15d • General discussion
Concurrent Mixed Methods: Self-Signified Narrative Data Collection
Understanding organizational context requires an approach that captures both the richness of stories and the structure of quantitative data. The self-signified narrative method — where storytellers code their own stories through closed questions — offers a unique concurrent mixed method design that honors both depth and analytical rigor.
Stories as Self-Coded Data
Unlike traditional mixed methods where quantitative and qualitative data are collected through separate instruments, this approach integrates both within a single collection moment. After sharing their narrative, storytellers themselves answer closed questions about their own story. As Cynthia Kurtz explains in Working with Stories (2014), this self-signification process respects the storyteller’s interpretation while creating structured, analyzable data.
The Method in Practice
The concurrent collection works as follows:
1. Narrative elicitation — The storyteller shares their experience in their own words
2. Self-signification — The storyteller then answers closed questions about their story, which may include:
∙ Scale questions (e.g., “How much control did you feel in this situation?” rated 1-10)
∙ List selections (e.g., “Which factors influenced this outcome?” with predefined options)
∙ Triangle or matrix questions (e.g., positioning the story along multiple dimensions simultaneously)
This approach ensures that the context of both the story and the storyteller is systematically explored. The storyteller — not the researcher — codes the narrative, preserving authenticity while generating quantitative data.
Why Self-Signification Matters
Kurtz emphasizes that “people are experts on their own experience” (Kurtz, 2014, p. 89). When storytellers code their own stories, several advantages emerge:
∙ Authenticity preserved — The meaning-making remains with the person who lived the experience
∙ Context captured — Closed questions can explore dimensions that might not emerge spontaneously in the narrative
∙ Pattern detection enabled — Multiple stories with consistent coding schemes reveal organizational patterns
∙ Immediate integration — Qualitative and quantitative data are inherently linked through the same collection moment
StoryConnect’s Storycycle Framework
StoryConnect.nl applies this self-signified approach throughout their storycycle:
1. Collect — Gather stories with self-signified contextual data through scales, lists, and triangles
2. Analyze — Examine patterns in both narratives and coded responses, exploring where stories cluster or diverge
3. Act — Use integrated insights to design contextually appropriate interventions
4. Evaluate — Track changes in both story content and self-signified dimensions over time
This cyclical process ensures that the voices of those experiencing the situation remain central while enabling systematic analysis (StoryConnect.nl, n.d.).
The Concurrent Architecture
This is truly concurrent mixed method design because:
∙ Both data types are collected simultaneously in one interaction
∙ The same respondent provides both narrative and structured data
∙ Quantitative coding is directly linked to specific stories, enabling micro-level analysis
∙ The storyteller’s interpretation remains authoritative throughout
As Kurtz notes, this approach recognizes that “stories carry meaning that numbers alone cannot capture, but numbers can help us see patterns across many stories” (Kurtz, 2014, p. 134). The self-signification process bridges this gap elegantly.
From Individual Stories to Collective Context
When multiple storytellers code their experiences along the same dimensions, collective patterns emerge. A scale question about autonomy across fifty stories reveals more than an average score — it shows the distribution of experiences, outliers, and relationships between autonomy and other story dimensions. Lists and triangles add layers of contextual understanding that surveys alone cannot achieve.
The beauty of this method lies in its respect for both the particular and the pattern, the individual voice and the collective insight. Context is not imposed by researchers but revealed through the systematic aggregation of self-interpreted experiences.
References
Kurtz, C. F. (2014). Working with stories in your community or organization: Participatory narrative inquiry (3rd ed.).
StoryConnect.nl. (n.d.). De storycycle: Van verhaal naar impact. Retrieved from https://storyconnect.nl
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Concurrent Mixed Methods: Self-Signified Narrative Data Collection
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