Effects of Editorial Policies on Demand for Comprehensive Research on News Coverage in Print and Social Media Channels in Kenya

Abstract

Media houses play pertinent roles in the social transformation of their consumers and ultimately their countries. By casting light on issues affecting society, they spur and steer national dialogue on these issues from the grassroots of households in the community to the offices of leaders in power. For this to take place though, journalists should ideally work in an atmosphere devoid of unnecessary limitations. Regrettably, journalists have to contend with an ever-decreasing operating sphere, due to limitations posed by editorial policies among other restrictions. The purpose of this study was to examine the effects of editorial policies on demand for comprehensive research on the coverage of news in the print and social media channels in Kenya. The study adopted the Gatekeeping Theory. The mixed method study was used. The target population was 60 journalists, 30 editors and 20 sub-editors all from the NMG. The sample size was 110 individuals drawn from the above. The study participants were purposively sampled. Questionnaires and interviews were used in data collection. The findings show that journalists are forced to work within a constrained framework by editorial norms in media organizations, particularly when it comes to obtaining, developing, and disseminating news information. This might result in some news stories being excluded, which would reduce the tendency of media outlets to support social change. Thus, the interaction between editorial policies and the spread of social media necessitates that we reconsider what gatekeeping is and how to modify the editorial policies. According to Pearson correlation, there was a statistically significant association between compressive research policy and media house news coverage (r=0.527, p<0.05). Demand for thorough research policies was thus refused, leading to the conclusion that they had no appreciable impact on Kenya's print and social media news coverage. Compressive research policies might statistically and significantly predict media house news coverage, according to an analysis of variance (ANOVA) (F=18.036, p<0.05). Compressive research policy (t=19.955, p<0.05) could statistically significantly predict media house news coverage, according to t-test results. The study makes the suggestion that editorial practices be revisited in order to improve their capacity to report on news that may have an impact on social transformation.