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Ethnographic principles


Explanations > Social ResearchAnalysis > Ethnographic principles

Grounding | Evolution | Complexity | Detail | Generativity | Immersion | Experience | Induction and deduction | See also


Quantitative analysis uses tables of data and statistical analysis to create numerical results. Qualitative ethnographic analysis, resulting from participation / observation, is not that easy and certainly not as quick.

Data from qualitative research can be very varied and may include field observation logs, interview notes, personal diaries, letters, brainstorm lists, survey results, collected artifacts and so on. 

As qualitative analysis does not have the simplicity of quantitative data, it needs careful approaches if it is to be accepted as serious research.


To avoid speculation drifting off into the ether, most work needs to be grounded in some way, connecting it to reality and established theory. When conclusions are drawn, then the more evidence and theoretical connections made, the more credible the assertion.

Evolution and emergence

Interpretation and consequent understanding tends to evolve as the researcher explores, connects and re-reads data. Initial ideas are tentative and final theories emerge only after repeated and exhaustive exploration.


Quantitative theories tend to be very simple, reducing things to a couple of variables. Qualitative theories tend to be conceptually dense, with many linkages and acceptance of the complexity of the real world.


The approach requires a strong attention to detail, putting even seemingly unimportant things under the microscope. The construction of a spoken sentence or the use of a particular word can turn out to be of critical importance.


Raising generative questions, those that create new thinking and ideas, is important to be able to make distinctions and comparisons between items.


To handle the complexity and discover the detail, the researcher becomes immersed in the data, often for an extended period. There may be periods of reflection, reading and re-reading notes, bringing things together to discover connections and so on.


The experience of the researcher can be very important, both in the developed ability to spot patterns in the haystack of data and in the personal involvements and interpretations that allows them to give new meaning.

Induction and deduction

Induction is the development of a hypothesis by 'chunking up' from review of data. Deduction is the 'chunking down' generalization from this hypothesis to create implications for other areas.

After induction and deduction, it is important to seek verification of the conclusions made.

Qualitative research evolves results through constant induction, deduction and verification.


Theories do not stand alone and a key part of qualitative analysis is in linking things together to form a web of interrelated meaning. This may be done both internally, within the area of study, and externally, linking discoveries with external theories and concepts.

A useful method of integration is to construct a narrative storyline, showing how elements relate and link in a format that can be understood.

See also

Ethnographic coding, Ethnographic data collection, Storytelling

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