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Record W2143810862 · doi:10.1093/rpd/ncq273

Psychosocial considerations for mass decontamination

2010· article· en· W2143810862 on OpenAlexaff
Louise Lemyre, Candice Y. Johnson, Wayne Corneil

Bibliographic record

VenueRadiation Protection Dosimetry · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsWilfrid Laurier UniversityUniversity of Ottawa
Fundersnot available
KeywordsPsychosocialLibrary sciencePolitical scienceMedia studiesMedicineSociologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

Mass exposure to explosions, infectious agents, foodborne illnesses, chemicals or radiological materials may require mass decontamination that have critical psychosocial implications for the public and for both traditional and non-traditional responders in terms of impact and of response. Five main issues are common to mass decontamination events: (i) perception, (ii) somatisation, (iii) media role and communication, (iv) information sharing, (v) behavioural guidance and (vi) organisational issues. Empirical evidence is drawn from a number of cases, including Chernobyl; Goiania, Brazil; the sarin gas attack in Tokyo; the anthrax attacks in the USA; Three Mile Island; and by features of the 2003 severe acute respiratory syndrome pandemic. In this paper, a common platform for mass casualty management is explored and suggestions for mass interventions are proposed across the complete event timeline, from pre-event threat and warning stages through to the impact and reconstruction phases. Implication for responders, healthcare and emergency infrastructure, public behaviour, screening processes, risk communication and media management are described.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.028
GPT teacher head0.336
Teacher spread0.307 · 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 designTheoretical or conceptual
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

Citations22
Published2010
Admission routes1
Has abstractyes

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