Data Journalism, Impartiality And Statistical Claims: Towards more independent scrutiny in news reporting. (26th November 2017)

• Record Type: Journal Article
• Authors: Cushion, Stephen; Lewis, Justin; Callaghan, Robert
• Is Part Of: Journalism practice. Volume 11:Number 10(2017)
• Page Start: 1198
• Page End: 1215
• Publication Date: 2017-11-26
• Subjects: content analysis -- data journalism -- impartiality -- public service broadcasting -- sources -- statistics; Journalism -- Periodicals; 070.405
• DOI: 10.1080/17512786.2016.1256789
• Languages: English
• ISSNs: 1751-2786

Abstract

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 many 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.