Application of the Multiple Streams Model in Analysing the New Population Policies Agenda-Setting in Iran Publisher



Jafari H¹ ; Pourreza A¹ ; Vedadhir AA² ; Jaafaripooyan E¹ Show Affiliations
Source: Quality and Quantity Published:2017

Abstract

Agenda-setting is the process by which problems and alternative solutions gain or lose public and elite attention. This study aimed to demonstrate new population policy agenda-setting in Iran using the multiple streams model developed by John Kingdon. The study was conducted using a qualitative approach in the years of 2014–2015 and consisted of 15 semi-structured interviews with Iranian key informants. The sampling was purposeful and continued using snowball method until the data saturation is reached. In addition, 25 policy documents were reviewed and analyzed. The data analysis was conducted using the framework analysis by MAXQDA software. The problem stream was highlighted with the release of 2006 census and reaching total fertility rate to below the replacement level in Iran. Political stream formed by supporting the high-ranking officials of the country, academics and researchers, the mass media, clergy and particularly leadership. Policy stream continued with policies such as the future plan of children [Barname-e-Atiyeh], funding removal for population control and also abolished the previous limiting rules, formulation of the new law on the maternity leave. Finally, with the overall population policies notification by the supreme leader of the revolution, the window of opportunity was opened and the issue of population growth was set as agenda. In conclusion, application of the multiple streams model and identification of its various aspects in the new approach of the population policy in Iran would assist policy-makers and officials in this area of policy to recognize the problem better and thereby make more evident and rich policies. Further studies to understand better the interactions between these streams and development of this model in the country population policy recommended. © 2016, Springer Science+Business Media Dordrecht.