Research Productivity of Social Work PhD Candidates Entering the Academic Job Market: An Analysis of Pre- and Postadmission Productivity Indicators

Cunningham-Williams, Renee M.; Wideman, Ellie; Fields, LaShawnda; Jones, Brittni D.

doi:10.1080/10437797.2018.1503126

Cited by 12 publications

(3 citation statements)

References 44 publications

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“…This finding implies that while efficient tenure and promotion schemes promote RP, without institutional support and research funding that would support the provisions of the tenure and promotion guidelines of an organization, its potential may be insufficient to hold significant ground. Cunningham-Williams et al [114] argued that the relatively higher requirements of tenure and promotion schemes (e.g., research areas) have a perverse effect on the motivation of academics to pursue more research goals. This relationship may be aggravated by the presence of no financial funding and supportive policies that would foster an environment for academics to achieve tenure and promotion requirements.…”

Section: Resultsmentioning

confidence: 99%

“…Negative perceptions of tenure and promotion are prevalent in HEIs. One common misconception is that once an academic is awarded through tenure and promotion, they have minimal incentive to allocate more effort to academic work [114]. However, some studies (e.g., [19,115]) assessed that the productivity of the faculty tends to maintain or increase following the granting of tenure.…”

Section: Tenure and Promotionmentioning

confidence: 99%

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Research Productivity for Augmenting the Innovation Potential of Higher Education Institutions: An Interpretive Structural Modeling Approach and MICMAC Analysis

Ocampo

Aro

Evangelista

et al. 2022

Journal of Open Innovation: Technology, Market, and Complexity

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Current literature merely identifies the driving factors of research productivity in higher education institutions without directly examining their interrelationships that would offer some fundamental insights into the nature of these factors. Thus, this work intends to identify those driving factors and establish their structural relationships to determine those factors with crucial roles in advancing research productivity. Due to the subjectivity of the identified driving factors and the notion that the evaluation of their relationships reflects an expert judgment, an interpretive structural modeling (ISM) approach and the Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis were adopted. Results show that institutional support, reward system, research funding, mentoring, and electronic information resources are the most crucial factors influencing research productivity. When addressed, these driving factors would motivate other driving factors, contributing to higher research productivity. In particular, these findings encourage higher education institutions to (1) efficiently allocate research funds and design mentoring programs, (2) offer efficient research incentive schemes, (3) develop initiatives that would support promising research proposals beneficial to the institution, and (4) collaborate with external organizations to grant funding for research proposals. These results contribute significantly to the literature as it provides meaningful insights that aid decision-makers in higher education institutions in resource allocation decisions, policy-making, and the design of efficient initiatives for augmenting their innovation potential.

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Section: Resultsmentioning

confidence: 99%

Section: Tenure and Promotionmentioning

confidence: 99%

Research Productivity for Augmenting the Innovation Potential of Higher Education Institutions: An Interpretive Structural Modeling Approach and MICMAC Analysis

Ocampo

Aro

Evangelista

et al. 2022

Journal of Open Innovation: Technology, Market, and Complexity

View full text Add to dashboard Cite

show abstract

“…Most of the studies regarding increasing the quality in social work PhD education have been looking at the content of curriculum, such as Drisko, Hunnicutt, and Berenson's (2015) content analysis of PhD programs, or methods to increase scholarly output, such as Bender and Windsor's (2010) piece on demystifying the publication process or Grant and Tomal's (2015) guide for publishing and presenting for PhD students not studying in research universities. Cunningham-Williams, Wideman, Fields, and Jones (2018) conducted the only recent study of PhD student productivity, and they found that the graduates from the Brown School at Washington University had a mean of 5.3 publications per student over a nine-year period. However, this study was limited to only one PhD program in a highly ranked school and included students who were admitted as far back as 2002, more than a decade before the newest GADE quality guidelines.…”

mentioning

confidence: 99%

An Examination of the Productivity of Social Work Doctoral Students

Lightfoot

2023

Preprint

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This study examined social work doctoral student productivity related to the Group for Doctoral Education in Social Work's (GADE) aspirational goals regarding publication, author order, presentations, and teaching by examining doctoral student CVs of students graduating from PhD Programs in the top 39 Schools of Social Work in the United States. On average, students exceeded GADE's publication goals, with an average of 4.0 (median) peer-reviewed articles, and met its sole or first-authored article goal, with an average of 1.0 (median). Students far exceeded GADE’s aspirational presentation goal of two or three presentations, averaging 9.5 (median) presentations at peer-reviewed conferences. Finally, students exceeded GADE’s aspirational goal of teaching at least one independent section, averaging 2.0 (median) independent sections taught. There were no differences productivity based on the ranking of the school in which they were studying.

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The same starting line? The effect of a master’s degree on PhD students’ career trajectories

Jung

Horta

2022

Studies in Continuing Education

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Research Productivity of Social Work PhD Candidates Entering the Academic Job Market: An Analysis of Pre- and Postadmission Productivity Indicators

Cited by 12 publications

References 44 publications

Research Productivity for Augmenting the Innovation Potential of Higher Education Institutions: An Interpretive Structural Modeling Approach and MICMAC Analysis

Research Productivity for Augmenting the Innovation Potential of Higher Education Institutions: An Interpretive Structural Modeling Approach and MICMAC Analysis

An Examination of the Productivity of Social Work Doctoral Students

The same starting line? The effect of a master’s degree on PhD students’ career trajectories

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