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Record W4392977221 · doi:10.3138/cjc-2023-0003

The Role of Municipalities in Communicating for Community Resilience during the COVID-19 Pandemic: A Study of Niagara Region’s Crisis Communication

2024· article· en· W4392977221 on OpenAlexaffvenue
Duncan Koerber, Tim Ribaric, Fletcher Johnson, Cal Murgu, David Sharron

Bibliographic record

VenueCanadian Journal of Communication · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsWestern UniversityBrock University
Fundersnot available
KeywordsResilience (materials science)Coronavirus disease 2019 (COVID-19)PandemicCrisis communicationCommunity resilience2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Political scienceBusinessSociologyGeographyPublic relationsVirologyMedicineEngineering

Abstract

fetched live from OpenAlex

Background: Municipal governments have played an important but underappreciated role in crisis communication for community resilience during the COVID-19 pandemic. Analysis: This study analyzes the Niagara Region municipal webpage communication from web archives over the first two years of the pandemic, employing computational research methods and close reading to understand the strengths and deficiencies of municipal COVID-19 communication. Conclusion and implications: This study finds that the communication of the upper-tier municipality Niagara Region addressed the needs of citizens; however, the communication of the lower-tier municipalities varied and showed deficiencies.

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)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.561

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.003
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.082
GPT teacher head0.370
Teacher spread0.288 · 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 designQualitative
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
Published2024
Admission routes2
Has abstractyes

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