Quantitative and Qualitative Approaches to Generalization and Replication-A Representationalist View.

Area of Science:

• Philosophy of Science
• Research Methodology

Background:

• Qualitative and quantitative modeling are often seen as distinct.
• A representationalist perspective offers a unified view of these modeling approaches.

Purpose of the Study:

• To re-interpret qualitative and quantitative modeling from a representationalist perspective.
• To analyze generalization and replication strategies in both approaches.
• To propose benefits of inductive reasoning for quantitative research.

Main Methods:

• Utilizing a representationalist framework to analyze modeling approaches.
• Applying modal logic to examine reasoning strategies.
• Distinguishing between variable-based (quantitative) and case-based (qualitative) models.

Main Results:

• Both quantitative (variable-based) and qualitative (case-based) models construct abstract representations.
• Quantitative research typically uses deductive reasoning and top-down generalization.
• Qualitative research typically uses inductive reasoning and bottom-up generalization.
• Replication serves as theory testing in deductive reasoning and scope exploration in inductive reasoning.

Conclusions:

• Quantitative research could benefit from adopting bottom-up generalization strategies from qualitative research.
• Inductive reasoning enhances understanding of theory boundary conditions.
• Failed replications are valuable for exploring the scope of theories, not just testing them.