Crowdworksheets: Accounting for individual and collective identities underlying crowdsourced dataset annotation

M Díaz, I Kivlichan, R Rosen, D Baker… - Proceedings of the …, 2022 - dl.acm.org
Human annotated data plays a crucial role in machine learning (ML) research and
development. However, the ethical considerations around the processes and decisions that …

Digital and computational demography

R Kashyap, RG Rinderknecht… - … handbook on digital …, 2023 - elgaronline.com
Like demography more generally, digital and computational demography is concerned with
measuring populations and demographic processes of fertility, mortality, and migration, as …

Introduction to the special collection on the fragile families challenge

MJ Salganik, I Lundberg, AT Kindel, S McLanahan - Socius, 2019 - journals.sagepub.com
The Fragile Families Challenge is a scientific mass collaboration designed to measure and
understand the predictability of life trajectories. Participants in the Challenge created …

What tears couples apart: A machine learning analysis of union dissolution in Germany

B Arpino, M Le Moglie, L Mencarini - Demography, 2022 - read.dukeupress.edu
This study contributes to the literature on union dissolution by adopting a machine learning
(ML) approach, specifically Random Survival Forests (RSF). We used RSF to analyze data …

Successes and struggles with computational reproducibility: lessons from the fragile families challenge

DM Liu, MJ Salganik - Socius, 2019 - journals.sagepub.com
Reproducibility is fundamental to science, and an important component of reproducibility is
computational reproducibility: the ability of a researcher to recreate the results of a published …

Exploring Childhood Disabilities in Fragile Families: Machine Learning Insights for Informed Policy Interventions

J Wang, SK Alam, S Ganguly, MR Hassan… - Journal of Disability …, 2024 - scienceopen.com
This study delves into the multifaceted challenges confronting children from vulnerable or
fragile families, with a specific focus on learning disabilities, resilience (measured by grit) …

[PDF][PDF] Comparing Humans and Algorithms in Feature Ranking: A Case-Study in the Medical Domain.

J Hanselle, J Kornowicz, S Heid, K Thommes… - LWDA, 2023 - ceur-ws.org
The selection of useful, informative, and meaningful features is a key prerequisite for the
successful application of machine learning in practice, especially in knowledge-intense …

[图书][B] Human-Machine Collaboration in Real-World Machine-Learning Applications

CV Roberts - 2023 - search.proquest.com
Automation tools like machine learning are a necessity in our big data world. Thanks to the
Internet and advancements in all facets of computer and storage technology, almost …

[图书][B] Towards Automated Axiom Generation: A Semi-Automated Approach to Generating" Knowledge and Rule Base" Corpora from Text Narratives

A Prabhu - 2021 - search.proquest.com
With the exponential rise of data in recent years, deep learning has risen to be one of the
most prominent forms of artificial intelligence. With many successful applications, deep …

[PDF][PDF] Effectiveness of Human-in-the-loop Design Concept for eHealth Systems

D Diyasena, N Arambepola, L Munasinghe - 2022 - researchgate.net
In the modern era, AI has revolutionized eHealth applications. For instance, existing systems
could automate complex decisions or tasks performed by medical personnel and deliver …