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Accumulated evidence identifies discernible gender gaps across many dimensions of professional academic careers including salaries, publication rates, journal placement, career progress, and academic service. Recent work in political science also reveals gender gaps in citations, with articles written by men citing work by other male scholars more often than work by female scholars. This study estimates the gender gap in citations across political science subfields and across methodological subfields within political science, sociology, and economics. The research design captures variance across research areas in terms of the underlying distribution of female scholars. We expect that subfields within political science and social science disciplines with more women will have smaller gender citation gaps, a reduction of the "Matthew effect" where men's research is viewed as the most central and important in a field. However, gender citation gaps may persist if a "Matilda effect" occurs whereby women's research is viewed as less important or their ideas are attributed to male scholars, even as a field becomes more diverse. Analysing all articles published from 2007–2016 in several journals, we find that female scholars are significantly more likely than mixed gender or male author teams to cite research by their female peers, but that these citation rates vary depending on the overall distribution of women in their field. More gender diverse subfields and disciplines produce smaller gender citation gaps, consistent with a reduction in the "Matthew effect". However, we also observe undercitation of work by women, even in journals that publish mostly female authors. While improvements in gender diversity in academia increase the visibility and impact of scholarly work by women, implicit biases in citation practices in the social sciences persist.

Simulation enables analysis of social systems that would be difficult or unethical to experiment upon directly. Agent-based models have been used successfully in the field of generative social science to discover parsimonious sets of factors that generate social behavior. This methodology provides an avenue to explore the spread of anti-government sentiment in populations and to compare the effects of potential Military Information Support Operations (MISO) actions. This research develops an agent-based model to investigate factors that affect the growth of rebel uprisings in a notional population. It adds to the civil violence model developed by Epstein (2006) by enabling communication between agents in the manner of a genetic algorithm and friendships based on shared beliefs. A designed experiment is performed. Additionally, two counter-propaganda strategies are compared and explored. Analysis identifies factors that have effects that can explain some real-world observations, and provides a methodology for MISO operators to compare the effectiveness of potential actions.

The main purpose of this paper is to identify lawlike regularities inside social sciences. This purpose rises from our will to contribute to the debate about the scientificity of such topics. After providing an overview of the most authoritative scholars who have broached the issue, an attempt will be made to propose an alternative answer through scientific computational research, that is neural networks.

I. General Methodology -- A New Epitheoretical Analysis of Social Theories; A Reconstruction of their Background Knowledge including a Model of Statistical Decision Theory -- Theories and Phenomena -- Partial Interpretation and Microeconomics -- The Foundation of Science on Cognitive Mini-Models, with Applications to the German Methodenstreit and the Advent of Econometrics -- II. Methods for Laying the Foundations of Social Systems and Social Structures -- Systems of Social Exchange -- The Concept of Social Structure -- Societies and Social Decision Functions -- Honing Occam's Razor: A General System Theory Perspective on Social Science Methodology -- III. Vagueness, Imprecision and Uncertainty in Social Laws and Forecasts -- Toward Fuzzy Reasoning in the Behavioral Sciences -- Evolutionary Laws in the Social Sciences -- Methodological Analysis of Imprecision in the Assessment of Personal Probabilities -- The Necessity, Sufficiency and Desirability of Experts as Value Forecasters -- Rational Choice Models and Self-Fulfilling and Self-Defeating Prophecies -- IV. Methodology of Statistics and Hypothesis Testing -- Statistical Probabilities: Single Case Propensities vs. Long-Run Frequencies -- Variety of Objects as a Parameter for Experimentation: An Extension of Carnap's Inductive Logic -- The Strategic Combination Argument -- Index of Names -- Index of Subjects.

Existing formal models of political behavior have followed the lead of the natural sciences and generally focused on methods that use continuous-variable mathematics. In 2002, Stephen Wolfram produced an extended critique of that approach in the natural sciences, and suggested that a great deal of natural behavior can be accounted for using rules that produce discrete patterns. This paper reports some initial findings designed to apply this pattern-based method to political event data. We believe that discrete sequence rule (DSR) models can provide a new social science methodology that is capable of preserving the agential basis of social interaction, tracking multiple agents as they enact rules through behavior directed at one another, and capturing the evolution of such interaction over time. The core of this project is a new, publicly accessible Web-based tool designed for the visualization and analysis of event data patterns (http://www.nkss.org). Using event data on the Israel-Palestine conflict generated by the TABARI automated coding program of the Kansas Event Data System (KEDS) for the period 1979-2004, we perform an initial exploration of this methodology. Specifically, we identify patterned behavior for which specific rule use can be imputed, and then examine several agent-based rules, plus four "meta-rules," to parse Israeli-Palestinian interaction over time. Face validity of the analysis is apparent, and we also find the qualitative historical record can be augmented through observation of rule enactment in the event stream. Several descriptive empirical applications are demonstrated, including moving totals and increasingly complex sequences of rule enactment that go beyond the simple variations on tit-for-tat responses. While this paper represents an exploratory analysis of the method, the results are promising enough to warrant further investigation beyond its use in thick description as demonstrated here, to ultimately include hypothesis generation and falsification. Adapted from the source document.