Foundations of Quantitative Social Science Research - Chapter 1 to Chapter 4
Citation: HUANG, W. (2026, January 9). [Book] Foundations of Quantitative Social Science Research. https://doi.org/10.17605/OSF.IO/EVR46
Current Research Projects
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- Generative Relational Economics
Economic relations, generative capacity, and the formation of value; a developing chapter series.
- Heterogeneous Value Conversion and Justice
Conversions between forms of value, procedural ordering, and their implications for justice.
- Normative Formation and Relational Responsibility
Social contracts, asymmetric generative capacity, and the conditions of effective alternatives.
- AI, Interpretation, and Judgment
Clarifying dialogue and theory of mind, problem formation, and the education of judgment.
- Governance near Criticality
Intervention, evidence-to-action, and distributed possibilities under critical-transition uncertainty.
Recent Manuscripts
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- Generative Relational Economics - Chapter 14: Generative ValueChapter preprint · PDF
- A Preliminary Formalism for Heterogeneous Value Conversion in the Generative Relational FrameworkPreprint · PDF
- Heterogeneous Value Conversion and Justice: A Generative Relational DiscussionPreprint · PDF
- Procedural Justice in Heterogeneous Conversion: A Note on Noncommutative OrderingPreprint · PDF
- A Preliminary Discussion of Normative Formation under Asymmetric Generative CapacityPreprint · PDF
- Reflections on Judgment in the Age of AI: Problem Formation, Aesthetic Judgment, and the Education of JudgmentPreprint · PDF
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Reflections on Partially Observable Markov Decision Processes and Decision Rationality
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I am deeply interested in the Partially Observable Markov Decision Process (POMDP) model as developed in fields such as computational neuroscience and machine learning.
First Draft of Chapter 4, Section 3 - Epistemology of Measurement and Data Quality in Quantitative Social Science Research
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Having established what we dataficate, namely entities and their associated states, processes, properties, relations, and events, and how these phenomena are represented in quantitative research, we now confront the epistemological question: how do we know that our measurements validly capture what
Abstract 'A Relational-Ontological and Constructivist Analysis of Neurodynamical Geometry in the Language of Quantum Field Theory'
The dynamics of neural systems form geometric structures in phase space whose analysis offers potential for identifying and predicting neurodynamics-related disorders such as epileptic seizures.
The Crisis of the Symbolic Order and Relational Being (2nd Discussion)
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In the process of seeking self-subjectivity, humanity often requires the presence of an Other. The human being is an animal that witnesses its own subjectivity in the Other and witnesses its own existence in interaction with the Other.
Discussion on Future Education (1st) - How AI Brings Challenges and Opportunities
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“Future education” is a grand and expansive object. From a retrospective view of how human beings come to know the world and change the world, this process passes through at least three levels.
First Draft of Chapter 4, Section 1 - The Ontology of Social Facts and Data in Quantitative Social Science Research
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Data is conceptualized differently across disciplines. In statistics, data are observations that can be analyzed to reveal patterns (Fisher, 1925).
【Research Note】The Representation Problem in International Relations Event Modeling and Exploration of Theoretical Tools — An Event-Driven Research Path Based on Quantum Spiking Neural Networks
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This study proposes an international relations modeling approach based on Quantum Spiking Neural Networks (QSNNs), combining the representational structures of quantum computation with event-driven neural dynamics.
Anarchy, Nonlinearity, and Emergence in International Relations - A Spiking Neural Network Framework Approach
Citation: HUANG, W. (2026, January 12). Anarchy, Nonlinearity, and Emergence in International Relations: A Spiking Neural Network Framework Approach.
Foundations of Quantitative Social Science Research - Introduction Chapter
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Citation: HUANG, W. (2026, January 9). [Book] Foundations of Quantitative Social Science Research. https://doi.org/10.17605/OSF.IO/EVR46