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Record W2074008618 · doi:10.1080/13698570802166431

Communicating about emerging infectious disease: The importance of research

2008· article· en· W2074008618 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Risk & Society · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEmerging infectious diseaseInfectious disease (medical specialty)DiseasePublic healthPublic relationsHealth communicationCommunication studiesEmerging technologiesMedicinePolitical scienceComputer scienceSociologySocial science

Abstract

fetched live from OpenAlex

Emerging infectious diseases have taken on renewed significance in the public health sector since the 1990s. Worldwide, governments are preparing emergency plans to guide them; their plans acknowledge that communication will be vital in the event of an outbreak. However, much of the emerging infectious disease communication literature deals with one-way transmission of facts to the public by experts. Little attention is paid to how differently various groups conceptualize risk, or to the idea that there is more to communication than the intentional transfer of information. Emerging infectious disease communication is often based in traditional health promotion or emergency/crisis communication literature, where it is assumed that the only ‘enemy’ is the disease, the right course of action is obvious and the expertise (coming from a public health assumed to be value-free) will not be questioned. Research tends to be limited to exploring barriers to understanding or education, to facilitate better message development. Emerging infectious disease communication research should be broadened to include exploration of implicit assumptions about the nature of the problem at hand (and how to deal with it) as well as the concepts of uncertainty, trust, power, values and biases. Recent risk communication theory, whose focus has historically been on more obviously controversial technological/environmental situations, should guide such research, as it would highlight important contextual factors in which to embed emerging infectious disease communication. This article reviews existing emerging infectious disease communications literature, discusses risk communications theories that could broaden emerging infectious disease communication research, and suggests next steps in a research agenda.

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.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
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 head0.114
GPT teacher head0.469
Teacher spread0.355 · 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