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Record W4319601225 · doi:10.54097/ehss.v8i.4239

Culture, Virus, Anxiety: Global Anxiety Level during the COVID-19 Pandemic Using a Cultural Lens

2023· article· en· W4319601225 on OpenAlexaff
Zichen Zhang

Bibliographic record

VenueJournal of Education Humanities and Social Sciences · 2023
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAnxietyPandemicPsychologyMental healthPanicCoronavirus disease 2019 (COVID-19)Clinical psychologyCognitionDevelopmental psychologySocial psychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

The world average anxiety level has increased since the 2019 outbreak of the new coronavirus. Although there are many studies on pandemics and anxiety levels, few have examined predictors of anxiety during the pandemic and possible pathways of influence, specifically comparing regional differences under different cultural influences. This paper argues that culture and cognition as the two main predictors of rising global anxiety levels, as well as provides an analysis of panic buying as an example of maladaptive anxiety, through a re-analysis of the existing literature. The findings of the paper suggest that culture, especially when recruiting participants from multiple countries and regions, is an essential factor in conducting psychological research. One of the limitations of previous studies is the lack of data across all phases of COVID-19. Future research should conduct longitudinal studies to examine the dynamic changes over time. The results could contribute to the study of the mental health of culturally diverse groups affected by 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.413
GPT teacher head0.508
Teacher spread0.095 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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