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Record W4410494581 · doi:10.1016/j.dib.2025.111682

Dataset on cognitive and social well‑being of older adults around the COVID-19 pandemic: The CoSoWELL corpus of written life stories, release 2

2025· article· en· W4410494581 on OpenAlexaff
Aki-Juhani Kyröläinen, Victor Kuperman

Bibliographic record

VenueData in Brief · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsLonelinessSocial isolationCoronavirus disease 2019 (COVID-19)PandemicPsychologyNarrativeCognitionQuality of life (healthcare)Developmental psychologyGerontologySocial psychologyMedicinePsychiatryLiteratureArtPsychotherapist

Abstract

fetched live from OpenAlex

This paper presents the revised and extended release 2 of the Cognitive and Social Well-Being (CoSoWELL) project. The dataset comprises data that was collected n at 8 different time points in the three-year period, between March 2019 until March 2022, thereby covering the entire duration of the COVID-19 pandemic. More than 2000 unique North American older adults (range: 55-84 years old) took part in this data collection. The dataset contains sociodemographic information, along with data on perceived loneliness, the size and quality of social network, frequency of social interactions, and emotion regulation. Personal narratives were also collected, which consisted of personal stories that drew upon long-term, short-term and prospective memory. This dataset can be used to study linguistic markers of loneliness and social isolation in older adults, especially during the times of crisis.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.066
GPT teacher head0.383
Teacher spread0.317 · 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
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

Citations0
Published2025
Admission routes1
Has abstractyes

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