When Walter Williams, the founder of University of Missouri's school of journalism wrote the famed Journalist's Creed (1908), he mentioned that: I believe that the journalism which succeeds best is constructive, he had the idea of constructive journalism in mind. A story on CNN's website on October 2018 read: Tropical Storm Rosa is about to make landfall and drench the arid Southwest. The story went ahead to highlight how the storm could soak the dry Southwest. A few hours later, a different story was published: Chinese warship in 'unsafe' encounter with US destroyer, amid rising US-China tensions. The story discussed several tensions existing between US and China, as well as the cancelation of Secretary of Defense James planned visit to Beijing. These stories show how conflict and negativity are synonymous in the news media. They show how media careen from one sad story to another, forging forward a breathless tour of disease, death, and war (Moeller, 1999).
Negative story frames can be attributed to Lasswell (1948) who suggested that a key function of the media is to scan the environment for threats. Some of these negative stories that dominate media waves are on violence, crime, police brutality, and other negative tropes (Wenzel, Moreno, Son & Hawkins, 2018). With all this negativity, newspapers and television channels have been struggling with a waning readership and advertising revenues. Schudson (2012) argues that individuals' interest in serious news has declined over the years. This decline could be attributed to compassion fatigue brought about by too much focus on negative stories. Compassion entails the ability to recognize someone's suffering and engage in an activity aimed at alleviating the suffering (Moore et al., 2015). On the other hand, compassion fatigue refers to the burnout brought by excessive negativity leading to a reduced desire to help (Moeller, 1999). It occurs when the public become weary of unrelenting media coverage of human tragedy (Kinnick, Krugman, & Cameron, 1996, p. 687). Kinnick and his colleagues argue that journalism contributes to compassion fatigue by constantly projecting bad news and not doing enough to provide solutions to social problems they project.
As Shoemaker (1996) argues, human beings gravitate toward environmental threats, and therefore this emphasis on negative stories makes sense. Given the other functions of the media such as the watchdog role (Bennett & Serrin, 2005; Eriksson & ?–stman, 2013) and informing the public (Schudson, 2008), it will be hard for the media not to report negative stories. However, this conflict-driven journalism does not work always. As (2012) argues, negative journalism fails to address government policies that are working. On the other hand, audiences choose to read negative stories despite preferring more positive ones (Trussler & Soroka, 2013). Scholars have delved into this area and research shows that negative emotions and events have a more lasting effect on people than positive ones (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001).
To counter this negativity in news and reverse the trend of compassion fatigue, news media have been embracing the concept of constructive journalism as an alternative to negative stories that are ubiquitous in today's media. This concept is relatively ambiguous and has been defined differently by scholars with others confusing it with peace journalism (Galtung, 1986; Galtung & Fischer, 2013; Lynch, McGoldrick, & Heathers, 2015) or even solutions journalism (Mcintyre, 2017). However, I argue that constructive journalism goes beyond the two areas and therefore, need to explicate it to clear the ambiguity in its definition. There is also limited research on this area and there are no concrete theories to explain how it works. Even with these extant studies, constructive journalism lacks clear measurement guidelines, and most of the studies related to the concept do not account for the multiple factors that can influence constructive journalism. Therefore, this paper is a concept explication of constructive journalism as it seeks to clear any ambiguity surrounding the concept to aid in theory construction.
Concept explication is a cognitive process of taking an abstract idea and creating a nexus between the idea and the evidence we observe in real world through empirical research. Through concept explication, a scholar can connect primitive knowledge to the practical examples and these examples to the abstract, using evidence observed from the environment. Concept explication helps clear confusion among scholars regarding concepts and their definitions by dispelling ambiguity among definitions put forth. It enables researchers to determine how they may observe a central concept exhaustively and exclusively. The process of concept explication aids in fortifying the connection between theory, observation, and research. This makes a theory testable. In doing this, it helps researchers identify gaps in the existing research and explore new dimensions about a concept.
To conceptualize constructive journalism, this paper will utilize McLeod and Pan's (2004) concept explication procedure. They suggest six steps for concept explication: identifying the concept, searching the literature, examining empirical properties, developing a tentative conceptual definition, defining the concept operationally, and gathering data. Here, except for the last step of gathering data, this paper follows these steps and aims at narrowing down the definition of constructive journalism. These steps stem from Chaffee's (1991) book on explication and are centered on the first procedure: meaning analysis. Meaning analysis is the fulcrum between the literature review and empirical definition (Chaffee, 1991). It involves the use of logical procedures to define concepts with clearly connected conceptual and operational definitions. This comes in handy during empirical analysis, the second procedure in explication. It is the reverse process whereby one evaluates a concept based on empirical evidence after gathering data. Thus, the sixth step (gathering data) will not be part of this explication.
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