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The purpose of this paper is to illuminate for teachers how the suffrage movement is centered in whiteness. The authors posit that this historical erasure is intentional, and teachers should actively find ways to counter that erasure. This paper positions teachers to ask critical questions of dominant narratives, and have students do the same.

Given the existence of historical erasure and the absence of Black suffrage stories, the authors sought to build teachers' content base by conducting a historiography of the dominant narrative of the women's suffrage movement. They examined how state standards and popular online archival collections perpetuate the dominant narrative. They provide teachers with a rich content base and include primary sources they could use to teach this content to their students.

Unsurprising, the Texas and Missouri state standards do little to advance the voices of underrepresented people, especially when it comes to the suffrage movement. Likewise, archival collections are limited by the choice of those who curated the collections. The article presents teachers with lesser known stories of the movement and accompanying primary sources.

Teachers cannot teach what they do not know. So the authors sought to build a teacher's content base so they could tell a more inclusive history. They want to help teachers identify dominant narratives and where historical erasure is happening, and commit to asking critical questions of those narratives and seek to diversity their histories.

This piece is original because much of this content is missing from current history classrooms. In addition, the primary sources and additional resources provided can strengthen a teacher's ability to teach about it.

Quality of life is dependent on a healthy lifestyle and the self-care behavior of individuals. The study's purpose is to find out the determinants of individuals' self-care behavior. As such, self-care behavior is influenced by several factors that include individual knowledge, available information sources and their use, information-seeking related skills and cognitive state.

A quantitative research design followed using a questionnaire-based survey method. A total of 384 responses from the Pakistani public were collected using the convenience sampling technique. Structural equation modeling (SEM) was performed for examining the possible link between the variables.

Health literacy, Internet and social media use, and health information-seeking behavior had a direct/indirect positive impact on self-care behavior, but health anxiety had a negative impact. Health literacy and health information-seeking behavior positively mediated the relationship among Internet and social media use health anxiety and self-care.

Improving health literacy appears to be key to supporting better self-care, but it is an exploratory study, more research is required to confirm these findings. Policymakers, health professionals and information professionals should work together to improve health literacy and support informed self-care among the population.

Thus far, no previous study has examined the collective role of social media exposure, health anxiety, health literacy and health information-seeking behavior as predictors of self-care behavior. Although self-care behavior among the general population might be different compared to chronic patients, only few studies have examined the former as a unit of analysis.

There is a growing need for methodological plurality in advancing operations management (OM), especially with the emergence of machine learning (ML) techniques for analysing extensive textual data. To bridge this knowledge gap, this paper introduces a new methodology that combines ML techniques with traditional qualitative approaches, aiming to reconstruct knowledge from existing publications.

In this pragmatist-rooted abductive method where human-machine interactions analyse big data, the authors employ topic modelling (TM), an ML technique, to enable constructivist grounded theory (CGT). A four-step coding process (Raw coding, expert coding, focused coding and theory building) is deployed to strive for procedural and interpretive rigour. To demonstrate the approach, the authors collected data from an open-source professional project management (PM) website and illustrated their research design and data analysis leading to theory development.

The results show that TM significantly improves the ability of researchers to systematically investigate and interpret codes generated from large textual data, thus contributing to theory building.

This paper presents a novel approach that integrates an ML-based technique with human hermeneutic methods for empirical studies in OM. Using grounded theory, this method reconstructs latent knowledge from massive textual data and uncovers management phenomena hidden from published data, offering a new way for academics to develop potential theories for business and management studies.