GRF · Information Integrity and Public Trust

Science communication

Science reaches the public through journals, press releases, media, social platforms and advisers to government. Along the way, uncertainty is dropped, preliminary results are presented as settled, and corrections lag. Good science communication states what is known, how confident scientists are and what would change their view. This page sets out how science communication works and fails, the records that show it, and who decides.

01Register

Science communication on the record.

02The question

Science communication: how the risk develops.

Uncertainty and honest communication. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

Mechanism

Uncertainty is lost in translation

Caveats in papers disappear in press releases and headlines. Calibrated language helps, but competition for attention pushes towards certainty.

Mechanism

Preprints move fast

Preprints share findings before peer review. They speed science and can spread unreviewed claims widely before errors are caught.

Mechanism

Corrections lag

Retractions and corrections arrive long after the original claim and reach fewer people. Retracted papers continue to be cited.

Mechanism

Messengers shape reception

Audiences weigh scientific claims by who delivers them and whether they fit prior beliefs. Engagement and listening matter as much as accuracy.

03Monitor

Narrative monitor.

The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.

Narrative monitor

Science communication · Crisis information cell · Week 34

Harmful rumour spreadingGRF · Information Integrity and Public Trust

Narratives

Tap water poisoned after flood82HighFalseCorrection out
Shelters charging fees61MediumFalseDrafting
Dam about to fail78HighCheckingHolding line
Aid only for registered voters41MediumFalsePrebunked

Spread

Response protocol

  1. Detectmonitor
  2. Verifyprovenance
  3. Assess harmthreshold
  4. Respondcorrect · prebunk
  5. Reporttransparency
Narrative monitor: the screen's structure, terms and states for Science communication.Example names and illustrative values; a design, not a record or a live system.
04Indicators

What is measured, and how well.

Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.

IndicatorUnitCadenceSource typeLabel
Retractionscount by fieldannualRetraction Watch DatabaseREPORTED
Citations of retracted papers after retractioncountperiodicBibliometric studiesESTIMATED
Press releases with exaggerationshare in sampled releasesper studyContent analysesESTIMATED
Trust in scientistsshare of respondentsperiodicWellcome Global MonitorESTIMATED
Science advisory bodies publishing advicecounton changeGovernment recordsPublished statistics
Preprints later published after peer reviewshareper studyBibliometric studiesESTIMATED
05Decision model

What tips a population into acting.

How the share of early movers and the thresholds people hold decide whether a protective behaviour, or a false narrative, stays local or spreads to most people. Teaching model with stated illustrative values, not a prediction.

Controls

Mean threshold (share of neighbours)
18%
Spread of thresholds
8 points
Early movers
2.0% of people
Contacts per person
8

Readouts

Share who acted in the end
100%
Global cascade
Yes
Steps to settle
12
Numbers, methods and sources
StepShare who have acted (%)
01.8
15.8
215.8
330.3
445.8
559.5
672.8
784.0
891.0
996.0
1099.8
11100.0
12100.0

Methods

  1. Threshold models of collective behaviour Granovetter (1978), American Journal of Sociology 83
  2. Global cascades on random networks Watts (2002), PNAS 99
  3. Complex contagions Centola and Macy (2007), American Journal of Sociology 113
  4. One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley

Data

No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme's own evidence.

What tips a population into acting. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: Threshold models of collective behaviour (Granovetter (1978), American Journal of Sociology 83); Global cascades on random networks (Watts (2002), PNAS 99); Complex contagions (Centola and Macy (2007), American Journal of Sociology 113).
06Sources

Where the evidence comes from.

Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.

SourceWhat it givesLicence class
Retraction Watch DatabaseRetracted papers with reasonsFree to access via Crossref, terms to check
Crossref metadataPublication, correction and retraction metadataMetadata free, CC0 for most fields
Wellcome Global MonitorPublic trust in scienceFree to read, terms to check
IPCC guidance on consistent treatment of uncertaintiesCalibrated language for confidence and likelihoodFree, IPCC terms
INGSA recordsInternational network of government science adviceFree to read, terms to check
07Implementation

From mandate to evaluation, by pillar.

The steps an instrument takes from mandate to evaluation, each with the pillar that runs it, and the decisions that stay with the authority. Teaching model with stated illustrative values, not a prediction.

  1. Mandate and problem framing Competent authority (outside the programme)
    A competent authority frames the problem and the mandate under its own rules. Howlett, Ramesh and Perl (2009)
  2. Evidence and system model Foundry
    The system is modelled with its feedbacks, data and stated limits. OECD (2014), principle 2
  3. Options appraised with scenarios Foundry
    Instruments are compared under scenarios, with uncertainty shown. Hood (1983)
  4. Exercise with stakeholders Universe
    The options are tested in an exercise with those who would implement and bear them. OECD (2014), principle 3
  5. Standard or guidance drafted Nexus Standards
    What works is codified as a standard or guidance, open to comment. Nexus Standards process
  6. Decision by the authority Competent authority (outside the programme)
    The authority decides, outside the programme, with the evidence on record. Howlett, Ramesh and Perl (2009)
  7. Capacity and training Risk Academy
    Those who implement are trained on the decided instrument and its data. Sendai Framework (2015), priority 2
  8. Monitoring and public report Reports
    Indicators are published with sources, limits and corrections. OECD (2014), principle 5
  9. Evaluation and revision Nexus Standards
    Results return to the standard and the model: the cycle closes. Howlett, Ramesh and Perl (2009)

Methods

  1. Policy cycle Howlett, Ramesh and Perl (2009), Studying Public Policy, Oxford University Press
  2. Governance of critical risks OECD (2014), Recommendation of the Council on the Governance of Critical Risks
  3. Layered drawing of directed graphs Sugiyama, Tagawa and Toda (1981), IEEE SMC 11
From mandate to evaluation, by pillar: the steps as recorded, each with its pillar; sources as cited on each step.
08Decisions

Who decides, and what the evidence serves.

