While there is a vast literature that considers the collection and analysis of qualitative data, there has been limited attention to audio transcription as part of this process. In this paper, I address this gap by discussing the main considerations, challenges and implications of audio transcription for qualitative research on the third sector. I present a framework for conducting audio transcription for researchers and transcribers, as well as recommendations for writing up transcription in qualitative research articles.

The paper investigates processes and consequences of ‘philanthropic kinning’, that is the use of kinship and family idioms in constructing and maintaining personal relations between donors and recipients in philanthropy. Usual studies collapse the occurrence of kinship metaphors in philanthropy either as evidence of ‘prosociality’ (e.g. trust, care or love) or more frequently as evidence of ‘paternalism’ (power and domination of donors over recipients, and their objectification). This paper claims that introducing kinship and parenting studies into researching philanthropy would greatly refine our understanding of donor–recipient relations. In the framework of a qualitative case study of a philanthropic ‘godparenthood’ programme organised in Hungary supporting ethnic Hungarian communities in Romania, this paper looks at the roles, responsibilities and obligations various forms of philanthropic kinship offer for the participants; and relations of power unfolding in helping interactions. With such concerns, this paper complements earlier research on hybridisation of philanthropy, through its sectoral entanglements with kinship and family. Also, it contributes to research on inequalities in philanthropy, by showing how philanthropic kinning may recreate, modify or reshape donor–recipient power relations in diverse ways.

Why did some individuals react to the Covid-19 crisis in a prosocial manner, whereas others withdrew from society? To shed light onto this question, we investigate changing patterns of charitable giving during the pandemic. The study analyzes survey data of 2000 individuals, representative of the populations of Germany and Austria. Logistic regressions reveal that personal affectedness by Covid-19 seems to play a crucial role: those who were personally affected either mentally, financially, or health-wise during the first 12 months of Covid-19 were most likely to have changed their giving behavior. The observed patterns fit psychological explanations of how human beings process existential threats. Our findings indicate that a profound societal crisis in itself mainly leads to changes in charitable giving if individuals are severely affected on a personal level. Thereby, we contribute to a better understanding of the mechanisms underlying individuals’ charitable giving behavior in times of crisis.

Elite donors are a crucial and sought-after source of funding for many nonprofit organisations, but there is a dearth of substantive empirical studies presenting primary data on such donors’ motivations, experiences and perspectives. There are challenges for social scientists in conducting interviews with elites, notably: gaining access to elite donors; developing sufficient rapport to discuss a topic that involves money and morals; and making sense of data without being dazzled by striking surface differences between elites and non-elites. These barriers have resulted in a long-standing over-reliance on secondary sources and on interviews with proxies such as foundation staff and wealth advisers. This paper reviews the small body of work that presents findings from interviews with elite donors and draws on my experience of conducting interviews with 46 wealthy UK donors, in order to critically analyse the implementation of this research design. This paper adds to the literature by extending understanding of elite donors’ reasons for agreeing to be interviewed and contributes to advancing third sector research by highlighting strategies to overcome challenges in conducting elite interviews in order to gain a less mediated understanding of the contexts, cultures and subjectivities of their focus of study.

A combination of computer-aided qualitative data analysis (CAQDAS) and latent class analysis (LCA) can substantially augment the qualitative analysis of textual data sources used in third-sector studies. This article explains how to employ both techniques iteratively to capture often implicit ideas and meaning-making by third-sector leaders, donors, and other stakeholders. CAQDAS facilitates the coding, organization, and quantification of qualitative data, effectively creating parallel qualitative and quantitative data structures. LCA facilities the discovery of latent concepts, document classification, and the identification of exemplary qualitative evidence to aid interpretation. For third-sector research, CAQDAS and LCA are particularly promising because diverse stakeholders usually do not share homogenous views about core issues such as organizational effectiveness, collaboration, impact measurement, or philanthropic approaches, for example. The procedure explained here provides a rigorous method for discovering and understanding diversity in perspectives and is especially useful in medium-n research settings common to third-sector scholarship.

“Resilience and the Management of Nonprofit Organizations” is a book that explores the concept of resilience management for nonprofit organizations. The authors, Dennis Young and Elizabeth Searing, argue that the current paradigm of nonprofit management, which focuses on trustworthiness and efficiency, needs to be revised to adequately address the challenges facing nonprofit organizations. They propose a new paradigm based on resilience, which they define as the ability of organizations to adapt to changing circumstances and continue serving their missions effectively. The book provides strategies for anticipating and preparing for crises, explores the various dimensions of organizational resilience, and offers management strategies for achieving organizational resilience. It also discusses the need for “organizational slack” in order to be flexible and adaptable in the face of challenges.

Extant research has focused on the role of philanthropy in the socio-economic development of western countries, but little is known about the role of indigenous voluntary organisations in bridging social divides in the developing world. To help redress this imbalance, we present findings on the motivations, strategies, methods, and impact of five large philanthropically funded voluntary organizations in Pakistan. We ask how and why such organizations are formed and gain traction to provide valuable services for large numbers of poor people in a society riddled with inequalities. Although differing considerably in their relations to markets and philanthropy, we find that success in all cases followed from commitment to Islamic philanthropy and the ideal of social inclusion, social innovation, exploitation of social capital, and scaling-up. Our contribution is to demonstrate how in developing countries philanthropy and social entrepreneurship together can play a decisive role in realizing a more just society.

This paper charts the rapid rise of data science methodologies in manuscripts published in top journals for third sector scholarship, indicating their growing importance to research in the field. We draw on critical quantitative theory (QuantCrit) to challenge the assumed neutrality of data science insights that are especially prone to misrepresentation and unbalanced treatment of sub-groups (i.e., those marginalized and minoritized because of their race, gender, etc.). We summarize a set of challenges that result in biases within machine learning methods that are increasingly deployed in scientific inquiry. As a means of proactively addressing these concerns, we introduce the “Wells-Du Bois Protocol,” a tool that scholars can use to determine if their research achieves a baseline level of bias mitigation. Ultimately, this work aims to facilitate the diffusion of key insights from the field of QuantCrit by showing how new computational methodologies can be improved by coupling quantitative work with humanistic and reflexive approaches to inquiry. The protocol ultimately aims to help safeguard third sector scholarship from systematic biases that can be introduced through the adoption of machine learning methods.