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Record W4391910789 · doi:10.1038/s41467-024-44999-5

Changes in social norms during the early stages of the COVID-19 pandemic across 43 countries

2024· article· en· W4391910789 on OpenAlexaff
Giulia Andrighetto, Áron Székely, Andrea Guido, Michele J. Gelfand, Jered Abernathy, Gizem Arıkan, Zeynep Aycan, Shweta Bankar, Davide Barrera, Dana Basnight-Brown, Anabel Belaus, Elizaveta Berezina, Sheyla Blumen, Paweł Boski, Huyen Thi Thu Bui, Juan-Camilo Cárdenas, Đorđe Čekrlija, Mícheál de Barra, Piyanjali de Zoysa, Angela Rachael Dorrough, Jan B. Engelmann, Hyun Euh, Susann Fiedler, Olivia Foster‐Gimbel, Gonçalo Freitas, Márta Fülöp, Ragna B. Garðarsdóttir, Colin Mathew Hugues D. Gill, Andreas Glöckner, Sylvie Graf, Ani Grigoryan, Katarzyna Growiec, Hirofumi Hashimoto, Tim Hopthrow, Martina Hřebı́čková, Hirotaka Imada, Yoshio Kamijo, Hansika Kapoor, Yoshihisa Kashima, Narine Khachatryan, Natalia Kharchenko, Diana Marcela León, Lisa M. Leslie, Yang Li, Kadi Liik, Marco Tullio Liuzza, Angela T. Maitner, Pavan Mamidi, Michele McArdle, Imed Medhioub, Maria Luísa Mendes Teixeira, Sari Mentser, Francisco J. Morales, Jayanth Narayanan, Kohei Nitta, Ravit Nussinson, Nneoma G. Onyedire, Ike E. Onyishi, Evgeny Osin, Seniha Özden, Penny Panagiotopoulou, Oleksandr Pereverziev, Lorena R. Pérez-Floriano, Anna‐Maija Pirttilä‐Backman, Marianna Pogosyan, Jana L. Raver, Cecilia Reyna, Ricardo Borges Rodrigues, Sara Romanò, Pedro Romero, Inari Sakki, Ángel Sánchez, Sara Sherbaji, Brent Simpson, Lorenzo Spadoni, Eftychia Stamkou, Giovanni A. Travaglino, Paul A. M. Van Lange, Fiona Fira Winata, Rizqy Amelia Zein, Qingpeng Zhang, Kimmo Eriksson

Bibliographic record

VenueNature Communications · 2024
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsQueen's University
FundersAgencia Estatal de InvestigaciónVetenskapsrådetNational Research University Higher School of EconomicsEngineering and Physical Sciences Research CouncilUK Research and InnovationAkademie Věd České RepublikyNemzeti Kutatási, Fejlesztési és Innovaciós AlapGrantová Agentura České RepublikyHungarian Scientific Research FundNederlandse Organisatie voor Wetenschappelijk OnderzoekMinistero dell’Istruzione, dell’Università e della RicercaNemzeti Kutatási Fejlesztési és Innovációs HivatalEuropean Regional Development FundEuropean CommissionArmy Research OfficeKnut och Alice Wallenbergs Stiftelse
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Norm (philosophy)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)EnforcementSocial psychologySocial distancePsychologyPolitical scienceDevelopment economicsDiseaseInfectious disease (medical specialty)BiologyMedicineVirologyEconomicsLaw

Abstract

fetched live from OpenAlex

The emergence of COVID-19 dramatically changed social behavior across societies and contexts. Here we study whether social norms also changed. Specifically, we study this question for cultural tightness (the degree to which societies generally have strong norms), specific social norms (e.g. stealing, hand washing), and norms about enforcement, using survey data from 30,431 respondents in 43 countries recorded before and in the early stages following the emergence of COVID-19. Using variation in disease intensity, we shed light on the mechanisms predicting changes in social norm measures. We find evidence that, after the emergence of the COVID-19 pandemic, hand washing norms increased while tightness and punishing frequency slightly decreased but observe no evidence for a robust change in most other norms. Thus, at least in the short term, our findings suggest that cultures are largely stable to pandemic threats except in those norms, hand washing in this case, that are perceived to be directly relevant to dealing with the collective threat.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.125
GPT teacher head0.451
Teacher spread0.326 · 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 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

Citations22
Published2024
Admission routes1
Has abstractyes

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