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Record W3164387020 · doi:10.1016/j.socec.2023.101983

Expectations, reference points, and compliance with COVID-19 social distancing measures

2023· article· en· W3164387020 on OpenAlexafffund
Guglielmo Briscese, Nicola Lacetera, Mario Macis, Mirco Tonin

Bibliographic record

VenueJournal of Behavioral and Experimental Economics · 2023
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsUniversity of Toronto
FundersLibera Università di BolzanoUniversità di BolognaUniversità BocconiJohns Hopkins UniversityUniversity of PittsburghUniversity of Toronto
KeywordsSocial distanceCoronavirus disease 2019 (COVID-19)Compliance (psychology)Context (archaeology)Extension (predicate logic)PandemicSocial psychologyPsychologyIsolation (microbiology)Duration (music)Test (biology)Social isolation2019-20 coronavirus outbreakDistancingSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Demographic economicsEconomicsMedicineComputer scienceGeographyVirology

Abstract

fetched live from OpenAlex

We study the behavioral impact of announcements about the duration of a policy and their relationship with people's expectations in the context of the COVID-19 lockdowns. We surveyed representative samples of Italian residents at three moments of the first wave of the pandemic to test how intentions to comply with social-isolation measures depend on the duration of their possible extension. Individuals were more likely to reduce, and less likely to increase, their compliance effort if the hypothetical extension was longer than they expected, whereas positive surprises had a lesser impact. The behavioral response to the (mis)match between expected versus hypothesized extensions is consistent with expectations acting as reference points and can help explain the increase in observed physical proximity in Italy following lockdown extension announcements. Our findings suggest that public authorities should consider citizens' expectations when announcing policy changes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.445
GPT teacher head0.468
Teacher spread0.023 · 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 source (direct Gemma or distilled Codex), 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

Citations64
Published2023
Admission routes2
Has abstractyes

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