Evidence map›Paper›PMID 42026857›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2026

Looking for a Straw in a Haystack by Bridging the Cracks Between Individual Judgments: Narrowing the Knowledge Gap To Anticipate Surprises by Transforming Risk Assessors' Small Worlds Into Large Worlds.

James Derbyshire, Terje Aven

Abstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Potential Surprise Theory as a Practical and Theoretical Cornerstone of the Uncertainty-Based Perspective on Risk.Risk analysis : an official publication of the Society for Risk Analysis · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

James DerbyshireChester Business School, Chester University, Chester, UK.
Terje AvenDepartment of Security, Economics and Planning, University of Stavanger, Stavanger, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The world is constantly changing, yet a risk assessment is based on the knowledge available at one point in time. There will therefore be a gap between the range of possibilities known or conceivable to the assessor at that time and all the possibilities that could occur over infinite time. This will leave the door open to surprises. Anticipating surprises, therefore, requires the narrowing of this knowledge gap. We outline an approach to narrowing it that transforms risk assessors' small-world representations into a large-world representation by configuring them into a small-world network. Small-world representations are individuals' partial and subjective perspectives on an aspect of reality. What we call a large-world representation integrates these small-world representations. This transformation narrows the knowledge gap by integrating dispersed knowledge about, and intersecting alternative framings of, a focal risk, thereby dynamically updating the knowledge landscape underpinning its assessment. We use the 9/11 attack as an example. That surprise resulted from a failure to intersect the frames "suicide attack" and "hijacking," meaning that the possibility of a "suicide hijacking" went unconsidered. Configuring risk assessors into a small-world network would have increased the chance that these two frames would intersect in a risk assessment, thereby anticipating this surprise outcome. In sum, the approach we outline operationalizes the recently extended (C, U) risk-assessment framework. It increases the chance that surprises are anticipated by enabling risk assessors to see as an integral whole what they could otherwise see only fragmentarily.

Indexed as

risk assessmentsmall‐world networksurpriseuncertainty

Identifiers

PMID42026857
PMCPMC13106966

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.