What is narrative analysis?

“Narrative analysis has both a long history and is an umbrella term for multiple, often quite distinct but sometimes overlapping (and sometimes confusing) approaches. Narrative approaches are diverse, and discourses depicting their complexity are correct.”

Emily Bishop, 2012: 371

Narratives make us human. Narrative researchers claim that narratives are our means of sense-making. Clandinin and Rosiek (2007: 55) describe narrative inquiry as beginning “with a pragmatic ontology that treats lived experience as both the beginning and ending points of inquiry”.

There are two main approaches to narrative analysis, event centered or experience centered narrative analysis. Event centred narrative analysis is also called a Labovian approach, after its creator William Labov. It is a very structured way of identifying and/or coding narratives using the below six-part model. Drawing on Labov, researchers tend to conduct fine-grained socio-linguistic analyses of participants' speech.

Labov’s 6-part model:

  1. Abstract

  2. Orientation

  3. Complicating action

  4. Result

  5. Evaluation

  6. Coda

A major down side of this approach is that it excludes many narratives that do not fit its strict formula for what makes a narrative. As Patterson notes (2008): “There is much to be gained from the Labovian approach but if one takes a strictly Labovian approach to some types of data then much will be lost” (Patterson, 2008 in Doing Narrative Research).

An experience-centered approach captures more of ‘the narrative’. Experience centred narrative research focuses on the personal narrative, which includes “all sequential and meaningful stories of personal experience that people produce” (Squire, 2008: 42). This sees the data analysed for the story it tells – thus permitting the researcher to not only explore particular personal experiences, but also the context of those experiences, the key players, and the way the participant sees themselves in relation to the experience. Experience centred narrative analysis provides a more holistic approach to data than other narrative approaches – moving away from the fragmentation and de-contextualisation of data and towards an analysis of the gestalt of the narrative. This allows for the analysis to be grounded in the biographical contingencies of individuals’ lives (Hollway and Jefferson, 2000), which is essential for many qualitative studies to achieve their aims.

Experience-centered narrative researchers understand that narratives are constructed (or reconstructed), that stories are performed differently in different contexts and this element of a narrative can also be analysed. Researchers may choose to analyse non-dialogue narratives, such as the meaningfulness located in interviewer-interviewee interaction. Some have broken down an experience-centred narrative to include both ‘the lived life’ and the ‘told story’ - whereby the lived life represents the factual, objective and transparent representation of a life, and the told life is more constructed (see Chamberlayne, Rustin and Wengraf, 2002).

Similarly, Ann Pheonix’s chapter in Doing Narrative Research introduces the idea of ‘big stories’ and ‘small stories’. She describes layers within data – specifically, macro and micro layers of data. The ‘big stories’ refer to the content of the auto-biographical story, and small stories are the unspoken elements of narrative, the way a narrative is performed, and how people build their narratives, allowing insight into the dilemmas and troubled subject positions speakers negotiate as they tell their stories. It allows a focus on the ways in which narrators construct their biographies. Small stories are also referred to as ‘canonical narratives’. The helpful thing about the big/small story approach is that it captures both the local and situated account within the interview and the broader context of that person’s story telling – the societal context that stories are produced within, which no doubt, influences the story told.

An experience centred approach to narrative analysis is far more difficult than a Labovian approach because it lacks the structure that a Labovian approach comes at the data with - it is by no means a ‘one-size-fits-all’ approach. In fact, the method of analysis may look strikingly different for each project – for example compare this method of analysis to this one.

At Rapid Context our research is primarily informed by peoples lived experiences. During the data gathering stage, our utmost concern is getting to the bottom of the problem, into the nitty-gritty - the heart of the issue that we are investigating. We have found that the best way to do this is to sit one on one with people and ask them to share their lived experience of the research subject with us. Often what follows is a series of stories, because, narrative tends to be the best way of representing and understanding human experience (Clandinin & Connelly, 2000:18).

Want to read more about narrative approaches to research? Sociologist Arthur Frank’s book ‘Letting Stories breathe: A socio-Narratology” is fantastic.

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