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Record W4225299886 · doi:10.1177/01640275221092177

COVID-Related Perceptions of the Future and Purpose in Life Among Older Canadian Women

2022· article· en· W4225299886 on OpenAlexafffundabout
Nicky J. Newton, Hua Huo, Lauren Hytman, Cara Ryan

Bibliographic record

VenueResearch on Aging · 2022
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsYorkville UniversityToronto Metropolitan UniversityWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCoronavirus disease 2019 (COVID-19)PsychologyPerspective (graphical)PandemicPerceptionGerontologyDemography2019-20 coronavirus outbreakMedicineSociology

Abstract

fetched live from OpenAlex

Global events that prime thoughts of proximity to death (e.g., the COVID-19 pandemic) can compress individuals’ perceptions of future time horizons, and previous studies have found that compressed time horizons can be beneficial for older adults’ well-being. However, findings from recent studies are mixed, and studies of well-being during the early months of COVID-19 show that older adults have fared comparatively well. The current study examines relationships between Future Time Perspective (FTP), COVID-19 impact, and purpose in life (PIL) among older Canadian women ( N = 190; ages 59+). We expected that total FTP would be positively associated with PIL but that FTP subscales would be associated with PIL in different ways; COVID-19 impact would not be associated with PIL, but COVID-19 impact would moderate the FTP-PIL relationship. We found partial support for these hypotheses, as well as prevalence of social connection themes in open-ended question responses regarding COVID-19 impact.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0140.000

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 head0.071
GPT teacher head0.429
Teacher spread0.358 · 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.

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

Citations6
Published2022
Admission routes3
Has abstractyes

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