Academic journal article German Policy Studies

Method Parallelization and Method Triangulation: Method Combinations in the Analysis of Humanitarian Interventions

Academic journal article German Policy Studies

Method Parallelization and Method Triangulation: Method Combinations in the Analysis of Humanitarian Interventions

Article excerpt

1 Introduction and Overview *

As both the variety and the specialization of methods increases steadily, combining methods is a common thread in actual research and self-reflexive scientific discourses. There are different catch-phrases for these discussions like "mixed methods" (Tashakkori and Teddlie 1998, Tashakkori and Teddlie 2003), "integrative social sciences" (Seipel and Rieker 2003), or "triangulation" (Flick 2011) - the latter gained arguably the most prominence throughout the last years. As the different catch-phrases or labels indicate, these debates both attract quite some attention and take place in various scholarly communities that each by and large focus on one aspect, be it a critical discussion on whether and how to combine qualitative (small-N) and quantitative (large-N) studies (see, for instance, "integrative social sciences") or be it an analysis of various mechanisms of aggregating data, which is the focus of, for example, the "triangulation" camp. As fruitful as these debates were for advancing the methodological reflections and in fostering a pluralistic thinking in social sciences, they come with a certain baggage: firstly, there is a tendency of being either caught up in some ideological debates (a strive for pluralism and methodological non-conformism) or focused overly on a specific subfield (data aggregation in triangulation) losing sight of the overall picture of combining methods. Secondly, terms like triangulation and phrases like mixing methods have become ubiquitous in articles, conference papers, and grant proposals oftentimes not adhering to the rigor of the original concepts and thus making them more and more devoid of any methodological substance. Thirdly, there are new advances in the methodological literature that have not received attention by scholars devoted to method combinations. A case in point is the role of temporality, most notably the discussions on causal process tracing or causal chains in case study designs (see, for instance, Blatter and Haverland forthcoming).

Hence, this article attempts to map a more comprehensive picture of combining methods, introduces a typology that focuses on the basic standards of each subtype, and exemplifies one specific subtype (causal chains) by investigating a theoretical framework, which explains humanitarian interventions as a multilevel process.

At the core of the typology is both a distinction between method triangulation and method parallelization and corresponding subtypes differentiated between the combination of data-generation and data-analysis techniques. While scholars often refer to triangulation when in fact undertaking parallelization, the two should be clearly distinguished: method triangulation is based on a vertical logic of combining methods to aggregate data or data-analyses for the score of one explanatory factor, method parallelization follows a horizontal logic of combining methods according to their conceptual linkages.

In the first part, the article introduces this typology and distinguishes between two subtypes of method triangulation (data generation and data analysis triangulation) and three subtypes of method parallelization: multivariate designs, research programs, and causal chains, whereas the latter links to current debates in methodological literature.

To illustrate the differences and applications, the article investigates international decision-making in the field of humanitarian interventions. To that end, humanitarian interventions are modeled as a causal process, which is analyzed by falling back on different methods at different steps of the process but sometimes triangulating methods to explore one condition at one step of the process.

2 Triangulating and Parallelizing Methods - Mapping Method Combinations

Combining methods in one research endeavor is nowadays quite common. However, mono-method designs dominated the scene before the 1990s (Tashakkori and Teddlie 1998), even though the methodological reflection of combining various methods had already advanced quite considerably at that point of time: as early as 1959, Campbell and Fiske called for combinations of various operationalizations of one explanatory factor to refine the measurement and to make the results more reliable and valid. …

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