In the situation where subjects independently rank order a fixed set of items, the idea of a consensus ordering of the items is defined and employed as a parameter in a class of probability models for rankings. In the context of such models, which generalize those of Mallows, posterior probabilities may be easily formed about the population consensus ordering. An example of rankings obtained by the Graduate Record Examination Board is presented to demonstrate the adequacy of these generalized Mallows' models for describing actual data sets of rankings and to illustrate convenient summaries of the posterior probabilities for the consensus ordering.

This paper addresses methodological issues that concern the scaling model used in the international comparison of student attainment in the Programme for International Student Attainment (PISA), specifically with reference to whether PISA’s ranking of countries is confounded by model misfit and differential item functioning (DIF). To determine this, we reanalyzed the publicly accessible data on reading skills from the 2006 PISA survey. We also examined whether the ranking of countries is robust in relation to the errors of the scaling model. This was done by studying invariance across subscales, and by comparing ranks based on the scaling model and ranks based on models where some of the flaws of PISA’s scaling model are taken into account. Our analyses provide strong evidence of misfit of the PISA scaling model and very strong evidence of DIF. These findings do not support the claims that the country rankings reported by PISA are robust.

This paper presents a bimatrix structure for examining ordinal partial rankings. A set of axioms is given similar to those of Kemeny and Snell (1962) and Bogart (1973), which uniquely determines the distance between any pair of such rankings. The l1 norm is shown to satisfy this set of axioms, and to be equivalent to the Kemeny and Snell distance on their subspace of weak orderings. Consensus formation is discussed.

This paper discusses the issue of differential item functioning (DIF) in international surveys. DIF is likely to occur in international surveys. What is needed is a statistical approach that takes DIF into account, while at the same time allowing for meaningful comparisons between countries. Some existing approaches are discussed and an alternative is provided. The core of this alternative approach is to define the construct as a large set of items, and to report in terms of summary statistics. Since the data are incomplete, measurement models are used to complete the incomplete data. For that purpose, different models can be used across countries. The method is illustrated with PISA’s reading literacy data. The results indicate that this approach fits the data better than the current PISA methodology; however, the league tables are nearly identical. The implications for monitoring changes over time are discussed.

This study aims to explore the dependencies on the cryptocurrency market using social network tools. We focus on the correlations observed in the cryptocurrency returns. Based on the sample of cryptocurrencies listed between January 2015 and December 2022 we examine which cryptos are central to the overall market and how often major players change. Static network analysis based on the whole sample shows that the network consists of several communities strongly connected and central, as well as a few that are disconnected and peripheral. Such a structure of the network implies high systemic risk. The day-by-day snapshots show that the network evolves rapidly. We construct the ranking of major cryptos based on centrality measures utilizing the TOPSIS method. We find that when single measures are considered, Bitcoin seems to have lost its first-mover advantage in late 2016. However, in the overall ranking, it still appears among the top positions. The collapse of any of the cryptocurrencies from the top of the rankings poses a serious threat to the entire market.

Expert and peer reviews and popularity are freely available both on the Internet and in printed materials for a variety of food products. Using two experimental studies with non-hypothetical tastings and auctions, we explore the impact of peer tasting popularity, actual peer ratings, and expert ratings on demand for wines consumers can or have tasted. We find that higher own wine ratings are associated with higher willingness to pay (WTP). Morevoer, higher peer and expert rating scores increase consumer WTP for wine even after controlling for the impact of consumers’ own ratings. Observed peer popularity also increases WTP for preferred wines.

This article reports a series of studies of judgments of satisfaction with salary, manipulating the distribution of salaries of others doing the same work. The experiments were designed to compare 6 theories of contextual effects in judgment, including adaptation-level theory, correlation–regression theory, inferred distribution (ID) theory, decision by sampling (DbS), ensemble (EN) theory, and range–frequency (RF) theory. Manipulations of the frequency distribution using cubic density functions produce a double crossover of curves relating judgments to salaries; this double crossover violates implications of 4 of the theories but remains consistent with DbS and RF theories. ID theory assumes that rank is inferred from the mean and endpoints, so it fails to describe the double crossover. Manipulations of the endpoints produce changes in the heights and slopes of the curves, which are not explained by DbS and are partially inconsistent with EN theory. EN theory implies no effect of the rank of a salary and assumes that endpoints only affect judgments of salaries on the same side of the mean, contrary to the results. RF theory implies that ratings of stimuli holding the same ranks in 2 contexts with differing endpoints should be linearly related, and the data appeared consistent with this implication. RF theory is the only theory that gives a consistent account of all of the results. RF theory can be extended in order to estimate the effective context, which appears to differ systematically between people according to their full-time incomes.

