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Record W4366424909 · doi:10.4000/articulo.5034

Becoming homebound by choice and constraint: a mixed-methods look into ageing and mobility transitions

2023· article· en· W4366424909 on OpenAlexaff
Michel Després

Bibliographic record

VenueArticulo – revue de sciences humaines · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsMitel (Canada)
Fundersnot available
KeywordsDiversity (politics)AutonomyTransition (genetics)Constraint (computer-aided design)PsychologyAdaptation (eye)GerontologySociologyPolitical scienceMedicineEngineering

Abstract

fetched live from OpenAlex

This paper focuses on the transition of mobility practices and more specifically how certain older individuals experience patterns of Déprises leading them to adopt a more homebound lifestyle. As individuals age and advance in their life cycle, their capacities for mobility are prone to change, along with their lifestyles. Sometimes these changes are voluntary and done in a proactive manner, sometimes they are the product of external events. In some instances, following a transition period, these changes can result in a loss of mobility capacities, a continuation or reconfiguration of activities, or sometimes even an extension of mobility capacities, and therefore autonomy. As shown in earlier research, this process takes place in ways that are as diverse as the life course of each individual. This diversity, however, is still underrepresented in research, where older adults are often studied as a block according to their age (65+, 75+). This paper aims to delve deeper into the events and process leading to transition in mobility capacities among diverse profiles of older adults living in urban and suburban environments. To do so, the paper first presents results from statistical analysis showing how mobility practices can differ in older adults of different age groups representing different moments of the life cycle. Focusing afterward on a specific profile (the Stay-at-home), the article uses interview data to illustrate how diverse events, decisions and adaptation strategies led diverse individuals to become more homebound over the course of ageing. The article exposes a diversity of situations among Stay-at-home individuals, with transitions that are chosen or suffered. We conclude on strategies this plurality of Stay-at-home use to maintain their mobility and how we can support them to help them keep their autonomy.

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)0.036
metaresearch head score (Gemma)0.044
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 score0.036
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.004
Science and technology studies0.0040.004
Scholarly communication0.0060.005
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.029
GPT teacher head0.360
Teacher spread0.331 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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