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Predictive Sequential Research Design to Study Complex Social Phenomena.

Romel Ramón González-Díaz1, Gladys Inés Bustamante-Cabrera2

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Summary
This summary is machine-generated.

Complex social phenomena require advanced analysis. This study introduces a Predictive Sequential Research Design (DISPRE) using fuzzy logic to overcome biases in mixed-methods research for better understanding and prediction.

Keywords:
artificial intelligencecomplex thinkingdesigndiffuse logicmixed methodologypluralismqualitative researchresearch methodssocial sciences

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Area of Science:

  • Social Sciences
  • Research Methodology

Background:

  • Social phenomena exhibit exponential complexity and interconnectedness.
  • Single research methods are insufficient for analyzing complex social issues.
  • Mixed-methods research aims for integration but faces challenges like methodological bias and 'investigative diffraction'.

Purpose of the Study:

  • To propose a novel research design for analyzing complex social phenomena.
  • To address information biases arising from integrating diverse research methodologies.
  • To enhance the capture, explanation, understanding, and prediction of social complexities.

Main Methods:

  • Development of a Predictive Sequential Research Design (DISPRE).
  • Application of fuzzy logic to mitigate biases from investigative diffraction.
  • Integration of data fracture and redirection strategies.

Main Results:

  • DISPRE offers a framework to manage complexity in social phenomena.
  • Fuzzy logic effectively resolves information biases inherent in mixed-methods integration.
  • The proposed design facilitates a more comprehensive analysis of social entities.

Conclusions:

  • The Predictive Sequential Research Design (DISPRE) provides an innovative approach to studying complex social phenomena.
  • Fuzzy logic is a valuable tool for enhancing the rigor and validity of integrated research.
  • This methodology improves our ability to understand and predict intricate social dynamics.