A study note on the hermeneutic circle for qualitative data analysis in secondary research

A study note on the hermeneutic circle for qualitative data analysis in secondary research (information from perplexity.ai)

My question 1: "What is the hermeneutic circle all about with reference to qualitative data analysis of secondary research for dissertation projects of MBA and Housing Studies?"

The reply: "The hermeneutic circle in qualitative data analysis—particularly relevant to secondary research in MBA and Housing Studies dissertation projects—is about an iterative process of understanding and interpretation. It involves moving back and forth between the parts (individual pieces of data, such as sections of texts, excerpts from studies, interview transcripts) and the whole (the broader context, overall theoretical framework, or research question) to progressively deepen understanding. This circular movement helps to refine both the interpretation of specific data and the broader understanding simultaneously.

Specifically, with respect to secondary research qualitative data analysis (i.e., analyzing existing literature, documents, or datasets rather than collecting new primary data), the hermeneutic circle guides the researcher to:

• Engage in a cyclical dialogue between individual studies or data excerpts (parts) and the overall research aim or theoretical lens (whole).

• Continuously question and revise preconceptions, allowing for an evolving interpretation that integrates new insights from the material.

• Ensure interpretations remain grounded in the data by providing concrete evidence and avoiding unfounded speculation.

• Use the process to develop a rich, contextualized understanding that is sensitive to both the specific aspects of the data and their broader significance.

In the context of MBA and Housing Studies dissertations:

• For MBA, the hermeneutic circle can be used in reviewing business literature and secondary datasets by iteratively relating specific case studies or theories (parts) to overarching business strategy concepts or research questions (whole), refining understanding of organizational behavior, market dynamics, or management practices.

• In Housing Studies, the approach helps interpret textual data, such as policy documents or homeowners' narratives in secondary sources, by moving repeatedly between detailed descriptions (e.g., statements about housing affordability, policy impact) and the larger social, economic, or policy context surrounding housing issues, promoting a deeper understanding of housing solutions and their implications.

The hermeneutic circle also influences how the dissertation is structured:

1. Literature Review: Researchers engage in an ongoing interpretive dialogue with the literature, moving between individual studies and the whole research framework, developing a nuanced understanding supported by the data.

2. Research Methodology: The iterative interpretive process and the researcher’s reflexivity on their preconceptions and engagement with the hermeneutic circle are explained here, emphasizing the qualitative secondary analytical approach.

3. Findings and Analysis: Presentation of results reflects the iterative movement between parts and whole, showing how themes or insights emerge by continually relating data fragments to larger theoretical and contextual frames, often acknowledging the co-construction of meaning between the researcher and the data/text.

These steps ensure that the analysis is rigorous, reflective, and deeply contextualized, which strengthens the quality and trustworthiness of dissertations in both fields.

In summary, the hermeneutic circle is about iterative, reflexive interpretation guiding the researcher from fragmentary data to holistic understanding and back—especially crucial when analyzing qualitative secondary data in MBA and Housing Studies dissertation projects, thus enhancing depth, rigor, and contextual sensitivity in qualitative analysis."

My question 2: "Highlight 8 main ideas of the hermeneutic circle with reference to our discussion topic."

The reply: "Here are 8 main ideas of the hermeneutic circle with reference to its use in qualitative secondary data analysis for MBA and Housing Studies dissertations:

1. Iterative Movement Between Parts and Whole
   Understanding involves a continuous back-and-forth between smaller parts of the data (e.g., case studies, policy excerpts) and the whole context (e.g., overall research questions or theoretical frameworks). This iterative process deepens interpretation of both.

2. Pre-understanding and Interpretation Interaction
   Researchers begin with preconceptions or prior knowledge (their "horizon") that shapes initial interpretation of data parts. Engagement with new data challenges and revises this understanding, producing a progressively refined view.

3. Reflexivity and Questioning
   The process requires active reflection on and questioning of one’s assumptions to avoid bias. Researchers revise their understanding by continuously interrogating the meaning of data and their own perspectives.

