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Record W834323105 · doi:10.18151/7217512

Just Keep Tweeting: Emergency Responder's Social Media Use Before and During Emergencies

2015· article· en· W834323105 on OpenAlexaff
Annemijn F. van Gorp, Nicolai Pogrebnyakov, Edgar Maldonado

Bibliographic record

VenueCBS Research Portal (Copenhagen Business School) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSocial mediaFirst responderComputer scienceInternet privacyBusinessMedical emergencyWorld Wide WebMedicine

Abstract

fetched live from OpenAlex

This study investigates how emergency response organizations use social media during emergency preparedness and response. Using qualitative (interviews and documents) and quantitative (Facebook posts) data, the study identifies several uses of social media in emergency preparedness and emergency management, as well as the organizational context that affects this use. Findings indicate that social media support various purposes of use, including information dissemination, obtaining input from the public and other organizations, and participation by other emergency response organizations. Branding of the organization during the emergency preparedness phase was found to be an important aspect of information dissemination, and helps social media to be useful tool to connect with the public and other organizations during the emergency response phase. Nevertheless, social media use in the emergency response domain still has to overcome leadership and staff adoption barriers.

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)0.005
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0030.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.234
GPT teacher head0.426
Teacher spread0.192 · 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.

Study designNot applicable
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

Citations12
Published2015
Admission routes1
Has abstractyes

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