Information Integrity and Public Trust prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

Who decidesThe questionEvidence this page serves
Research institutions and press officesHow findings are announced and uncertainty statedEvidence on exaggeration and its effects
Journals and preprint serversHow corrections and retractions are flaggedRetraction records and practice
Government science advisersHow advice and its uncertainty are publishedComparative advice systems
NewsroomsHow to report preliminary and contested scienceReporting guidelines and research

Outputs this topic produces

  • Guide to calibrated uncertainty language
  • Comparative notes on science advice systems and transparency
  • Dialogue briefs on preprints in public debate
  • Questions for institutions on correcting the record
09Instruments and commitments

How science communication is governed: instruments, mandates and commitments.

The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.

Accountability cycle

How commitments on science communication are held to account, from commitment to correction.

  1. CommitGovernmentA commitment with a mandate and a legal basis.
  2. PlanLead agencyA national plan with owners and milestones.
  3. ResourceMinistry of financeA budget line or financing on record.
  4. ImplementAgencies and local governmentDelivery against the plan.
  5. ReportStatistics officeIndicators reported in agreed definitions.
  6. ReviewLegislature, audit, civil societyIndependent review of results and gaps.
  7. CorrectGovernmentChanges to the plan, published with reasons.
A generic accountability cycle; the owner of each step follows the country's own constitution and law.
Sendai Framework for Disaster Risk Reduction · UNDRRParis Agreement · UNFCCC2030 Agenda and the Sustainable Development Goals · United NationsInternational Health Regulations · WHO
10Core questions

What experts ask.

Science communication researchers ask how to be honest about uncertainty and still be useful.

  • How should scientific uncertainty be communicated to non-specialist audiences?
  • How does communicating changing evidence affect trust in science?
  • How should disagreement among experts be presented?
  • What responsibilities do scientists and institutions have when their findings are misused?
  • How do values and identity shape how people receive scientific information?
11Mechanisms and drivers

Uncertainty, values and trust.

Research suggests that communicating uncertainty honestly, for example as ranges or likelihoods with explanation, generally has small effects on trust and can increase perceived credibility, while overstated certainty that later proves wrong damages it. How uncertainty is framed matters: numerical ranges, verbal terms and visual formats are understood differently by different audiences.

People interpret scientific information through their values and identities. When scientific issues become associated with political or cultural identity, evidence alone rarely changes minds. Communication that respects audiences, acknowledges values and comes from trusted messengers tends to be more effective than repeated assertion of facts.

Why now: scientists and public bodies communicate risk under more scrutiny and faster cycles than before, and uncertainty is easily misread. The platform is designed to convene communicators and scientists on how uncertainty is stated, and to test messages in exercises before they are needed.

12Methods and data

How the evidence is built, and where it stops.

  1. 01

    Experimental communication research

    Testing formats for presenting uncertainty with social and behavioural science. Results vary by topic and audience.

  2. 02

    Media content analysis

    Studying how science is reported. Coverage varies across outlets and countries.

  3. 03

    Survey research

    Tracking trust in science over time. General trust differs from trust on specific topics.

  4. 04

    Case studies

    Examining communication during contested episodes. Hindsight can distort assessments.

13Methods

How it is studied, and what the methods cannot say.

14Questions

Questions and answers.

What is calibrated uncertainty language?
A fixed set of terms tied to probability ranges or confidence levels, such as the IPCC's likely and high confidence, used to state uncertainty consistently.
Should the public read preprints?
Preprints are useful but have not been peer reviewed. Responsible reporting says so and seeks independent comment.
Why are retracted papers still cited?
Because retraction notices are not always visible where people find papers, and citing authors may not check. Metadata on retractions helps.
Does admitting uncertainty reduce trust in science?
Research generally finds small effects, and honest uncertainty can increase credibility. Overstated certainty that later changes is more damaging.
Should experts present a single consensus view?
Where a strong consensus exists, saying so helps. Where experts genuinely disagree, presenting the range of views and the reasons for them is more honest.
Does GRF communicate science on behalf of GCRI?
No. Each institution speaks for itself. This platform studies science communication and convenes dialogue on it.
ReportsContribute

Contribute evidence from this page.

Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

Global Risks ForumInformation Integrity and Public TrustEvidence Brief
Information Integrity and Public Trust

Bring a governance question to the Forum.

Information and enquiries are open today. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.

The Global Risks Forum

Convening · leadership · urgency

Not for profit

Our articles, maps and twins are free to read and free to republish. Readers and partners keep it that way.

Partner with us

Who funds us

GRF is a not-for-profit institution. To ask who funds a piece of work, use the funding questions form.

Independence

Editors and the expert reviewers named on each article decide what we publish. Funders and partners do not review or approve articles before publication.

Licence

Articles: CC BY 4.0. Figures, maps, twins and data: CC BY 4.0. Other uses: ask through the permissions form.