Super Qualitative Analysis

Methodology

How the analysis works—and what it can establish.

Super Qualitative Analysis helps a researcher examine a corpus systematically without separating conclusions from the evidence and choices behind them.

Executive summary

The system organizes research documents into reviewable codes, patterns, findings, challenges, and claims. Language models make semantic proposals; deterministic checks preserve document identity and verify quoted source spans. The researcher remains responsible for the research question, interpretive choices, and final conclusions.

Central limitation: a completed analysis is evidence-linked and auditable, but it is not automatically methodologically valid, representative, causal, or equivalent to independent human agreement.

Choose an analysis approach

Qualitative content analysis

Systematically organizes the corpus into categories and compares where they appear.

Thematic framework

Identifies and interprets recurring patterns across documents while retaining their evidence.

Grounded-theory-inspired

Develops categories and relationships iteratively. This is inspired by grounded-theory practices; a fixed corpus and automated run do not establish theoretical saturation or full grounded-theory fidelity.

From source to result

  1. Ingest and preserve document identity.
  2. Examine source segments against the research question.
  3. Develop and apply codes.
  4. Synthesize patterns, findings, contrary evidence, and claims.
  5. Expose results through an evidence matrix and sourced write-up.

Evidence and researcher control

A source anchor keeps an application or claim connected to the text that supports it. A negative case makes disagreement and exceptions inspectable rather than silently smoothing them away.

What the outputs mean

The evidence matrix supports corpus-wide comparison. The sourced write-up presents findings with their evidence and qualifications. Counts describe the analyzed records; they do not by themselves measure importance, prevalence, or causal strength.

Limits and non-claims

  • Model output remains a proposal open to review.
  • Fixed-corpus adequacy is not theoretical saturation.
  • Code counts are not participant prevalence or population estimates.
  • Relationships are not automatically causal.
  • Evidence linkage does not replace expert methodological judgment.