Recent developments in causal inference and machine learning
This article reviews recent advances in causal inference relevant to sociology. We focus on
a selective subset of contributions aligning with four broad topics: causal effect identification …
a selective subset of contributions aligning with four broad topics: causal effect identification …
REFORMS: Consensus-based Recommendations for Machine-learning-based Science
Machine learning (ML) methods are proliferating in scientific research. However, the
adoption of these methods has been accompanied by failures of validity, reproducibility, and …
adoption of these methods has been accompanied by failures of validity, reproducibility, and …
Disparate Effects of Disruptive Events on Children
Disruptive events such as economic recessions, natural disasters, job loss, and divorce are
highly prevalent among American families. These events can have a long-lasting impact …
highly prevalent among American families. These events can have a long-lasting impact …
Measuring vaccination coverage and concerns of vaccine holdouts from web search logs
To design effective vaccine policies, policymakers need detailed data about who has been
vaccinated, who is holding out, and why. However, existing data in the US are insufficient …
vaccinated, who is holding out, and why. However, existing data in the US are insufficient …
On the actionability of outcome prediction
Predicting future outcomes is a prevalent application of machine learning in social impact
domains. Examples range from predicting student success in education to predicting …
domains. Examples range from predicting student success in education to predicting …
Reforms: Reporting standards for machine learning based science
Machine learning (ML) methods are proliferating in scientific research. However, the
adoption of these methods has been accompanied by failures of validity, reproducibility, and …
adoption of these methods has been accompanied by failures of validity, reproducibility, and …
Variable importance in high-dimensional settings requires grouping
Explaining the decision process of machine learning algorithms is nowadays crucial for both
model's performance enhancement and human comprehension. This can be achieved by …
model's performance enhancement and human comprehension. This can be achieved by …
[HTML][HTML] Exploring the other side of innovative managerial decision-making: Emotions
AM Kanzola, K Papaioannou, PE Petrakis - Journal of Innovation & …, 2024 - Elsevier
The strict rational paradigm of neoclassical economic theory has resulted in limited
exploration of emotions in managerial decision-making processes. This study attempts to …
exploration of emotions in managerial decision-making processes. This study attempts to …
Methodological advances in quantitative social science: In celebration of the Social Science Research 50th anniversary
Methodological advances in quantitative social science: In celebration of the Social Science
Research 50th anniversary Methodological advances in quantitative social science: In …
Research 50th anniversary Methodological advances in quantitative social science: In …
Literature Review on Health Emigration in Rare Diseases—A Machine Learning Perspective
The article deals with one of the effects of health inequalities and gaps in access to
treatments for rare diseases, namely health-driven emigration. The purpose of the paper is …
treatments for rare diseases, namely health-driven emigration. The purpose of the paper is …