In his 1903 book Mankind in the Making, the British science-fiction novelist and social commentator Herbert George Wells (1866–1946) argued for a new type of political system in which society renounced any claim of absolute truths and people's ideas were based on presented facts – a system in which overall policy and public affairs in society were scientifically examined in the light of mathematical and statistical reasoning. Wells would go on to argue that

Wells, who was a biologist by training and one of the top science-fiction writers of the time, lived in the age of modern scientific utopias, marked by the rise of industrialization and workers’ struggles. However, what makes Wells’ contribution so relevant today is that he was standing up against Eugenics at a time when other intellectuals, including some fellow socialists, were siding with this racist pseudoscientific idea.

Wells was not opposed to a science of heredity, nevertheless he rejected the notion of Francis Galton (1822–1911), the father of modern statistics, that the state should intervene in order to breed human beings selectively. Positive traits such as beauty, health, capacity, and genius, as well as supposed negative traits such as criminality and alcoholism, says Wells, are in fact such complex entanglements of characteristics that ignorance and doubt bar our way. Still today at the Rijksmusem Boerhaave of science and medicine in Leiden, the Netherlands, the visitors can see some drawings of a facial angle, a geometrical system invented by the Dutch scientist Petrus Camper (1722–1789) and later used to justify slavery and racism.

While wrapping up this book, we witness the global crisis set in motion by the spread of the COVID-19 virus. According to the latest figures released in May 2020 by the European Centre for Disease Prevention and Control, there were almost 300,000 deaths worldwide at that time, and the consequences on the worldwide economy seemed probably huge and long lasting, although by then still unknown in detail. What was certain then and now was that many lives were shattered and whole communities disseminated by this crisis. Indeed, by the time it was officially declared a pandemic by the World Health Organization (WHO), it was already a full-scale destructive force that resembled – at least in the eyes of those in places such as Guayaquil, Ecuador, and in Bergamo, Italy – one of the Horsemen of the Apocalypse.

In response to these events, governments and political leaders engaged at different speeds in the implementation of emergency strategies that involved all sectors of their societies. The state of emergency forced them to undertake action, although only for some of these leaders the action and sense of urgency were in fact ‘immediate’. This is because while some prioritized the health and lives of people, others instead believed that saving the economy was far more important. As these debates took place among elites, doctors, nurses, first responders and, overall, ordinary people such as postal workers, cleaners and rubbish collectors kept society afloat. The sheer number of ordinary people who suddenly became heroes but who until those days were often invisible to the public eye reminded us that society is not made by the few but by the many.

As the number of deaths climbed, fingers started to be pointed at culpables even before any peak was reached, perhaps looking to displace responsibilities. Some leaders spoke every day while others remained silent. During that leadership vacuum, fake news and the misrepresentation of numbers spread globally as fast as the pandemic did. The battle for the hearts and minds of the public soon became an information war or ‘Infodemic’, as described by the director-general of the WHO, Tedros Adhanom Ghebreyesus.

Our central question, so far, has asked about the nature of the engagement between journalists and statistical data in the pursuit of quality. In so doing, we would want also to know if the quality statistics automatically lead to quality journalism. If so, we ought to know if the information quality then translates into quality journalism. Does the nature of a statistic's source affect the news reporting? What is the purpose of statistics in news reporting? Do journalists emphasize a certain type of statistics? What statistics sources do journalists use most often? And, how does the audience engage with statistically driven stories?

To answer these and other questions, we used a mixed-method approach, in which we have triangulated qualitative and quantitative methods as this ‘is major research approach’ (Johnson, Onwuegbuzie & Turner, 2007). The importance of such a triangulation is the validity of the results that can lead to a more balanced and detailed answer to the research questions by also comparing and contrasting different accounts of the same situation (Turner & Turner, 2009). The aim was to develop a ‘practical theory’ that would help to rationalize the issue under scrutiny (Altrichter, 2010; Altrichter, Posch & Somekh, 1993). We included content analysis, semi-structured interview, close reading and focus groups, which allowed us to carry out a multilevel assessment of the data. The overall mixed method used in this research should be understood in a broader ‘cross-sectional design’ (F. L. Cook et al., 1983; Johnston & Brady, 2002), which allows a combination of quantitative and qualitative research.

