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Record W4323652877 · doi:10.1080/0361073x.2022.2163831

Increase in Linguistic Complexity in Older Adults During COVID-19

2023· article· en· W4323652877 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueExperimental Aging Research · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsMcMaster University
FundersMcMaster UniversityWilson Foundation
KeywordsNarrativeCoronavirus disease 2019 (COVID-19)CognitionCreativityPsychologyPandemicCognitive skillLinguisticsSocial psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

The reported psychological impact of the COVID-19 pandemic and related public health measures included a decline in cognitive functioning in older adults. Cognitive functioning is known to correlate with the lexical and syntactic complexity of an individual’s linguistic productions. We examined written narratives from the CoSoWELL corpus (v 1.0), collected from over 1,000 U.S. and Canadian older adults (55+ y.o.) before and during the first year of the pandemic. We expected a decrease in the linguistic complexity of the narratives, given the oft-reported reduction in cognitive functioning associated with COVID-19. Contrary to this expectation, all measures of linguistic complexity showed a steady increase from the pre-pandemic level throughout the first year of the global lockdown. We discuss possible reasons for this boost in light of exiting theories of cognition and offer a speculative link between the finding and reports of increased creativity during the pandemic.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.182
GPT teacher head0.468
Teacher spread0.286 · 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