
KeywordsAging in placeNegotiationSociologyContext (archaeology)CentralityDiversity (politics)Occupational scienceProcess (computing)Place makingEpistemologyPsychologySocial scienceGeographyComputer science

Abstract

fetched live from OpenAlex

'Aging in place' has become a key conceptual framework for understanding and addressing place within the aging process. However, aging in place has been critiqued for not sufficiently providing tools to understand relations or transactions between aging and place, and for not matching the diversity of contemporary society in which people are moving between and across nations more than ever before. In this article, the authors draw from concepts of place and migration that are becoming increasingly visible in occupational science. The concept of 'aging in place' is critically examined as an example of an ideal where the understanding of place is insufficiently dynamic in a context of migration. The authors suggest that the concept of place making can instead be a useful tool to understand how occupation can be drawn upon to negotiate relationships that connect people to different places around the world, how the negotiated relations are embedded within the occupations that fill daily lives, and how this process is contextualized and enacted in relation to resources and capabilities.

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)0.002
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 score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0050.037
Scholarly communication0.0070.012
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.359
Teacher spread0.320 · 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

Citations85
Published2012
Admission routes1
Has abstractyes

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Same venueJournal of Occupational ScienceSame topicMigration, Aging, and Tourism StudiesFrench-language works237,207