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The U.S. has moved beyond peak water security. Infrastructural degradation, institutional inertia, and climate change are reducing the ability of households and communities to benefit from near-universal safe, adequate, affordable, sustainable water services. Yet, current supply-side research tools, that focus largely on system performance, are not equipped to measure the prevalence and lived experiences of household water insecurity, thus limiting the evidence available to policymakers, utilities, and communities to make decisions about water services. We discuss how demand-side metrics, such as household-level water insecurity scales validated for high-income contexts, such as the U.S., can help stakeholders to better identify local variation in user water issues, guide resource allocation, and improve hazard and disaster response. Targeted infrastructure investments informed by these metrics can enhance water security, reduce reliance on emergency social services, and promote public health and economic vitality. To address 21^st-century water challenges effectively, we must integrate experiential measures into local, regional, and national water assessments. 

Writing winning proposals for funding research is an essential skill for doctoral students in the social sciences. Still, most anthropology programs lack formal instruction on this, relying instead on informal mentorship. To advance this, we evaluated the Value Proposition framework in teaching anthropology Ph.D. students to write proposals. Our findings from the feedback from students and faculty in the NSF-funded Cultural Anthropology Methods Program (CAMP) offer insights for using this framework to bridge the proposal-writing gap in the training of cultural anthropologists. 

An increasing number of studies find that water sharing—the non-market transfer of privately held water between households—is a ubiquitous informal practice around the world and a primary way that households respond to water insecurity. Yet, a key question about household water sharing remains: is water sharing a viable path that can help advance household water security? Or should water sharing be understood as a symptom of water insecurity in wait for more formalized solutions? Here, we address this question by applying Sen’s entitlement framework in an integrative review of empirical scholarship on household water sharing. Our review shows that when interhousehold water sharing is governed by established and well-functioning norms it can serve as a reliable transfer entitlement that bolsters household water security. However, when water sharing occurs outside of established norms (triggered by broader entitlement failures) it is often associated with significant emotional distress that may exacerbate conditions of water insecurity. These findings suggest that stable, norm-based water sharing arrangements may offer a viable, adaptive solution to households facing water insecurity. Nevertheless, more scholarship is needed to better understand when and how norm-based water transfer entitlements fail, the capacity of water sharing practices to evolve into lasting normative entitlements, and the impact of interhousehold water sharing on intrahousehold water security. 

There has been a recent explosion of articles on minimum sample sizes needed for analyzing qualitative data. The purpose of this integrated review is to examine this literature for 10 types of qualitative data analysis (5 types of saturation and 5 common methods). Building on established reviews and expanding to new methods, our findings extract the following sample size guidelines: theme saturation (9 interviews; 4 focus groups), meaning saturation (24 interviews; 8 focus groups), theoretical saturation (20–30+ interviews), metatheme saturation (20–40 interviews per site), and saturation in salience (10 exhaustive free lists); two methods where power analysis determines sample size: classical content analysis (statistical power analysis) and qualitative content analysis (information power); and three methods with little or no sample size guidance: reflexive thematic analysis, schema analysis, and ethnography (current guidance indicates 50–81 data documents or 20–30 interviews may be adequate). Our review highlights areas in which the extant literature does not provide sufficient sample size guidance—not because it is epistemologically flawed, but because it is not yet comprehensive and nuanced enough. To address this, we conclude by proposing ways researchers can navigate and contribute to the complex literature on sample size estimates. 

ABSTRACT Biological anthropologists have long engaged in qualitative data analysis (QDA), though such work is not always foregrounded. In this article, we discuss the role of rigorous and systematic QDA in biological anthropology and consider how it can be understood and advanced. We first establish what kinds of qualitative data and analysis are used in biological anthropology. We then review the ways QDA has been used in six subfields of biological anthropology: primatology, human biology, paleoanthropology, dental and skeletal biology, bioarchaeology, and anthropological genetics. We follow that with an overview of how to use QDA methods: three simple QDA methods (i.e., word‐based analysis, theme analysis, and coding) and three QDA approaches for model‐building and model‐testing (i.e., content analysis, semantic network analysis, and grounded theory). With this foundation in place, we discuss how QDA can support transformative research in biological anthropology—emphasizing the valuable role of QDA in inductive and community‐based research. We discuss how QDA supports transformative research using mixed‐methods research designs, participatory action research, and abolition and Black feminist research. Finally, we consider how to close a QDA project, reflecting on the logistics, ethics, and limitations of qualitative data sharing, including how researchers can use the CARE Principles (Collective Benefit, Authority to Control, Responsibility, and Ethics) to support Indigenous data sovereignty.