Field-based Metaphor Analysis — Naturalistic Metaphor Elicitation and Interpretation
Field-based Metaphor Analysis · Also known as: field metaphor elicitation, naturalistic metaphor analysis, contextual metaphor analysis, FbMA
Field-based metaphor analysis is a qualitative method that collects and interprets spontaneous or elicited metaphors from participants in their natural settings. Grounded in Lakoff and Johnson's conceptual metaphor theory, it reveals how individuals and communities structure abstract concepts — such as teaching, leadership, or illness — through figurative language encountered or produced in real contexts. Unlike purely document-based metaphor studies, field-based variants combine data collection in natural field settings with systematic analytic coding.
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When to use it
Use field-based metaphor analysis when you want to understand the tacit beliefs, assumptions, or conceptual frameworks that individuals or groups hold about an abstract concept — and when those beliefs are likely to be shaped by a specific institutional or social context. It is well suited to educational research (teachers' conceptions of learning), organisational studies (employees' mental models of leadership), and health and social sciences (patients' representations of illness). The method requires participants who can produce written or spoken responses; it is not appropriate for populations with very limited literacy or expressive capacity without adaptive data collection support. Avoid it when the research question calls for a causal explanation or statistical generalisation — it is exploratory and interpretive by design.
Strengths & limitations
- Surfaces tacit, often unarticulated conceptual frameworks that standard interviews or surveys miss.
- The field setting ensures metaphors are ecologically valid — grounded in participants' actual lived context rather than abstract laboratory prompts.
- Flexible across disciplines: widely applied in education, organisational behaviour, health sciences, and social policy.
- Combining frequency counts with interpretive analysis provides both breadth (how common each conceptual category is) and depth (what it means).
- Relatively accessible — open-ended sentence completion prompts require minimal instrumentation.
- Metaphor identification requires interpretive judgment; different analysts may disagree on whether an expression is metaphoric and what category it belongs to — inter-rater reliability checks are essential.
- Findings describe conceptual structures in a specific context and are not statistically generalisable.
- Participants' written metaphors may not fully capture the richness of their thinking; follow-up interviews are often needed to avoid surface-level readings.
- Large datasets with hundreds of metaphor responses can be labour-intensive to code systematically.
- The method assumes participants can and will engage with open-ended elicitation; low engagement produces thin data.
Frequently asked
What makes this 'field-based' rather than just ordinary metaphor analysis?
Standard metaphor analysis is often conducted on pre-existing textual corpora (novels, news articles, political speeches) or controlled laboratory prompts. Field-based metaphor analysis situates data collection in participants' natural environments — classrooms, offices, clinics — so that the social and institutional context is part of the design, not merely acknowledged as a limitation. The field setting also allows supplementary observational data that can enrich interpretation.
How large does my sample need to be?
There is no fixed rule, but studies in the educational literature typically involve 30–200 participants when using open-ended questionnaires, since the method relies partly on frequency distributions across conceptual categories. Smaller samples (15–30) are feasible when combined with in-depth interviews. The goal is sufficient diversity of metaphor types to identify dominant conceptual patterns.
Do I need a linguistic background to conduct this analysis?
A basic understanding of conceptual metaphor theory (Lakoff and Johnson 1980) is necessary, but formal linguistics training is not required. Researchers in education, management, and health sciences have successfully applied the method using structured coding protocols. Consulting a systematic coding guide and having a second analyst verify categories is more important than disciplinary background in linguistics.
Can I combine field-based metaphor analysis with other methods?
Yes — and this is often recommended. Metaphor elicitation questionnaires can be followed by semi-structured interviews to probe the reasoning behind chosen metaphors. Results can also be triangulated with observational field notes or with findings from thematic analysis of interview data. Mixed-methods designs that combine metaphor frequency data with in-depth narrative accounts are increasingly common.
How do I report inter-rater reliability?
The most common approach is to have a second trained coder independently categorise a subset of metaphors (typically 20–30%), then compute Cohen's kappa or percentage agreement. A kappa above 0.70 is generally considered acceptable. Disagreements are resolved through discussion, and the final category scheme should be documented in sufficient detail for replication.
Sources
- Lakoff, G., & Johnson, M. (1980). Metaphors We Live By. University of Chicago Press. ISBN: 978-0226468013
- Saban, A. (2009). Prospective teachers' mental images about the concept of student. Teaching and Teacher Education, 25(2), 750–764. link ↗
How to cite this page
ScholarGate. (2026, June 3). Field-based Metaphor Analysis. ScholarGate. https://scholargate.app/en/qualitative/field-based-metaphor-analysis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Content AnalysisQualitative↔ compare
- EthnographyQualitative↔ compare
- Metaphor AnalysisQualitative↔ compare
- PhenomenologyQualitative↔ compare
- Thematic AnalysisQualitative Research↔ compare