Võrdle meetodeid

	Võrdlev Straussi alusteooria (Comparative Straussian Grounded Theory)	Klassikaline maanduv teooria
Valdkond	Kvalitatiivne	Kvalitatiivne
Perekond	Process / pipeline	Process / pipeline
Tekkeaasta	1967 (discovery); systematic Straussian procedures codified 1990/1998	1967
Looja	Anselm Strauss & Juliet Corbin (Straussian GT); comparative extension built on Glaser & Strauss (1967)	Barney G. Glaser and Anselm L. Strauss
Tüüp	Qualitative comparative research design	Qualitative research method
Algallikas	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.
Rööpnimetused	Strauss-Corbin comparative GT, comparative systematic grounded theory, multi-site Straussian GT, comparative grounded theory (Straussian)	Glaserian GT, CGT, original grounded theory, classic GT
Seotud	6	6
Kokkuvõte	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.