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Record W4285478741 · doi:10.51952/9781447352570.ch004

Walking in the city: seniors’ experience in Canada and France

2021· book-chapter· en· W4285478741 on OpenAlexaboutno aff
Marie‐Soleil Cloutier, Florence Huguenin-Richard

Bibliographic record

VenuePolicy Press eBooks · 2021
Typebook-chapter
Languageen
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyGerontologyRegional scienceHistoryMedicine

Abstract

fetched live from OpenAlex

In Canada, as well as in other Western countries, mobility, defined as the ability to move between different activity sites, tends to decrease past 65 years old for all modes of transportation, even if today’s elderly are more motorized than before (Armoogum et al, 2010; Turcotte, 2012; Böcker et al, 2017). Accordingly, seniors’ mobility is characterized by a decrease in the number of trips and distances travelled to reach those activity sites (grocery stores, library, friend’s home, etc), a situation worsened by the loss of their driving licence (Lord et al, 2009a, 2009b; Chapon, 2010). Moreover, there is little attention given to seniors’ mobility experience outside of the actual, quantitatively measured, travel behaviour (Franke et al, 2019). Walking is therefore essential as an alternative mode of travel to nearby destinations and its promotion is a way to perpetuate seniors’ socialization and greater autonomy, a guarantee of healthy aging. A recent article on accessibility to retail activities in Spain highlighted again the importance of taking into account seniors in our mobility planning. The authors found that willingness to reach retail stores on foot by seniors (>65 years old) was significantly different from other population sub-groups, potentially contributing to social exclusion (Arranz-López et al, 2019). Long neglected to the benefit of the automobile, walking, a non-polluting mode of transport beneficial to health, is today revalorized in urban policies, particularly in major cities. However, this encouragement to walk should be based on an assessment of the safety and comfort of built urban environments in order to better document the (in) adequacy between the walking environment and the needs and travel habits of elderly pedestrians.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.927
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.081
GPT teacher head0.383
Teacher spread0.301 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes1
Has abstractyes

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