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Record W4380521252 · doi:10.6000/1929-4409.2020.09.22

SHORT COMMUNICATION: COVID-19 Pandemic and Attitude of Citizens in Bandung City Indonesia (Case Study in Cibiru Subdistrict)

2022· article· en· W4380521252 on OpenAlexvenueno aff
Asep Sumaryana, Toni Toharudin, Rezzy Eko Caraka, Resa Septiani Pontoh, Rung-Ching Chen, Bens Pardamean

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsnot available
FundersMinistry of Education, IndiaChaoyang University of Technology
KeywordsGovernment (linguistics)PandemicSurrenderCoronavirus disease 2019 (COVID-19)EnforcementWork (physics)Public relationsCompensation (psychology)PsychologyDescriptive researchSettlement (finance)BusinessPolitical scienceSociologyLawSocial psychologyMedicineEngineeringSocial science

Abstract

fetched live from OpenAlex

In the beginning, the pandemic panicked the people of Cibiru. Over time, the case fell in line with the increasing number of patients recovering. In addition, different views between elements of government make people surrender and believe in the power of nature's creator. Under these conditions, the researchers were interested in learning more. The study was conducted using a descriptive analysis of a number of parties regarding economic and social activities. The results show that there are three important components: First, trust builds the creator and reduces to the government component, communication that a number of parties do not work consistently when responding to COVID-19, and enforcement of unclear rules. In a nutshell. The citizens, grouped into two groups, agree that a pandemic is dangerous and urge them to follow values in the form of existing rules. Also,The pandemic communication competes in a short time and therefore cannot be carried out interactively.The government’s assertiveness of forcing residents to be at home becomes difficult as compensation can be granted for lost opportunities to seek family income Lastly, due to the preparation of the strategy that precedes the arrival of a pandemic, it cannot be face wisely.

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)0.003
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 score0.023
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.179
GPT teacher head0.434
Teacher spread0.255 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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