RACE AND EMPLOYMENT OUTCOMES: EVIDENCE FROM NBA COACHES

We study the impact of management diversity on employment outcomes using data on NBA head coaches that includes information on the race of each coach and his supervisor. We find that a supervisor is more likely to hire a coach of his own race. We also find that black coaches are less likely to be rehired to a second job within three years than their white counterparts, and that a head coach's race affects the quality of the opportunities he is offered. These findings are stronger for first-time coaches than experienced coaches, suggesting that observable information on performance mitigates bias. (JEL J0, J4, J7)     

A history of the mid-south sociological association

Abstract

Prior to his death in 2018, Marc Matre, Archivist and the longest serving Secretary-Treasurer of the Mid-South Sociological Association (MSSA), submitted a paper to the journal on the history of the MSSA. Reviewers wanted revisions that Marc was unable to complete because of his infirmity, and his last professional wish was that the journal and members of the association finish the work he had started. The following is that revision. It is the combined work of many who contributed to the project as noted in the acknowledgments. Biographical information about Marc follows the list of the principal founders of the association.     

Time‐change models for asymmetric processes

Many records in environmental sciences exhibit asymmetric trajectories. The physical mechanisms behind these records may lead for example to sample paths with different characteristics at high and low levels (up–down asymmetries) or in the ascending and descending phases leading to time irreversibility (front–back asymmetries). Such features are important for many applications, and there is a need for simple and tractable models that can reproduce them. In this paper, we explore original time‐change models where the clock is a stochastic process that depends on the observed trajectory. The ergodicity of the proposed model is established under general conditions, and this result is used to develop nonparametric estimation procedures based on the joint distribution of the process and its derivative. The methodology is illustrated on meteorological and oceanographic data sets. We show that, combined with a marginal transformation, the proposed methodology is able to reproduce important characteristics of the data set such as marginal distributions, up‐crossing intensity, and up–down and front–back asymmetries.     

On tree representations of relations and graphs: symbolic ultrametrics and cograph edge decompositions

Tree representations of (sets of) symmetric binary relations, or equivalently edge-colored undirected graphs, are of central interest, e.g. in phylogenomics. In this context symbolic ultrametrics play a crucial role. Symbolic ultrametrics define an edge-colored complete graph that allows to represent the topology of this graph as a vertex-colored tree. Here, we are interested in the structure and the complexity of certain combinatorial problems resulting from considerations based on symbolic ultrametrics, and on algorithms to solve them.This includes, the characterization of symbolic ultrametrics that additionally distinguishes between edges and non-edges of arbitrary edge-colored graphs G and thus, yielding a tree representation of G, by means of so-called cographs. Moreover, we address the problem of finding “closest” symbolic ultrametrics and show the NP-completeness of the three problems: symbolic ultrametric editing, completion and deletion. Finally, as not all graphs are cographs, and hence, do not have a tree representation, we ask, furthermore, what is the minimum number of cotrees needed to represent the topology of an arbitrary non-cograph G. This is equivalent to find an optimal cograph edge k-decomposition \(\{E_1,\dots ,E_k\}\) of E so that each subgraph \((V,E_i)\) of G is a cograph. We investigate this problem in full detail, resulting in several new open problems, and NP-hardness results.For all optimization problems proven to be NP-hard we will provide integer linear program formulations to solve them.     

Capturing hearts and minds: The influence of relational identification with the leader on followers' mobilization and cardiovascular reactivity

The influence of relational identification (RI) on leadership processes and the effects of social identity leadership on followers' responses to stress have received scant theoretical and research attention. The present research advances theoretical understanding by testing the assertion that high RI with the leader drives follower mobilization of effort and psychophysiological responses to stress. Two experimental scenario studies (Study 1 and Study 2) support the hypothesis that being led by an individual with whom followers perceive high RI increases follower intentional mobilization. Study 2 additionally showed that high (vs. low) RI increases follower resource appraisals and cognitive task performance. A laboratory experiment (Study 3) assessing cardiovascular (CV) reactivity showed that, compared to neutral (i.e., non-affiliated) leadership, being led by an individual with whom participants felt low RI elicited a maladaptive (i.e., threat) response to a pressurized task. In addition, relative to the low RI and neutral conditions, high RI with the leader did not engender greater challenge or threat reactivity. In conclusion, advancing social identity leadership and challenge and threat theory, findings suggest that leaders should be mindful of the deleterious effects (i.e., reduced mobilization and greater threat state) of low RI to optimize follower mobilization of effort and psychophysiological responses to stress.     

Best Practices for Presentation of E-journal Titles on Provider Web Sites and in Other E-content Products

As a result of inaccurate displays of journal metadata in e-content access tools and on Web sites, researchers and readers do not find the content they are seeking, and the full value of e-content services is not realized. A group will be formed later this year to develop a set of NISO best practices for presentation of e-journal titles, provision of correct ISSN information, and other basic bibliographic data on provider Web sites and in other e-content products.     

Group betweenness and co-betweenness: Inter-related notions of coalition centrality

Vertex betweenness centrality is a metric that seeks to quantify a sense of the importance of a vertex in a network in terms of its ‘control’ on the flow of information along geodesic paths throughout the network. Two natural ways to extend vertex betweenness centrality to sets of vertices are (i) in terms of geodesic paths that pass through at least one of the vertices in the set, and (ii) in terms of geodesic paths that pass through all vertices in the set. The former was introduced by Everett and Borgatti [Everett, M., Borgatti, S., 1999. The centrality of groups and classes. Journal of Mathematical Sociology 23 (3), 181–201], and called group betweenness centrality. The latter, which we call co-betweenness centrality here, has not been considered formally in the literature until now, to the best of our knowledge. In this paper, we show that these two notions of centrality are in fact intimately related and, furthermore, that this relationship may be exploited to obtain deeper insight into both. In particular, we provide an expansion for group betweenness in terms of increasingly higher orders of co-betweenness, in a manner analogous to the Taylor series expansion of a mathematical function in calculus. We then demonstrate the utility of this expansion by using it to construct analytic lower and upper bounds for group betweenness that involve only simple combinations of (i) the betweenness of individual vertices in the group, and (ii) the co-betweenness of pairs of these vertices. Accordingly, we argue that the latter quantity, i.e., pairwise co-betweenness, is itself a fundamental quantity of some independent interest, and we present a computationally efficient algorithm for its calculation, which extends the algorithm of Brandes [Brandes, U., 2001. A faster algorithm for betweenness centrality. Journal of Mathematical Sociology 25, 163] in a natural manner. Applications are provided throughout, using a handful of different communication networks, which serve to illustrate the way in which our mathematical contributions allow for insight to be gained into the interaction of network structure, coalitions, and information flow in social networks.