Social Theory is often interested in describing and explaining social change. For such explanations, an understanding of how micro‐, meso‐ and macro phenomena interact and causally influence each other over time is essential. We refer to the empirical analysis of dynamic linkages on multiple levels as process‐oriented analysis. The works of Norbert Elias (e.g. with Scotson 2008 ) or Pierre Bourdieu (e.g. 1984) provide ample illustrations of this approach , moreover current field theory (e.g. Fligstein & McAdam, 2012; Hilgers & Mangez, 2015) or relational theory (e.g. Powell & Dépelteau, 2013; Crossley, 2015; Abbott, 2016), to name but a few examples, offer productive grounds for process‐oriented analysis.

This process orientation raises fundamental methodological issues (Baur, 2017):

Take, for example, case selection. A process‐oriented analysis struggles with the instability of social units and social problems over time. Shifting the focus to explaining change, a major task is to define before and after states of that social unit or social problem. Other methodological issues include defining a starting point for the analysis and the piecing of the longue durée into comparable and distinct phases. Further, a process‐oriented analysis needs to define relevant interactions, institutions, and structures at play and define the methods adequate to reconstruct these micro‐meso‐macro levels. Finally, a key methodological issue relates to identifying the causal relations between the different levels within and across periods. Only on such grounds can patterns of social change become evident.

Research designs typically combine or mix different data types in order to capture multiple levels and various time layers (Baur, 2011). Micro phenomena often address the individual life course or biographies, which are usually analyzed either with quantitative survey data or qualitative narrative interviews. Alternatively, very short‐term social processes are often grasped by methods such as ethnography and video analysis. Meso and macro phenomena, on the other hand, typically change only on the longue durée, thus requiring either longitudinal analysis, historical methods or archival methods, which make use of qualitative documentary analysis or quantitative public administrative data, structural or trend data. Such research designs realizing process‐oriented analysis in social research touch upon still unresolved methodological concerns.

These problems are owed to three blind spots in current methodological debates: First, a mixed‐methods debate that thus far mainly focuses on the integration of qualitative and quantitative methods, but only scarcely reflects upon the integration of historic or archival methods (e.g. Cresswell & Clark, 2011; Sligo, Nairn, & McGee, 2018). Second, digital and big data movements celebrate the progress made by an increasing availability of process‐generated data (both historical and contemporary public administrative data, trend data, but also pictures, private texts and audios). Lacking is, however, a critical reflection upon the socio‐historic circumstances that produce these data and thus the problems of selectivity and availability these kinds of data hold (e.g. Tinati & Halford, 2014; Halford et al 2017). Third, the debates about causality within qualitative and quantitative methods are often discussed separately. Hence, there is a need for an integrated reflection upon the meaning of causality in order to address time, multi‐level and multi‐method issues adequately (e.g. Harding, 2013; Johnson, Russo, & Schoonenboom, 2017).

This special issue aims at initiating a debate about the methodological underpinnings of process‐oriented analysis. Based on above considerations, we ask: How can we conduct process oriented micro‐meso‐macro analysis? By doing so, we aim at provoking reflections in three ways ‐ methodological issues connected to process‐oriented analyses, the empirical realization of process‐oriented analyses, and finally blind spots in current methodological debates. While this thematic issue does not aim at narrowing the debate to any particular theoretical couleur, we appreciate contributions and arguments that are sufficiently theoretically anchored.

We are particularly interested in contributions by scholars who have engaged themselves in empirical process‐oriented analyses. We welcome submissions that identify a particular methodological issue of process‐oriented analyses and discuss adequate solutions to address this issue. Ideally, contributions will contain three elements a.) a reflection of the selected methodological issue and how it relates to the overall research process b.) a description of the empirical design as it contributes to solving the methodological issue and c.) a discussion of how the solution may offer insights to thus far overlooked concerns in current methodological debates. Contributions that consider only one of these elements are also strongly encouraged to submit to this special issue.

Papers should be sent through the Canadian Review of Sociology website https://www.csa‐ scs.ca/canadian‐review/. Deadline: June 30, 2019.

For more information, please contact Isabell Stamm (isabell.stamm@tu‐berlin.de)

References
Abbott, A. (2016). Processual Sociology. Chicago: University of Chicago Press.
Baur, N. (2011). Mixing Process‐Generated Data in Market Sociology. Quality & Quantity, 45(6), 1233–1251.
Baur, N. (2017). Process‐Oriented Micro‐Macro‐Analysis. Methodological Reflections on Elias and Bourdieu. Historical Social Research, 42(4), 43–74.
Bourdieu, P. (1984). Distinction: A Social Critique of the Judgment of Taste. Cambridge: Harvard University Press. Cresswell, J. W., & Clark, V. L. P. (Eds.). (2011). Designing and Conducting Mixed Methods Research. Thousand Oaks: SAGE. Crossley, N. (2015). Relational Sociology and Culture. International Review of Sociology, 25(1), 65–85.
Elias, N., & Scotson, J. (2008). The Established and the Outsiders. Dublin: UCD Press. Fligstein, N., & McAdam, D. (2012). A Theory of Fields. New York: Oxford University Press.
Halford, S.; Weal, M.; Tinati, R.; Carr, L.; Pope, C. (2017): Understanding the production and circulation of social media data: Towards methodological principles and praxis. New Media & Society, online first http://journals.sagepub.com/doi/full/10.1177/1461444817748953
Harding, D. J. (2013). Mixed Methods and Causal Analysis. In S. L. Morgan (Ed.), Handbook of Causal Analysis for Social Research (pp. 91–110). Dodrecht: Springer.
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Powell, C., & Dépelteau, F. (Eds.). (2013). Conceptualizing Relational Sociology: Ontological and Theoretical Issues. New York: Palgrave Macmillan.
Sligo, J. L., Nairn, K. M., & McGee, R. O. (2018). Rethinking Integration in Mixed Methods Research Using Data from Different Eras: Lessons from a Project About Teenage Vocational Behaviour. International Journal of Social Research Methodology, 21(1), 63–75. https://doi.org/10.1080/13645579.2017.1321868