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Network Science In Education pp 117–138Cite as

Pay, Position, and Partnership: Exploring Capital Resources Among a School District Leadership Team

Abstract

Social science literature suggests that social networks play an important role in developing human and social capital, particularly in the education space. Human capital refers to the knowledge, training, experience, and perceptions that reside within an individual, and social capital reflects the resources that are generated from the social interactions of individual actors. While most studies in education focus on either human or social capital of educators in schools, very little attention has been paid to the idea of “intellectual capital,” which includes the interactions between human and social capital. Further, even less attention has been paid to the intellectual capital among school leaders, particularly in social settings that involve a high degree of human interaction. In addition to intellectual capital, we explore a more traditional form of capital, that of financial capital in the form of salary. This chapter attempts to fill this gap by exploring intellectual capital in the form of human (demographics and perceptions) and social capital and its relationship with actors’ salary, gender, and the level of organizational commitment. The study takes place in one large urban fringe school district with 29 schools serving diverse student populations in southern California. We collected data from all 29 principals, including social network data, demographics, perceptions of organizational commitment, and publicly available salary information. Key findings suggest that principals’ network positions vary by salary and by gender. Specifically, those principals with higher salaries are less likely to be connected with their principal colleagues. Male principals are more likely to have more mutual ties than female principals. For male principals, regardless of salary, their level of mutual ties was much greater when they also reported more organizational commitment. This chapter adds to the existing knowledge base around organizational network studies and sheds new light on educational leadership.

Keywords

  • Social network
  • Closeness
  • Reciprocity
  • Leadership
  • Organizational commitment

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Notes

  1. 1.

    Quadratic assignment procedure (QAP) is designed to test the statistical significance for social network data that is interdependence in nature. Unlike parametric statistical techniques, which assume observations that are analyzed are independent of one another, QAP is a nonparametric technique with no assumption of independence between observations. While using parametric statistics for social network data violates the assumption of independence, QAP is a suitable analytic strategy to test the statistical significance of social network data that are interdependent to one another. More information about QAP can be obtained from Hanneman and Riddle’s (2005) tutorial.

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Author information

Authors and Affiliations

  1. University of California, San Diego, San Diego, CA, USA

    Alan J. Daly & Peter Bjorklund Jr

  2. National Taipei University of Education, Taipei, Taiwan

    Yi-Hwa Liou

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  1. Alan J. Daly
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  2. Yi-Hwa Liou
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  3. Peter Bjorklund Jr
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Editor information

Editors and Affiliations

  1. Data Science Institute, Columbia University, New York, NY, USA

    Catherine B. Cramer

  2. Department of Mathematics, University of California Los Angeles, Los Angeles, CA, USA

    Mason A. Porter

  3. Department of Systems Science and Industrial Engineering, Binghamton University, State University of New York, Binghamton, NY, USA

    Hiroki Sayama

  4. Center for Leadership and Diversity in STEM, Department of Mathematical Sciences, United States Military Academy, West Point, NY, USA

    Lori Sheetz

  5. New York Hall of Science, Corona, NY, USA

    Stephen Miles Uzzo

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Daly, A.J., Liou, YH., Bjorklund, P. (2018). Pay, Position, and Partnership: Exploring Capital Resources Among a School District Leadership Team. In: Cramer, C., Porter, M., Sayama, H., Sheetz, L., Uzzo, S. (eds) Network Science In Education. Springer, Cham. https://doi.org/10.1007/978-3-319-77237-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-77237-0_8

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