Data journalism, impartiality and statistical claims: towards more independent scrutiny in news reporting

Cushion, Stephen ORCID: https://orcid.org/0000-0001-7164-8283, Lewis, Justin ORCID: https://orcid.org/0000-0002-5300-9127 and Callaghan, Robert ORCID: https://orcid.org/0000-0002-3590-5438 2017. Data journalism, impartiality and statistical claims: towards more independent scrutiny in news reporting. Journalism Practice 11 (10) , pp. 1198-1215. 10.1080/17512786.2016.1256789

Preview

PDF - Published Version Available under License Creative Commons Attribution. Download (384kB) | Preview

Abstract

The use of data is often viewed as a potentially powerful democratic force in journalism, promoting the flow of information sources and enriching debates in the public sphere. We explore a key feature of the relationship between data and journalism, drawing upon the largest ever study of statistical references in news reporting (N=4285) commissioned by the BBC Trust to examine how statistics inform coverage in a wide range of UK television, radio and online media (N=6916). Overall, our study provides a cautionary tale about the use of data to enlighten democratic debate. While we found that statistics were often referenced in news coverage, their role in storytelling was often vague, patchy and imprecise. Political and business elites were the main actors’ referencing statistics and interpreting them, but most of their claims were neither questioned nor interrogated further by journalists, with statistics often traded by opposing sides of an argument without independent analysis. In order to enhance the independent scrutiny of statistics, we argue a radical shift in newsgathering and journalistic interpretation is needed, which allows reporters to draw on a wider range of statistical sources and to adopt more critical judgements based on the weight of statistical evidence.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Journalism, Media and Culture
Uncontrolled Keywords:	data journalism; impartiality; public service broadcasting; content analysis; statistics; sources
Additional Information:	This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher:	Taylor & Francis (Routledge)
ISSN:	1751-2786
Funders:	BBC Trust
Date of First Compliant Deposit:	2 November 2016
Date of Acceptance:	2 November 2016
Last Modified:	06 Jan 2024 02:40
URI:	https://orca.cardiff.ac.uk/id/eprint/95806

Citation Data

Cited 57 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item