Transparency is once again a central issue of debate across types of qualitative research. Work on how to conduct qualitative data analysis, on the other hand, walks us through the step-by-step process on how to code and understand the data we've collected. Although there are a few exceptions, less focus is on transparency regarding…

Background/Context: Recently there has been increased emphasis on disaggregating students' experiences collected through surveys based on student identities (Arredondo, 2016). Yet demographic data collection is problematic by nature, often reducing the complexity of an individual's racial, gender, or sexual identity to a single category. Racial…

This paper explores the concept of dynamically generating definitions using a deep-learning model. We do this by creating a dataset that contains definition entries and contexts associated with each definition. We then fine-tune a GPT-2 based model on the dataset to allow the model to generate contextual definitions. We evaluate our model with…

Purpose: This study presents a novel methodology/process for assessing inclusion of theoretically-based implementation factors within available adoption-ready health promotion programs. Methods: Classroom-based physical activity (CBPA) programs were used as an example to describe the process. Our team selected an implementation science framework…