Social Sciences Overview

Principles

Definition

Social sciences is the academic domain encompassing diverse disciplines dedicated to the systematic study of human behavior, societies, and their interactions, employing analytical methods to understand social phenomena and societal dynamics. This field investigates the structures, relationships, and development of human society.

Ontological type

Research Methodologies

Core Disciplines

Key Theoretical Traditions

Key developments

Key Figures

Quantification and Institutionalization era

ダーウィンチャールス[1] はこの時代において、大学[1] や研究所[1] といった機関と結びつき、経験的手法を制度化した。The descent of man and selection in relation to sex[2] は人間の変異と自然選択の枠組みを形成することに寄与し、後の社会科学分野における定量的調査を可能にする基盤を提供した。ダーウィンチャールス[1] の考え方はこの制度的枠組みの中で発展し、系統的データ収集と比較分析の価値を強化し、時代の方法論的基準を形づくった[1]。総じて、この業績と時代は生物学の概念を確立された測定実践の枠組みの中に組み込み、経験的で再現可能な探究へと移行する道を強化した[1]。

Micro-Macro Synthesis era

Icek Ajzen [1] is a leading social psychologist active in this era with affiliations at Johns Hopkins University [3] and the University of Illinois Urbana-Champaign [4]. His key contribution in this era is the theory of planned behavior [6], which links attitudes, norms, and perceived behavioral control to behavioral intentions and actions, providing a framework that connects micro-level cognition to macro-level social outcomes. Mark Granovetter [2], associated with Stanford University [5] and Johns Hopkins University [3], published The Strength of Weak Ties [7] in 1973. The work demonstrates that weak ties bridge disparate social circles, facilitating diffusion, social capital formation, and the emergence of collective patterns in networks.

Data-Driven Policy Science era

Brian Nosek and Jeffrey Spies of the Center for Open Science have anchored the era by creating the Open Science Framework and advancing preregistration, data sharing, and reproducibility norms that enable policy-relevant social research. Andrew Gelman, a leading statistician in political and social science, has championed transparent analysis, public data and code, and robust modeling approaches that support credible, scalable inference for policy. Dirk Helbing and Michael Batty have pushed data-driven, geospatially informed modeling of social systems, urban dynamics, and policy simulations that translate empirical insight into city and regional interventions. Beth Noveck and The GovLab have translated data science into governance, promoting open data platforms, experimental policy pilots, and institutional practices that embed evidence into decision making.