Methoden vergelijken

	Vergelijkende Straussiaanse Grounded Theory	Klassieke Grounded Theory
Vakgebied	Kwalitatief	Kwalitatief
Familie	Process / pipeline	Process / pipeline
Jaar van ontstaan	1967 (discovery); systematic Straussian procedures codified 1990/1998	1967
Grondlegger	Anselm Strauss & Juliet Corbin (Straussian GT); comparative extension built on Glaser & Strauss (1967)	Barney G. Glaser and Anselm L. Strauss
Type	Qualitative comparative research design	Qualitative research method
Oorspronkelijke bron	Strauss, A., & Corbin, J. (1998). Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory (2nd ed.). Sage. ISBN: 978-0803959408	Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine.
Aliassen	Strauss-Corbin comparative GT, comparative systematic grounded theory, multi-site Straussian GT, comparative grounded theory (Straussian)	Glaserian GT, CGT, original grounded theory, classic GT
Verwant	6	6
Samenvatting	Comparative Straussian Grounded Theory applies the systematic open–axial–selective coding framework of Strauss and Corbin across two or more purposively selected contexts, groups, or sites to generate theory that explains both within-context processes and cross-context variation. The constant comparative method — the analytic engine first described by Glaser and Strauss (1967) — is elevated to a deliberate design-level strategy, allowing researchers to build mid-range theory that accounts for how social processes unfold differently under varying conditions.	Classic Grounded Theory (CGT) is a systematic qualitative methodology for generating substantive theory from empirical data. Developed by Barney Glaser and Anselm Strauss in 1967, it uses iterative cycles of data collection, constant comparison, and memo writing to produce a core category and surrounding conceptual framework that explains a social or psychological process. Unlike its later variants, Glaserian CGT insists on emergence — theory must arise from data without forcing preconceived frameworks.