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Author's abstract: The public school curriculum has devolved into merely being a political football for the forces of the dominant culture, no longer even attempting to serve the People of the community or the students that the school ostensibly should serve. In the absence of a curriculum that is meaningful to People, another curriculum has spontaneously appeared outside of school via shared online media between social networks. This new curriculum, identified by a relatively wide viewership and its challenge to social injustice, oppressive conventions or hegemonic forces, is a curriculum of viral videos shared because of their meaning and cogence in the moment. This inquiry examines a number of these videos through a modified method of Critical Discourse Analysis that utilizes aesthetic analysis as its primary lens to attempt to determine meaning.

In this paper I introduce new results on economies of scale and scope and develop implications of these results for contestability and regulation. This is done using a goal programming approach which endogenizes regulatory frameworks in a multiperiod and multiregion monopolistic and oligopolistic analysis. This explicitly spatial approach leads to useful distinctions between industrial contestability and market contestability and a multiperiod contestability‐based regulatory model. That model is then extended to a state preference framework with regulatory risk and windfall gains and losses.

AbstractMultivariate designs have been useful in testing models with more than one output variable. This paper explains the use of the step‐down F statistic, a technique that allows a more refined analysis than does the traditional multivariate or univariate F test by examining sequential interactions among dependent variables in a multiple‐response set. An illustration is presented within the context of a laboratory experiment designed to examine a manipulation effect on a three‐variable causal chain. The example illustrates the misleading interpretation that could result without the information provided by the step‐down statistic.