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Record W3135878296 · doi:10.1177/1368430220983452

Ageism in the time of COVID-19

2021· article· en· W3135878296 on OpenAlexafffund
Hannah J. Swift, Alison L. Chasteen

Bibliographic record

VenueGroup Processes & Intergroup Relations · 2021
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPandemicCoronavirus disease 2019 (COVID-19)PsychologyCohesion (chemistry)2019-20 coronavirus outbreakSocial psychologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)HomogeneousOrder (exchange)Sociology

Abstract

fetched live from OpenAlex

In this article, we outline how the response to the coronavirus (COVID-19) pandemic has the potential to fundamentally change how we think and feel about our own age, and how we think and feel about other age groups. Specifically, we outline how discourse surrounding the pandemic has strengthened the homogeneous view of older adults as vulnerable, has socially stigmatized being an older adult, and has exacerbated hostile and benevolent expressions of ageism. We explore the impact of these changing dynamics on intergenerational cohesion and relations, and propose that understanding theories of ageism will be essential for how we handle future pandemics in order to reduce the potential negative impact of crises on individuals as well as on communities and societies.

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)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0100.019
Scholarly communication0.0050.005
Open science0.0010.009
Research integrity0.0020.009
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.373
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 designNot applicable
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

Citations136
Published2021
Admission routes2
Has abstractyes

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