Evidence map›Paper›PMID 38985255›Full record

ArticleThe Journal of medical humanities2025

"This was never about a virus": Perceptions of Vaccination Hazards and Pandemic Risk in #Covid19NZ Tweets.

Maebh Long, Andreea Calude, Jessie Burnette

Abstract read
In one paragraph

Article in The Journal of medical humanities, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Maebh LongEnglish Programme, University of Waikato, Private Bag 3105, Hamilton, 3240, New Zealand. mlong@waikato.ac.nz.ORCID http://orcid.org/0000-0002-3787-8410
Andreea CaludeUniversity of Waikato, Hamilton, New Zealand.
Jessie BurnetteUniversity of Waikato, Hamilton, New Zealand.

Funding

Marsden Fund MFP-UOW2011University of Waikato 109277 ALPSS IDC Long
6 · The paper itself

Abstract

In this paper, we draw on qualitative methods from the medical humanities and quantitative approaches from corpus linguistics to assess the different mappings of pandemic risks by Twitter (X) users employing the #Covid19nz hashtag. We look specifically at their responses to government measures around vaccines between August and November 2021. Risk, we reveal, was a major discursive thread in tweets during this period, but within our tweets, it was the vaccine rather than the virus around which hazard perception and response were grouped. We find that the discursive stance of those opposed to the vaccine evoked entangled medical and political hazards, untrustworthy experts, obscure information, restrictions on sovereignty, threats to children, and uncertain future dangers, all of which positioned them within what Ulrich Beck termed the world risk society. We also found that these narratives of risk manifested in specific Twitter styles, which employed a consistently larger number of hashtags. The lack of conjunctions between the hashtags, we argue, encouraged a disordered reading of doubt and precaution, as the hashtags presented triggering phrases whose interconnections were hinted at rather than specified. By contrast, those who tweeted in support of government measures were rhetorically led by solutions rather than risks, with one exception: their perception of those who were vaccine opposed. We use scholarship on risk and precautionary logic to map out the contrasting positions in tweets addressing Aotearoa New Zealand's pandemic experience during the closing months of 2021.

Indexed as

COVID-19COVID-19 VaccinesPandemicsSocial MediaVaccinationHumansSARS-CoV-2COVID-19 VaccinesAotearoa New ZealandCOVID-19HashtagsTwitter (X)VaccinationWorld Risk Society

Identifiers

PMID38985255
PMCPMC11805863

What OpenQuestion holds

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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.