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Record W2393302407 · doi:10.1017/s0144686x15000288

Canadian power mobility device users' experiences of ageing with mobility impairments

2015· article· en· W2393302407 on OpenAlexafffundabout
Alexandra Korotchenko, Laura Hurd Clarke

Bibliographic record

VenueAgeing and Society · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsCognitive reframingContext (archaeology)Power (physics)Embodied cognitionPsychologyMobilitiesSocial mobilitySociologySocial psychologyComputer scienceHistorySocial science

Abstract

fetched live from OpenAlex

ABSTRACT In this article, we draw upon interviews with 14 men and 15 women aged 51–92 to examine the embodied experiences of Canadian power mobility device users. In particular, we investigate how individuals ageing with mobility impairments perceived and experienced the practical impacts and symbolic cultural connotations of utilising a power mobility device. Our findings reveal that those participants who had begun to use their power mobility devices later in life were dismayed by and apprehensive about the significance of their diminishing physical abilities in the context of the societal privileging of youthful and able bodies. At the same time, the participants who had used a power mobility device from a young age were fearful of prospective bodily declines, and discussed the significance and consequences of being unable to continue to operate their power mobility devices autonomously in the future. We consider the ways in which the participants attempted to manage, mitigate and reframe their experiences of utilising power mobility devices in discriminatory environments. We discuss our findings in relation to on-going theoretical debates pertaining to the concepts of ‘biographical disruption’ and the third and fourth ages.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.267
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.305
Teacher spread0.281 · 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 teacher head, 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

Citations11
Published2015
Admission routes3
Has abstractyes

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