WINTER 2012 - National Association of Schools of Public Affairs and ...

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Bin Chen, Feng Wang and Jianmin Song to 2.5 classmates for seeking career-related information and advice and shared the information and advice with 2.5 classmates. 3 Across the four networks, the academic network had the highest out-degree and in-degree centrality scores (5.9), the friendship network scored the second highest (4.8), and career advice network scored third (2.5). The socio-emotional support network had the lowest scores on out- and in-degree measures. The results are consistent with our visual observation that the academic and friendship networks are much more connected than the career advice and socio-emotional support networks. We observed similar patterns across the four networks in terms of closeness centrality and betweenness centrality. Closeness centrality is a measure of how centrally close a person is, meaning that he or she can reach all others more quickly. An individual with a higher closeness centrality score is usually considered as an information disseminator. On average, MPA students in the academic and friendship networks are able to reach other students more quickly than can those in the career advice and socio-emotional support networks. Betweenness centrality refers to the degree that a person lies between the paths connecting other persons. Individuals with high betweenness centrality scores are in a good position to function as gatekeepers or brokers. In a similar vein, on average, MPA students in the academic and friendship networks have more chances to play the intermediary role of gatekeepers or brokers. Existing literature offers two reasons to explain why MPA students’ career advice and socio-emotional support networks are much sparser than their academic and friendship networks. First, it usually takes more time to develop more personal interactions such as sharing career advice, sharing information, and seeking emotional comfort. Interpersonal interactions of this nature will not occur until a high level of trust can be cultivated after many other interactions are conducted at arms’ length (Sias & Cahill, 1998). Second, the weakest connectedness in the socio-emotional support network is consistent with other empirical findings that social and emotional support is the most difficult to find in Chinese society. A study of personal support network in Beijing concludes that Chinese are more likely to seek socio-emotional support from close family members and coworkers (Lee, Ruan, & Lai, 2005). Our findings on Chinese MPA academic and social networks also contrast with the findings for undergraduate students in the United States, who usually find social ties to be more numerous than academic ties (Smith, 2010). We expect this due to the nature of a professional graduate degree program. All the students in our study are commuting in-service professionals and studying parttime, while undergraduate students living in a residential campus have many more chances to establish extensive social ties. Whole Network Measures At the network level, we examined three structural properties of interaction patterns in MPA students’ academic and social networks: network centralization, 148 Journal of Public Affairs Education
network density, and network reciprocity (Wasserman & Faust, 1994). Table 3 provides the results of our analysis at the network level. Table 3. Network Centralization, Density, and Reciprocity Academic Network Career Advice Network Friendship Network Socio-emotional Support Network Density Out-degree Centralization Exploring Academic and Social Networks In-degree Centralization Betweenness Centralization Reciprocity 5.9% 9.3% 17.4% 10.2% 41.6% 2.6% 12.7% 8.7% 23% 29.4% 4.9% 12.4% 18.6% 21.1% 44% 1.01% 13.3% 5.1% 0.31% 20% Density is a measure of network cohesion. It is calculated by the total number of ties in a network divided by the total number of possible ties. Average density scores range from 0 (no cohesion) to 1 (complete cohesion). The higher the density score is, the greater the degree of cohesiveness or connectedness is found in the network. The statistics of density scores are also consistent with our visual inspection on network diagrams. The academic network reflects the greatest degree of connectedness among the four networks, with a density score of 5.9%. The density score of the friendship network is 1% smaller than that of the academic network. The socio-emotional support network is the least connected; only 1% of all possible ties are present. Centralization refers to how well connected the network members are collectively. Higher centralization scores indicate that a few network members hold highly central positions. Network centralization can be obtained for outdegree, in-degree, and betweenness measures. 4 The results yielded two different patterns. The in-degree centralization scores of the academic and friendship networks are greater than their out-degree centralization scores (17.4% versus 9.3% and 18.6% versus 12.4%). These scores suggest an unequal distribution of academic exchange and friendship. In the academic network, a few wellperforming students were sought by many other students to help them academically. In the friendship network, a small number of popular students were identified by many other students as their friends. In contrast, in-degree centralization scores are smaller than their out-degree centralization scores in the career advice and socio-emotional support networks (12.7% versus 18.7% and 13.3% versus 5.1%). These scores indicate that a few students reached out to many other students for career-related information and socio-emotional comfort. When it comes to the betweenness centralization, the career advice network stands out as having the highest score (23%), followed by the friendship network Journal of Public Affairs Education 149
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JPAE VOLUME 18 NUMBER 1 JOURNAL OF
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Journal of Public Affairs Education
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FROM THE EDITOR In the symposium in
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NASPAA Presidential Address Annual
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Leading by Example: Modeling Global
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FROM THE GUEST EDITOR FROM THE GUES
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FROM THE GUEST EDITOR A SYMPOSIUM I
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on other fronts, certainly it can h
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Picasso, P. (1937). Guernica. Pictu
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A View from the 50th Street Gate on
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Reflections of a Working-Class Acad
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Reflections of a Working Class Acad
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Reflections of a Working Class Acad
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Class Rooms Kenneth Oldfield Univer
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Class Rooms although I did, but not
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Class Rooms GRADUATE SCHOOL I was u
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Class Rooms the odds this appointee
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Class Rooms The Great Leveler, too
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Class Rooms of higher learning and
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ook (Oldfield & Johnson, 2009). The
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Didactic Changes Class Rooms Pedago
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Admittedly, it will be difficult to
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hooks, b. (2000). Where we stand: C
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Shaw, G. B. (1928). The intelligent
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What’s a Girl Like You Doing in a
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What’s a Girl Like You For exampl
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What’s a Girl Like You and operat
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What’s a Girl Like You captured t
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What’s a Girl Like You full-blown
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What’s a Girl Like You inside). I
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What’s a Girl Like You and collea
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What’s a Girl Like You toward ser
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Blue-Collar Teaching in a White-Col
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Blue-Collar Teaching Half of my fam
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Blue-Collar Teaching from physics.
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Blue-Collar Teaching lifelong dream
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Blue-Collar Teaching Before him, in
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Blue-Collar Teaching One may argue
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Blue-Collar Teaching graduation in
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Blue-Collar Teaching advantages oth
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Carrizales, T. (2010). Exploring cu
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Oldfield, K. (2010). Socioeconomic
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Moving Forward by Looking Back Gary
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Moving Forward My father married my
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Moving Forward became apparent that
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Moving Forward to Duane, because he
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Moving Forward by this contaminant.
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Page 111 and 112: REFERENCES Ashwander v. Tennessee V
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Page 141 and 142: Snee, R. D. (1993). What’s missin
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Stories from Local Public Managers
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Creating Quality Online Course Desi
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it was achieved. The assessment of
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Fulbright Program for Foreign Stude
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Review of Moral Controversies in Am
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application of those foundations to
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Journal of Public Affairs Education
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