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From the Editors

2009· article· en· W2397336953 on OpenAlexaboutno aff
Michael Greenberg, Karen Lowrie

Bibliographic record

VenueRisk Analysis · 2009
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Resilience and Vulnerability Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRisk managementRisk assessmentHomeland securityActuarial scienceIT risk managementVulnerability (computing)Risk analysis (engineering)Risk management toolsFactor analysis of information riskTerrorismBusinessOperations researchEngineeringPolitical scienceComputer securityComputer scienceRisk management information systemsLawFinanceInformation system

Abstract

fetched live from OpenAlex

The articles in the July 2009 issue of Risk Analysis: An International Journal demonstrate the broad range of subjects addressed by our journal and the global nature of risk analysis. The nine articles are written by authors representing six different countries, including: the United States; Canada; the United Kingdom; the Netherlands; Denmark; and New Zealand. The issue begins with a profile of B. John Garrick, a pioneer in quantitative risk analysis and one of our most illustrious members. The profile is followed by a perspective written by Tony Cox that challenges the practice of making risk management decisions without determining how one risk reduction action changes other risks. In other words, if cumulative risk reduction is considered, addressing the highest ranked risk may not be the best investment. The author applies this thinking to issues such as homeland security and terrorism risk assessment, environmental risk management, information system vulnerability rating, and business risks. Shahid Suddle develops quantitative risk assessment (QRA) and risk management approaches aimed at reducing falling objects during construction. If you have ever been hit by something falling from a construction project and your complaints have been brushed off by the on-site manager (as this Editor was), then the paper should provide comfort that the risks posed to third party safety can be reduced. The paper describes causal factors and uses the historical record and engineering experience to estimate the likelihood of falling materials, inputting these parameters into a Bayesian network to calculate human and financial risks. The author suggests lessons learned from these analyses that can be integrated into building design and construction. The recent swine flu outbreak reminds us that pandemic influenza is a serious world-wide public health threat. Many experts assert that we will not initially have an effective vaccine, and when we get a vaccine, there will be insufficient quantities and medical facilities will not have the capacity to treat all the infirm. Lawrence M. Wein and Michael Atkinson construct an influenza dispersion model with the goal of reducing exposure, especially during the initial wave of the event. Their model predicts that the key infection control measure is the use of N95 respirators. If households and businesses use these in combination with humidifiers and ventilation, a 40 to 70 percent reduction in the threshold parameter (which dictates whether or not an epidemic breaks out) is achievable. In 1984, the Editor first saw red tides in the Adriatic Sea, and can still recall the horrified expressions and behavioral changes of people who had gone to the coast to swim, fish, water ski, and windsurf. Highly concentrated algal blooms have become all too common. Kuhar et al. examine public perception of red tide on Florida's west coast beaches. Funded by the U.S. National Institute of Environmental Health Sciences, the authors use surveys and semi-structured interviews, observing wide variations in public responses to the red tide. Those who were better informed and had the most up-to-date information were less likely to amplify the risk. Comparisons of and public perceptions of hazards have helped us understand differences between scientist and public evaluation of risks. Funded by the European Commission, Hagemann and Scholderer elicit mental models to understand expert-consumer reactions to genetically modified foods in Denmark. While experts tend to assess risk and benefit using scientific methods, consumers use a variety of approaches that emphasize uncertainties. This study confirms previous literature that suggests a “clash of cultures,” or basic contrasts in risk assessment between experts and the public. Health-related damages associated with coal-fired power plant emissions have been a long-standing concern. Funded by the EPA/Harvard Center on Ambient Particle Health Effects and using a series of air quality and deposition models, Jonathan Levy et al. examine monetized damages associated with 407 coal-fired power plants in the United States. Focusing on premature mortality from fine particulate matter (PM2.5), the authors find complex interactions among exposed population distribution, weather patterns, and emission controls. The authors argue for pollution control strategies that take into account the variability in the magnitude and type of damages across facilities. Petra Mullner et al. offer a modified version of a Bayesian approach originally developed by Hald et al. to estimate the contribution of different food sources to the burden of human salmonellosis. Funded by the New Zealand Food Safety Authority, the authors modify the Hald model by introducing uncertainty into the estimates of source prevalence. The authors test their model with campylobacteriosis and salmonellosis in New Zealand. Medical practitioners are increasingly asked to use standard protocols in order to reduce errors and produce the best and most efficient health outcomes. Eileen Munro argues that standardization may have gone too far, and that what constitutes “good practice” in the case of children's safety or welfare may, in fact, impede beneficial innovations. Yue Wu et al. examine the relationship between maritime risks and weather conditions. Funded by the Canadian Coast Guard, the GEOIDE National Centre of Excellence and the Natural Sciences, and the Engineering Research Council of Canada, the authors examined Relative Incident Rate (RIR) for fishing incidents recorded in Atlantic Canadian waters. They find wave height and ice concentration to be stronger predictors than fog and precipitation. The analysis offers plausible risk reduction opportunities. The July issue concludes with a review of Nozer Singpurwalla's Reliability and Risk. Reviewer R. T. Smythe reports that the author successfully explains the purpose of the models, their limitations, and history, and provides an extensive bibliography. He sees it as a good reference for experts, but perhaps lacking a sufficient number of examples, problems and other features that would make it a good text for students.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.002
GPT teacher head0.199
Teacher spread0.197 · 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 designSimulation or modeling
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
Published2009
Admission routes1
Has abstractyes

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