The research context
Rebalancing Retention: Organizational Solutions for the Marine Corps Career Planning Program is a June 2025 Naval Postgraduate School thesis by a Marine gunnery sergeant, published in the Department of Defense Management’s Acquisition Research Program Sponsored Report Series and archived open access on Calhoun.
The author conducted 25 semi-structured interviews with active-duty Career Counselors across three billet types, a 73.5% participation rate, and applied a grounded analysis approach following the Gioia methodology. The study was approved by the Naval Postgraduate School and Marine Corps Institutional Review Boards.
Human judgment stayed in the loop
Evidano produced an initial structure of 62 first-order concepts tied to 799 interview excerpts. Through iterative review the researcher merged related concepts into second-order themes, ending with 25 concepts, 361 excerpts, six second-order themes, and two aggregate dimensions: workload management and resource allocation, and a systematic approach to retention.
The publication discloses its use of Evidano within the data analysis section, names the tool, and describes how the researcher reviewed and refined the AI-assisted output. It is a credible example of transparent, human-supervised AI use in published research, with the AI assisting the analysis rather than replacing the researcher.
How Evidano fit the workflow
The publication describes a workflow where AI accelerated structuring and the researcher kept interpretive control.
- 125 interviews, transcribed and prepared
Transcripts were reviewed against the audio for accuracy and anonymized before analysis, then distilled into research memos.
- 2Evidano surfaced an initial structure
The platform produced 62 first-order concepts tied to 799 interview excerpts.
- 3The researcher reviewed and refined
Through iterative human review, related concepts were merged into higher-order themes.
- 4A final, traceable model
25 concepts, 361 excerpts, 6 second-order themes, and 2 aggregate dimensions.
“To support the analysis, I used AILYZE Pro, a qualitative data analysis platform that leverages its own AI model to assist with theme identification, frequency tracking, and cross-group comparison.”
“Through iterative review and refinement, I merged related concepts into second-order themes, resulting in a final output of 25 concepts, 361 excerpts, six second-order themes, and two aggregate dimensions that form the structure of the final analytical model.”
Surfaced an initial set of concepts directly from interview language.
Mapped how each concept appeared across all 25 interviews.
Named in the thesis as one of the platform capabilities used to support the analysis.
Tied concepts back to specific interview excerpts for review.