In six studies, we find evidence for an upward mobility bias, or a tendency to predict that a rise in ranking is more likely than a decline, even in domains where motivation or intention to rise play no role. Although people cannot willfully change their height (Study 1), and geographical entities cannot willfully alter their temperature (Study 2), number of natural disasters (Study 3), levels of precipitation (Studies 4A and 4B), or chemical concentration (Study 5), subjects believed that each is more likely to rise than drop in ranking. This bias is due to an association between a ranking’s order and the direction of absolute change, and to the tendency to give considerable weight to a focal agent over non-focal agents. Because people generally expect change to be represented in terms of higher ranks, and because they tend to focus on specific, focal targets, they believe that any given target will experience a larger relative increase than other targets. We discuss implications for social policy.

The classic preference reversal phenomenon, where monetary evaluations contradict risky choices, has been argued to arise due to a focus on outcomes during the evaluation of alternatives, leading to overpricing of long-shot options. Such an explanation makes the implicit assumption that attentional shifts drive the phenomenon. We conducted an eye-tracking study to causally test this hypothesis by comparing a treatment based on cardinal, monetary evaluations with a different treatment avoiding a monetary frame. We find a significant treatment effect in the form of a shift in attention toward outcomes (relative to probabilities) when evaluations are monetary. Our evidence suggests that attentional shifts resulting from the monetary frame of evaluations are a driver of preference reversals.

The results of song contests offer a unique opportunity to analyze possible distortions arising from various biases in performance evaluations using observational data. In this study we investigate the influence of contestants’ order of appearance on their ranking. We found that, in the New Wave Song Contest, expert judgments were significantly influenced by the contestant’s running number, an exogenous factor that, being assigned randomly, clearly did not influence the output quality. We also found weaker statistical evidence of such an ordering effect in Eurovision Song Contest finals of 2009–2012.

We discuss a bi-objective two-stage assignment problem (BiTSAP) that aims at minimizing two objective functions: one comprising a nonlinear cost function defined explicitly in terms of assignment variables and the other a total completion time. A two-stage assignment problem deals with the optimal allocation of n jobs to n agents in two stages, where $n_1$ out of n jobs are primary jobs which constitute Stage-1 and the rest of the jobs are secondary jobs constituting Stage-2. The paper proposes an algorithm that seeks an optimal solution for a BiTSAP in terms of various efficient time-cost pairs. An algorithm for ranking all feasible assignments of a two-stage assignment problem in order of increasing total completion time is also presented. Theoretical justification and numerical illustrations are included to support the proposed algorithms.

We use comparable 2005 and 2018 population data to assess threats driving the decline of lion Panthera leo populations, and review information on threats structured by problem tree and root cause analysis. We define 11 threats and rank their severity and prevalence. Two threats emerged as affecting both the number of lion populations and numbers within them: livestock depredation leading to retaliatory killing of lions, and bushmeat poaching leading to prey depletion. Our data do not allow determination of whether any specific threat drives declines faster than others. Of 20 local extirpations, most were associated with armed conflicts as a driver of proximate threats. We discuss the prevalence and severity of proximate threats and their drivers, to identify priorities for more effective conservation of lions, other carnivores and their prey.

Human rights advocates continue to use shaming as a central tool despite recognizing its declining effectiveness. Shame is indeed a potent motivator, but its effects are often counterproductive for this purpose. Especially when wielded by cultural outsiders in ways that appear to condemn local social practices, shaming is likely to produce anger, resistance, backlash, and deviance from outgroup norms, or denial and evasion. Shaming can easily be interpreted as a show of contempt, which risks triggering fears for the autonomy and security of the group. In these circumstances, established religious and elite networks can employ traditional normative counter-narratives to recruit a popular base for resistance. If this counter-mobilization becomes entrenched in mass social movements, popular ideology, and enduring institutions, the unintended consequences of shaming may leave human rights advocates farther from their goal.