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Use when analyzing documents, artifacts, policies, or media as qualitative data sources.
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Basierend auf der SOC-Berufsklassifikation
Use when writing academic prose for qualitative research — findings, methods, discussion sections with appropriate voice and conventions.
Use when conducting participatory action research (PAR) involving collaborative inquiry, cycles of action and reflection.
Use when formatting academic work in APA 7th edition style — citations, references, headings, tables, and manuscript structure.
Use when designing or conducting case study research following Yin's multiple case study methodology or Stake's approach.
Use when developing and densifying categories with properties, dimensions, conditions, and consequences.
Use when formatting academic work in Chicago/Turabian style — notes-bibliography or author-date systems.
| name | document-analysis |
| description | Use when analyzing documents, artifacts, policies, or media as qualitative data sources. |
Documents include policies, emails, meeting minutes, curricula, clinical records (where permitted), social media threads, photographs, videos, and organizational charts. In qualitative research, documents are not “background”; they are potential primary data when your questions concern texts, practices encoded in artifacts, or institutional meaning-making.
Classify each document by authorship, audience, purpose, and genre before heavy interpretation.
Ask: Who produced this, when, under what constraints, and for whom? Triangulate with interviews or observations when documents conflict with practice (“official story” vs “work-as-done”). Note redactions, version control gaps, and translation effects if documents cross languages.
Qualitative content analysis codes meaning units into categories while preserving context. Steps typically include: define corpus boundaries; sample or include all relevant texts; define recording units (paragraph, post, case note segment); develop codes inductively, deductively, or hybrid; maintain a codebook with examples; iterate definitions as patterns clarify.
Discourse-oriented reading examines how language constructs subjects, objects, and power relations. Useful prompts: What is presupposed? Who is included/excluded? What metaphors recur? What silences matter? Align discourse analysis commitments (e.g., critical, Foucauldian, discursive psychology) with your paradigm statement.
Treat a document segment as an incident: compare segment to segment and segment to emerging concepts. Avoid letting document headings dictate your categories if the data pushes elsewhere. Keep a memo trail for interpretive leaps (e.g., why a policy clause signals “risk shifting” as a category).
GT’s “all is data” does not mean naive acceptance. Documents can misrepresent, lag reality, or perform legitimacy. Critical reading asks what the text does socially while still mining it for participant/informant meanings embedded in wording and format.
Before coding a page: note genre, intended audience, and production constraints (who could edit this, and why it exists).
While coding: treat each excerpt as an incident; compare to interviews/observations when interpretations hinge on “official vs practiced” gaps.
In write-ups: distinguish textual claims from your interpretation; flag uncertain authorship or missing pages rather than smoothing gaps silently.
