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The notion of temporal bracketing is in fact derived from Anthony Giddens's structuration theory. At the heart of the theory is the idea that the actions of individuals are constrained by social structures but that actions simultaneously reconstitute those structures over time. Because mutual influences are difficult to capture simultaneously, and because changes in structures follow diachronically from action, it makes sense to analyze these interacting dimensions in a sequential fashion by temporarily “bracketing” one of them. Thus, the temporal decomposition of data into time periods enables analysis of how the actions of one period lead to changes in the context that will affect action in subsequent periods.

For example, in a classic study of the mutual relationships between technology and structure, Stephen Barley examined how the scripts underlying interactions between radiologists and radiology technicians during radiology examinations shifted over time with the introduction of new technology. He decomposed his data into phases separated by changes in structural features (in this case, the technology and the people involved) and was able to show that the microlevel interactions taking place during one period contributed to precipitating changes in structure and that, in the next phase, the new structures in turn influenced the new modes of interaction that developed between the radiologists and technicians. These recursive patterns were observed to occur in two different hospital sites, although the number of distinct phases and the precise scripts used in interactions during each phase differed between the sites.

Temporal bracketing is an analytical strategy for dealing with diachronic process data, that is, case study data that are composed of detailed event histories over time. Specifically, the approach involves decomposing time lines into distinct phases where there is continuity in activities within each phase and discontinuity at the frontiers.

Conceptual Overview and Application

The identification of phases might at first sight appear to be a step toward the development of deterministic, life cycle-based process theories composed of a predictable set of stages. Indeed, this may sometimes be the result of using this analytical strategy when phase sequences appear to be similar in content and predictable across multiple cases (e.g., as in Lynn Isabella's study of the phases of interpretation of organizational change). However, this is not the primary purpose or outcome of temporal bracketing. The phases identified using this approach do not necessarily have any particular conceptual significance; instead, the decomposition into time periods is a heuristic device for segmenting the data into comparable units of analysis, enabling the exploration and replication of theoretical ideas. This strategy is particularly useful when it appears that mutual shaping, structuration, feedback loops, and multidirectional causality may be contributing to observed temporal patterns.

Stephen Barley and Pamela Tolbert subsequently generalized this approach to propose a systematic analytic strategy for understanding the recursive links between actions and institutions based on a form of temporal bracketing.

Temporal bracketing was also used by Jean-Louis Denis, Lise Lamothe, and Ann Langley in their studies of strategic change in healthcare organizations. Drawing on five longitudinal case studies, the authors showed how change initiatives during one period had substantive symbolic and political effects that led to modifications in the leadership teams, further altering the shape of change in the future. Similarly, Yves Doz used temporal bracketing to trace through the cycles of learning and re-evaluation in alliance development.

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