Checking in on the State of Nonprofit Scholarship: A Review of Recent Research

Minkowitz, Honey; Twumasi, Akua; Berrett, Jessica; Chen, Xintong; Stewart, Amanda

doi:10.20899/jpna.6.2.182-208

Cited by 9 publications

(15 citation statements)

References 30 publications

(43 reference statements)

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“…The categories of education and democracy are different from the previous content analysis findings conducted in the nonprofit studies field, such as Minkowitz et al (2020) and Ma and Konrath (2018). As demonstrated by answering research question three, democracy emerged in JNEL in 2015 and demonstrates the evolution of the field of nonprofit and philanthropic studies.…”

Section: Content Analysis Differencesmentioning

confidence: 72%

“…This paper reports on the preliminary keyword results and sorts them into main categories. Previous content analysis studies of nonprofit and philanthropic studies journals conducted by scholars (Coule et al, 2020, Ma & Konrath, 2018Marberg et al, 2019;Minkowitz et al, 2020) revealed similar themes and theories across nonprofit and philanthropic studies journals. In addition, a previous content analysis study has been conducted on one journal (Bingham & Bowen, 1994).…”

Section: Introductionmentioning

confidence: 84%

“…Therefore, it was necessary to review content analysis articles of more established and well-known nonprofit academic journals to inform our study development and methodology. Minkowitz et al (2020) reviewed 927 articles from the: Nonprofit and Voluntary Sector Quarterly (NVSQ), Nonprofit Management and Leadership (NML), and Voluntas: International Journal of Voluntary and Nonprofit Organizations (Voluntas) from 2013-2018 and found distinctive themes and keywords. Ma and Konrath (2018) used science mapping to review 12,016 articles from 12 different journals to identify a large database of nonprofit and philanthropic studies and conducted a deeper thematic analysis of 2848 articles from 1986-2015 within NML, Voluntas, and NVSQ.…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

A Content Analysis of the Journal of Nonprofit Education and Leadership: Results from Empirical and Theoretical Article Analysis

Carpenter¹,

Taylor²,

Goodman³

et al. 2023

JNEL

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This study reports a content analysis of the first 10 years of the Journal of Nonprofit Education and Leadership (JNEL). A team of 10 researchers spent two years piloting, and comprehensively reading and coding 97 theoretical articles published between 2010-2020. This analysis found the journal published education and leadership-focused articles with an emerging area of democracy-focused articles. The journal produced a mix of quantitative, qualitative, and mixed-methods articles, which differ from previous content analysis studies conducted in other nonprofit and philanthropic studies journals. The keywords were separated into the 16 categories of the NACC curricular guidelines, which demonstrated the variety of education and leadership-focused topics covered in the first 10 years of the journal. This study has implications for nonprofit and philanthropic studies as JNEL is a lesser-known emerging journal that caters to practitioners and scholars.

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Section: Content Analysis Differencesmentioning

confidence: 72%

Section: Introductionmentioning

confidence: 84%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

A Content Analysis of the Journal of Nonprofit Education and Leadership: Results from Empirical and Theoretical Article Analysis

Carpenter¹,

Taylor²,

Goodman³

et al. 2023

JNEL

View full text Add to dashboard Cite

show abstract

“…For example, Brass et al (2018) established the NGO Knowledge Collective 2 to synthesize the academic scholarship on NGOs. Studying our field's intellectual growth has been attracting more scholarly attention (Walk & Andersson, 2020;Minkowitz et al, 2020;Kang, Baek, and Kim 2021).…”

Section: Applying the Methods: The Knowledge Infrastructure Of Nonprofit And Philanthropic Studiesmentioning

confidence: 99%

Computational Social Science for Nonprofit Studies: Developing a Toolbox and Knowledge Base for the Field

Ebeid

Wit

et al. 2021

Voluntas

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How can computational social science (CSS) methods be applied in nonprofit and philanthropic studies? This paper summarizes and explains a range of relevant CSS methods from a research design perspective and highlights key applications in our field. We define CSS as a set of computationally intensive empirical methods for data management, concept representation, data analysis, and visualization. What makes the computational methods “social” is that the purpose of using these methods is to serve quantitative, qualitative, and mixed-methods social science research, such that theorization can have a solid ground. We illustrate the promise of CSS in our field by using it to construct the largest and most comprehensive database of scholarly references in our field, the Knowledge Infrastructure of Nonprofit and Philanthropic Studies (KINPS). Furthermore, we show that through the application of CSS in constructing and analyzing KINPS, we can better understand and facilitate the intellectual growth of our field. We conclude the article with cautions for using CSS and suggestions for future studies implementing CSS and KINPS.

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“…For example, Brass et al (2018) established the NGO Knowledge Collective 2 to synthesize the academic scholarship on NGOs. Studying our field's intellectual growth has been attracting more scholarly attention (Walk and Andersson 2020;Minkowitz et al 2020;Kang, Baek, and Kim 2021).…”

Section: Natural Language Processingmentioning

confidence: 99%

Computational social science for nonprofit studies: Developing a toolbox and knowledge base for the field

Ma¹,

Ebeid²,

Wit³

et al. 2020

Preprint

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How can computational social science (CSS) methods be applied in nonprofit and philanthropic studies? This paper summarizes and explains a range of relevant CSS methods, and highlights key applications in our field. Based on a typical design of empirical social science research, we define CSS as a set of computationally intensive empirical methods for data organization, concept representation, data analysis, and visualization. What makes the computational methods “social” is that the purpose of using these methods is to serve empirical social science research, such that theorization can have a solid ground. We illustrate the promise of CSS in our field by using it to construct the largest and most comprehensive database of scholarly references in our field so far, the Knowledge Infrastructure of Nonprofit and Philanthropic Studies (KINPS). Furthermore, we show that through the application of CSS in the analyses of the KINPS, our field’s knowledge and knowledge producing activities can be advanced, which is a core requisite for the development of our field as a discipline. We conclude the article with cautions for using CSS and suggestions for future research directions implementing CSS and the KINPS.

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Checking in on the State of Nonprofit Scholarship: A Review of Recent Research

Cited by 9 publications

References 30 publications

A Content Analysis of the Journal of Nonprofit Education and Leadership: Results from Empirical and Theoretical Article Analysis

A Content Analysis of the Journal of Nonprofit Education and Leadership: Results from Empirical and Theoretical Article Analysis

Computational Social Science for Nonprofit Studies: Developing a Toolbox and Knowledge Base for the Field

Computational social science for nonprofit studies: Developing a toolbox and knowledge base for the field

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