In June 2012, student activists in Nepal declared a campaign against private, for-profit colleges with foreign names, simultaneously decrying the schools’ names and their exorbitant tuition fees. During the campaign, members of multiple student unions vandalized signboards, buildings, computers, and buses belonging to various colleges and filed a court case demanding stricter management of private schools. These activists claimed control of the linguistic landscape of Kathmandu, objecting not to English in the classroom but to the material emblems of branded educational institutions. This article explores the semiotic implications of this movement through analysis of newspaper coverage of the protests. The school names and talk about appropriate names delineate two competing cultural chronotopes that students employed to promote a particular vision of proper Nepali behavior and to contest what they depicted as inappropriate commodification of higher education.

Given a set of items (predictors) suppose one wishes to predict another set of items (predictands) in asimultaneous way. Such a situation may occur when the predictands are different measurable aspects of the same phenomenon. Alternatively one might wish to predict the success of an event (say a successfully performed task) which has many correlated or uncorrelated failure modes (say a set of possible mental or physical disabilities each of them by itself precluding the achievement of the said task.) In such a case a unidimensional prediction is of value only if prediction is simultaneous for all possible failure modes. A linear summarization of the predictors is suggested, which is unique and has “maximum” predictability value for all predictands simultaneously. Other summarizations or scores are found that give “maximum” explanation of residual measures on the predictands and that are uncorrelated. The set of those simultaneous linear predictions is compared to the set of the individual multiple regression predictions as used, for instance, in the same context by Horst [4] for each predictand given the original predictors. We suggest that this technique can be applied in particular to the summarization of a subset of items when the whole set of items constitutes the set of predictands.

The most probable distribution method is applied to derive the logistic model as the distribution accounting for the maximum number of possible outcomes in a dichotomous test while introducing latent traits and item characteristics as constraints to the system. The item response theory logistic models, with a particular focus on the one-parameter logistic model, or Rasch model, and their properties and assumptions, are discussed for both infinite and finite populations.

A ‘functional’ approach to constitutional interpretation is well-accepted in many other jurisdictions, including the United States, and offers a promising middle path between the extremes of pure formalism and pragmatism. It is, however, under-developed as an approach to constitutional interpretation, rather than doctrine, in Australia. The article offers an exploration of what it would mean to adopt a more explicitly functionalist approach to the interpretation of the Constitution, drawing on constitutional cases decided by the High Court in 2014.

We experimentally study how mutual payoff information affects strategic play. Subjects play the Prisoner's Dilemma or Stag Hunt game against randomly re-matched opponents under two information treatments. In our partial-information treatment, subjects are shown only their own payoff structure, while in our full-information treatment they are shown both their own and their opponent's payoff structure. In both treatments, they receive feedback on their opponent's action after each round. We find that mutual payoff information initially facilitates reaching the socially optimal outcome in both games. Play in the Prisoner's Dilemma converges toward the unique Nash equilibrium of the game under both information treatments, while in the Stag Hunt mutual payoff information has a substantial impact on play and equilibrium selection in all rounds of the game. Belief-learning model estimations and simulations suggest these effects are driven by both initial play and the way subjects learn.

Component loss functions (CLFs) are used to generalize the quartimax criterion for orthogonal rotation in factor analysis. These replace the fourth powers of the factor loadings by an arbitrary function of the second powers. Criteria of this form were introduced by a number of authors, primarily Katz and Rohlf (1974) and Rozeboom (1991), but there has been essentially no follow-up to this work. A method so simple, natural, and general deserves to be investigated more completely. A number of theoretical results are derived including the fact that any method using a concave CLF will recover perfect simple structure whenever it exists, and there are methods that will recover Thurstone simple structure whenever it exists. Specific CLFs are identified and it is shown how to compare these using standardized plots. Numerical examples are used to illustrate and compare CLF and other methods. Sorted absolute loading plots are introduced to aid in comparing results and setting parameters for methods that require them.

Let x denote one of the variables in a factor analysis model. In 1935 Roff proved that the communality of x is greater than or equal to the squared multiple correlation coefficient of x with the other variables in the model. In this paper it is shown that the inequality is the first of an infinite sequence of inequalities, each sharper than the one before, and that the condition for equality is the same for all members of the sequence. Also, the limiting inequality is considered and the condition for equality derived. As this condition is always satisfied in a factor analysis model, the inequality is really an identity.

Missing values at the end of a test typically are the result of test takers running out of time and can as such be understood by studying test takers’ working speed. As testing moves to computer-based assessment, response times become available allowing to simulatenously model speed and ability. Integrating research on response time modeling with research on modeling missing responses, we propose using response times to model missing values due to time limits. We identify similarities between approaches used to account for not-reached items (Rose et al. in ETS Res Rep Ser 2010:i–53, 2010) and the speed-accuracy (SA) model for joint modeling of effective speed and effective ability as proposed by van der Linden (Psychometrika 72(3):287–308, 2007). In a simulation, we show (a) that the SA model can recover parameters in the presence of missing values due to time limits and (b) that the response time model, using item-level timing information rather than a count of not-reached items, results in person parameter estimates that differ from missing data IRT models applied to not-reached items. We propose using the SA model to model the missing data process and to use both, ability and speed, to describe the performance of test takers. We illustrate the application of the model in an empirical analysis.

A method is presented for collecting data which will yield a scale on which the entities are ranked in preference (ordinality), the distances between the entities on the scale are ranked (ordered metric), and all combinations of the distances are ranked (higher-ordered metric). The sources drawn upon are von Neumann and Morgenstern (9), and lattice theory. An empirical example is given in which a higher-ordered metric scale is derived.

This paper investigates risk preferences using an artefactual field experiment conducted with a non-standard subject pool of farmers in Ghana. I introduce an alternative methodology for studying preferences following replication of a seminal risk elicitation procedure by Binswanger (Am J Agric Econ 62(3):395407, 1980). An important feature of both approaches is that they are easy to understand and, hence, are particularly suitable for eliciting preferences among subjects with low levels of formal education. I successfully replicate Binswanger's study, documenting how his original result of the moderate level of risk aversion for an average farmer can be generalized to a different country. However, using my alternative approach, whereby lotteries are presented in the loss domain, I find that half of my experimental subjects violated expected utility theory. This approach is of relevance to the current literature on studying risk preferences among subjects with poor literacy skills.

A technique is presented that differs from the previous one in that the use of variance terms is eliminated from the computations; thus some formulas are simplified. A rationale for the improved method is presented.

Effort has been devoted to account for heteroscedasticity with respect to observed or latent moderator variables in item or test scores. For instance, in the multi-group generalized linear latent trait model, it could be tested whether the observed (polychoric) covariance matrix differs across the levels of an observed moderator variable. In the case that heteroscedasticity arises across the latent trait itself, existing models commonly distinguish between heteroscedastic residuals and a skewed trait distribution. These models have valuable applications in intelligence, personality and psychopathology research. However, existing approaches are only limited to continuous and polytomous data, while dichotomous data are common in intelligence and psychopathology research. Therefore, in present paper, a heteroscedastic latent trait model is presented for dichotomous data. The model is studied in a simulation study, and applied to data pertaining alcohol use and cognitive ability.