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Record W4399178724 · doi:10.4000/11qw5

Between Old and New Needs: The Issue of Inclusion of the Elderly before, during and after COVID-19. The Case of Rural Areas in Canada-Québec and Italy

2024· article· en· W4399178724 on OpenAlexvenueaboutno aff
Marco Alberio, Rebecca Plachesi

Bibliographic record

VenueInterventions économiques · 2024
Typearticle
Languageen
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsVulnerability (computing)PandemicContext (archaeology)Inclusion (mineral)Rural areaEconomic growthPublic healthCoronavirus disease 2019 (COVID-19)Social vulnerabilityPolitical scienceDevelopment economicsPsychologyGeographyMedicinePsychological interventionNursingSocial psychology

Abstract

fetched live from OpenAlex

During the health crisis, the elderly were identified as being among those most at risk of developing complications in the event of contamination by the virus, so in Italy, Canada and many other parts of the world, various specific measures were implemented to protect them. However, these have mainly involved measures to reduce both physical and social contact. This has led to repercussions not only on the social and psychological well-being of seniors but also on their social participation and inclusion. According to these aspects, in this article we analyze the situations and experiences of the elderly (aged seventy and over) in rural areas, in Italy and Canada, trying to highlight the socio-territorial effects of this health crisis on seniors. Therefore, on one hand, the aim is to identify the aspects that have accentuated the vulnerability of seniors and, on the other hand, the protective and supportive measures that have enabled them to cope with the pandemic crisis and its consequences. Furthermore, we will illustrate the different efforts to respond to the complex issue of ageing (demographic dimension) within rural areas (socio-territorial dimension) in an emergency-pandemic context (socio-health dimension), asking whether or not the initiatives and processes implemented by a variety of actors (non-profit associations, local or public institutions) respond to the needs and requirements of seniors living (in) the areas under study.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.292

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 science0.0000.001
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 head0.035
GPT teacher head0.357
Teacher spread0.322 · 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 designObservational
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
Published2024
Admission routes2
Has abstractyes

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