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This exploratory paper discusses the undemocratic agenda setting of elites in Britain and how it has changed politics within a form of capitalism where much is left undisclosed in terms of mechanism and methods. It argues for a more radical exploratory strategy using C. Wright Mills’ understanding that what is left undisclosed is crucially important to elite existence and power, while recognising the limits on democratic accountability when debate, decision and action in complex capitalist societies can be frustrated or hijacked by small groups. Have British business elites, through their relation with political elites, used their power to constrain democratic citizenship? Our hypothesis is that the power of business elites is most likely conjuncturally specific and geographically bounded with distinct national differences. In the United Kingdom, the outcomes are often contingent and unstable as business elites try to manage democracy; moreover, the composition and organisation of business elites have changed through successive conjunctures.

The author explores questions of authenticity in the media industry by showing how right-wing media figures look to present their views as authentic by defining themselves as citizen journalists and positioning themselves in opposition to mainstream media. Looking at two case studies from the United States, Andrew Breitbart and Mike Cernovich, the author shows how the language of citizen journalism (amateurism, independence, immediacy) is co-opted by such figures to appeal to increasingly distrustful and antagonistic conservative media audiences.

Typical undergraduate research programs involving HBCU students have several weaknesses including the short time of the students’ involvement in the research and the variable level of commitment of faculty mentors. Another issue at HBCUs is the lack of both start-up support for new faculty and external research support, which limits the quality of research projects and the pool of faculty mentors. We designed our NSF-funded undergraduate research program to be a professional development program to help faculty expand their research program and improve their mentoring skills, while at the same time involving undergraduates in research.

Faculty in STEM departments competed for Student Support Grants that provided support for research-related equipment, supplies, travel, and up to two students for one year. Faculty submitted proposals describing their research project, the role of students in the project, and their student mentoring plan. Faculty mentors could recruit their own students for the project, and both faculty mentors and students were required to commit to the research project for one year.

Outcomes of the program were very positive for both the faculty and the students. All of the involved students presented their research at conferences and several were co-authors on research publications. All but a few of the students continued working in research even after their time in the program was over. In addition, many of the supported faculty members were able to use the financial support as a springboard for successful applications for other grant programs.

This paper introduces a behavioral framework to model residential relocation decision in island areas, at which the decision in question is influenced by the characteristics of island regions, policy variables related to accessibility measures, and housing prices at the proposed island area, as well as personal, household (HH), job, and latent characteristics of the decision makers.

The model framework corresponds to an integrated choice and latent variable (ICLV) setting where the discrete choice model includes latent variables that capture attitudes and perceptions of the decision makers. The latent variable model is composed of a group of structural equations describing the latent variables as a function of observable exogenous variables and a group of measurement equations, linking the latent variables to observable indicators.

An empirical study has been developed for the Greek Aegean island area. Data were collected from 900 HHs in Greece contacted via telephone. The HHs were presented hypothetical scenarios involving policy variables, where 2010 was the reference year. ICLV binary logit (BL) and mixed binary logit (MBL) relocation choice models were estimated sequentially. Findings suggest that MBL models are superior to BL models, while both the policy and the latent variables significantly affect the relocation decision and improve considerably the models' goodness of fit. Sample enumeration method is finally used to aggregate the results over the Greek population.

This paper deals with choice set generation for the estimation of route choice models. Two different frameworks are presented in the literature: one aims at generating consideration sets and one samples alternatives from the set of all paths. Most algorithms are designed to generate consideration sets but fail in general to do so because some observed paths are not generated. In the sampling approach, the observed path as well as all considered paths is in the choice set by design. However, few algorithms can be actually used in the sampling context.

In this paper, we present the two frameworks, with an emphasis on the sampling approach, and discuss the applicability of existing algorithms to each of the frameworks.

University rankings and metrics have become an increasingly prominent basis of student decisions, generalized university reputation, and the resources university’s attract. We review the history of metrics in higher education and scholarship about the influence of ranking on the position and strategic behavior of universities and students. Most quantitative analyses on this topic estimate the influence of change in university rank on performance. These studies consistently identify a small, short-lived influence of rank shift on selectivity (e.g., one rank position corresponds to ≤1% more student applicants), comparable to ranking effects documented in other domains. This understates the larger system-level impact of metrification on universities, students, and the professions that surround them. We explore one system-level transformation likely influenced by the rise of rankings. Recent years have witnessed the rise of enrollment management and independent educational consultation. We illustrate a plausible pathway from ranking to this transformation: In an effort to improve rankings, universities solicit more applications from students to reduce their acceptance rate. Lower acceptance rates lead to more uncertainty for students about acceptance, leading them to apply to more schools, which decreases the probability that accepted students will attend. This leads to greater uncertainty about enrollment for students and universities and generates demand for new services to manage it. Because these and other system-level transformations are not as cleanly measured as rank position and performance, they have not received the same treatment or modeling attention in higher education scholarship, despite their importance for understanding and influencing education policy.