Abstract Summary
In our presentation, we publish the results of a systematic literature review that focuses on papers in journalism studies that adopt both etic and emic perspectives in their data gathering. We assess, for example, the balance of these perspectives and their degree of integration.
Abstract :
The methodologically oriented symposium "From the What to the Why" discusses emic and etic perspectives in research data gathering. As explained in the description of the symposium, both perspectives have their advantages and their limitations. To compensate for their inherent shortcomings, the crosscutting thread of this symposium is the art of combining etic and emic perspectives in one way or another.
In our presentation, we first introduce the origin, and varying definitions, of the concepts of etic and emic and discuss their advantages and disadvantages in data gathering. The bulk of the presentation is then dedicated to premiering the results of a systematic literature review that focused on methodologies that combine etic and emic in journalism studies. Based on a preliminary database search and manual analysis of over 3 000 peer reviewed articles, we identified some 250 papers published between 2000 and 2017 that focus on journalistic work processes and adopt both etic and emic perspectives in their data gathering.
The empirical part of our presentation begins with a quantitative description of what regional mediascape these papers investigated, what type of media they studied, what kinds of data gathering methods they combined, and what part(s) of the journalistic work process they focused on. We assess the balance of etic and emic perspectives in these studies and their degree of integration. We illustrate our results with examples from methodologically robust studies, i.e., studies in which etic and emic perspectives support each other from the beginning.
We admit that diverse data gathering might require a lot of preparation, that the fieldwork is labour intensive, and the analysis phase may be challenging. However, we conclude that this effort often pays off in the form of rich data with exceptional explanatory power.
