Evidence map›Paper›PMID 34512189›Full record

ArticleJournal of public affairs2021

The challenges of providing certainty in the face of wicked problems: Analysing the UK government's handling of the COVID-19 pandemic.

Darren G Lilleker, Thomas Stoeckle

Abstract read
In one paragraph

Article in Journal of public affairs, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Darren G LillekerDepartment of Humanities and Law Bournemouth University Poole UK.ORCID https://orcid.org/0000-0003-0403-8121
Thomas StoeckleDepartment of Humanities and Law Bournemouth University Poole UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Positioning Covid-19 as a wicked problem we analyse the extent that the UK government adhered to the guidelines for dealing with such problems and the extent to which the management of the pandemic exacerbated the crisis. We argue the management of the pandemic saw a continuance of political communication as usual, focusing on emphasising the optimistic rhetoric which underpinned the Brexit narrative and 2019 election campaign which delivered Boris Johnson a majority. The failure to break out of a narrow permanent campaigning mindset which saw the pandemic as a brief interlude during a period when the focus was on delivering Brexit led to public confusion as optimistic claims were proven to be inaccurate and promises unreachable. Johnson's government's attempts to offer certainty despite a situation characterised by volatility, uncertainty, complexity and ambiguity led to numerous U-turns that seriously damaged their credibility while the politicisation of the response led to poor decision making at key points. We therefore highlight the deficiencies of Johnson's strategy and highlight key lessons for communications professionals who navigate an increasingly volatile and uncertain world beset by wicked problems. In particularly we highlight the importance of depoliticising crises, seeking a diverse range of ideas and expertise, developing an empathic leadership style, starting a public conversation that recognises uncertainty and so develop a framework where wicked problems are a feature of public debate. We argue that failure in all of these areas contributed to the UK's poor comparative performance during the Covid-19 pandemic.

Indexed as

COVID‐19leadershippolitical communicationUK governmentwicked problems

Identifiers

PMID34512189
PMCPMC8420585

What OpenQuestion holds

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Registered trials

None linked

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.