4. Contextual Sensitivity
   Each data fragment is interpreted within the broader social, theoretical, or policy context, ensuring findings are grounded and meaningful to the specific disciplinary backdrop, such as business strategy or housing policy.

5. Co-construction of Meaning
   Meaning emerges through the interplay between the researcher and data. The researcher is an active participant, not a passive receiver, co-constructing interpretations with the secondary data sources.

6. Heuristic Closure or Understanding
   The hermeneutic circle "closes" when interpretations form a coherent, mutually supportive whole—where parts complement the whole, and the whole elucidates each part, reaching a comprehensive understanding applicable to the research.

7. Dynamic and Non-linear Process
   Data analysis following the hermeneutic circle is not linear. Instead, it is a dynamic, expanding spiral of understanding where new information revises or expands earlier meanings rather than finalizing a rigid interpretation.

8. Grounding Interpretations in Data
   While interpretation is central, it must remain anchored in the data itself. Claims should be supported by explicit evidence from secondary sources, avoiding speculative leaps beyond what the data justifies.

These principles guide rigorous, reflective, and contextually rich qualitative secondary research analysis in MBA and Housing Studies dissertations, enhancing the depth and credibility of findings."

My question 3: "What are the strengths, weaknesses and challenges of its usage by the researcher with regard to our discussion topic?"

The reply: "Strengths, Weaknesses, and Challenges of Using the Hermeneutic Circle in Qualitative Secondary Data Analysis for MBA and Housing Studies Dissertations

Strengths

• Depth of Understanding: The hermeneutic circle enables researchers to achieve a nuanced, holistic comprehension by continuously relating individual data segments to the wider context, promoting rich interpretation of complex phenomena.

• Flexibility: It suits diverse qualitative secondary sources (e.g., policy documents, business case studies) because the iterative process adapts to both theoretical and empirical data sets.

• Reflexivity: Encourages researchers to reflect critically on their presuppositions and interpretations, which can enhance the validity and rigor of the research.

• Contextual Sensitivity: By moving between parts and the whole, researchers are less likely to take findings out of context, thus producing interpretations that are more grounded and trustworthy for business and housing contexts.

Weaknesses

• Subjectivity Risks: The iterative interpretation process involves significant researcher judgment, introducing the possibility of bias if reflexivity and transparency are not sustained throughout the research.

• Time-Consuming: Moving repeatedly between individual data pieces and the research whole demands considerable time and cognitive investment, especially with voluminous or disparate secondary data.

• Ambiguity in Interpretation: Without clear, systematic procedures, the results may be seen as ambiguous, and different researchers might arrive at divergent conclusions using the same data.

Challenges

• Managing Preconceptions: Researchers must actively and continually question and revise their initial beliefs, which is not always straightforward and may require advanced self-awareness.

• Synthesizing Large Data Sets: Especially for secondary research in MBA and Housing Studies, where datasets and literature can be extensive and diverse, maintaining coherence in the circular movement between part and whole can be difficult.

• Demonstrating Rigor: It can be challenging to clearly document and justify how interpretations were reached—an essential requirement for dissertation research to ensure credibility to academic examiners.

• Balancing Iteration vs. Progress: The continuous back-and-forth can potentially lead to analysis paralysis, where the process becomes endless without clear closure or practical findings for dissertation requirements.

Application Insights

• In MBA research, the hermeneutic circle fosters integration of varied business theories and real-world cases, but may require additional methods (e.g., triangulation) to control for subjective bias.

• In Housing Studies, its strengths lie in contextualizing housing issues within broader socio-economic frameworks, but challenges include maintaining focus on the dissertation’s central research question amidst abundant data.

Researchers can capitalize on the method’s strengths by documenting their reflexive process, setting clear analytic boundaries, and complementing the hermeneutic approach with other systematic analytic strategies to offset its limitations and challenges."

A collection of blog notes on using chatgpt for research purpose.