Therefore, this chapter presents the analysis of the data collected followed by a discussion of the research findings that resulted from each method. It provides a detailed account of the findings, in the hope that these results will elucidate the uses of statistics in articulating the five quality dimensions in news reporting.

Overall, our findings suggest that journalists tend to use statistical information as a tool to fulfil their deontological expectations of producing quality journalism. However, as it became clear from the interviews, one of the underlying motivations seems to also be the need to achieve credibility and authority, which entails a certain degree of building up the ability to persuade by means of trust.

Over the past years, governments and corporations have come to develop media strategies to ‘manage’ the dissemination of statistics within the public. As we have discussed in this book, this was part of a long history in using numbers to assert social control and that in the twentieth century took the form of cybernetics. In more recent times, this has meant enshrining statistics and data into daily life by means of the information and communication technologies to be used by individuals, couples, families and communities. In so doing, they have dedicated immense resources towards ‘controlling’ narratives and interpretations of statistics released in the public sphere.

Moreover, mediatization practices to shape the way these numbers go out into the public are now at the centre of the controversies and issues that journalism confronts. This ‘mediatization of statistics communication’ (Lugo-Ocando & Lawson, 2017) is one which is understood to be not a policy-making process directed by the media but overall a policy-process in which publicityseeking activities and political decision-making become closely interlinked (Cater, 1965; T. Cook, 2005).

Statistics are far from being a neutral object in society and have their own politics and ideologies. They are also fundamental signifiers in the creation of social reality (Dorling & Simpson, 1999), displaying a politics of their own. Not that we ascribe agency to the output of a mathematical equation but that we see the equation itself as a human creation that has a history, a meaning and an intent. Over the years, as we have seen in this book, these numbers have gained a power of their own. From defining budgetary priorities to determining who can receive aid or buy a house, statistics and data, in more general terms, dominate human existence in many ways.

However, with the increasing presence of Big Data and controlling power of algorithms, we are entering into new uncharted territory, No longer is it just about the state or corporations controlling the production and analysis of statistics, but also about the active management of these numbers by means of mediated representation in the public domain. Recognized today as a process

The assumptions that quality can be only asserted through numbers hold both within journalism and government. Particularly, as these numbers bring a sense of impartial and objective assessment to both formulate and evaluate policies. Moreover, at the centre of this assumption is the deep-rooted belief that statistics can bring about the type of scientific-based knowledge, transparency and trust needed to implement and analyse government policy. Nowhere was this more evident than during the Tony Blair-led New Labour government in the United Kingdom (1997–2001), when evidence-based policy became central to the way politicians sold their own agendas to the public (Hope, 2004, 2005). To be sure, the Command Paper released under the title Statistics: A Matter of Trust (1998) made it clear that

In this sense, the UK Statistics Authority has adopted a structure broadly similar to that of the European Code, which sets out a number of high-level principles, each of which is further amplified by a series of more detailed practices (or ‘indicators’ in the European Code). Also, the UK Code of Practice for Official Statistics and the assessment programme that follows have been informed by, and are consistent with, both the UN Fundamental Principles of Official Statistics3 and the European Statistics Code of Practice.

According to Mark Pont, member of the board of directors of the UK Statistics Authority, the European Code has proved an effective basis for the international process of ‘peer review’ and ‘the Statistics Authority believes that a similar approach will provide a sound foundation for the Statistics Authority's quality assessment function’ (Code of Practice: 8). One of the strong points of the Code is its emphasis on the role of the user, and the need for statistical producers to consider the wider use that is – or may be – made of statistics. In addition to meeting specific policy needs within government, there is increasing demand by people working in research, academia and journalism for statistics in many aspects of social and economic life.