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Record W3178741733 · doi:10.3389/fpsyg.2021.647830

Obligation or Desire: Variation in Motivation for Compliance With COVID-19 Public Health Guidance

2021· article· en· W3178741733 on OpenAlexaff
Ting Ai, Glenn Adams, Xian Zhao

Bibliographic record

VenueFrontiers in Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProsocial behaviorObligationCompliance (psychology)PsychologySocial distanceSocial psychologyVariation (astronomy)DistancingCoronavirus disease 2019 (COVID-19)Independence (probability theory)Public healthPolitical scienceDiseaseMedicineLawNursing

Abstract

fetched live from OpenAlex

Why do people comply with coronavirus disease 2019 (COVID-19) public health guidance? This study considers cultural-psychological foundations of variation in beliefs about motivations for such compliance. Specifically, we focused on beliefs about two sources of prosocial motivation: desire to protect others and obligation to society. Across two studies, we observed that the relative emphasis on the desire to protect others (vs. the obligation to the community) as an explanation for compliance was greater in the United States settings associated with cultural ecologies of abstracted independence than in Chinese settings associated with cultural ecologies of embedded interdependence. We observed these patterns for explanations of psychological experience of both others (Study 1) and self (Study 2), and for compliance with mandates for both social distancing and face masks (Study 2). Discussion of results considers both practical implications for motivating compliance with public health guidance and theoretical implications for denaturalizing prevailing accounts of prosocial motivation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.772
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.336
GPT teacher head0.458
Teacher spread0.122 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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