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.

As a case study in the proliferation of global rankings, we examine the initiation, construction of, and response to the Access to Medicine Index, which ranks pharmaceutical companies according to their respective contribution to access to medicine for developing countries. Since it has served as the model for constructing global rankings in the fields of nutrition, seeds, mining, possibly in the future, oil, seafood, mobile internet, and agricultural commodities, and it serves as a blueprint for the development of corporate sustainability benchmarks in line with the United Nations Sustainable Development Goals, its significance goes well beyond public health. From an economic-sociological perspective we argue, first, that rankings can be conceived as symbolic classifications that serve predominantly as market-based coordination devices. To understand the proliferation of global rankings, we argue, secondly, that they are an integral part of the changing balance of power in the domain of global public health consisting of a historical shift from international organizations as the central mode of governance and coordination to a more decentralized and diversified global field structure. This global field is formed by an increasing number and variety of actors, but lacks a central decision-making body. The case of the Access to Medicine Index suggests that a historical-sociological field perspective has analytical advantages over both the micro-analysis of socio-technical devices and macro-level approaches to issues of governance in contemporary capitalism.

It may be possible for dairy farms to improve profitability and reduce environmental impacts by selecting for higher feed efficiency and lower methane (CH4) emission traits. It remains to be clarified how CH4 emission and feed efficiency traits are related to each other, which will require direct and accurate measurements of both of these traits in large numbers of animals under the conditions in which they are expected to perform. The ranking of animals for feed efficiency and CH4 emission traits can differ depending upon the type and duration of measurement used, the trait definitions and calculations used, the period in lactation examined and the production system, as well as interactions among these factors. Because the correlation values obtained between feed efficiency and CH4 emission data are likely to be biased when either or both are expressed as ratios, therefore researchers would be well advised to maintain weighted components of the ratios in the selection index. Nutrition studies indicate that selecting low emitting animals may result in reduced efficiency of cell wall digestion, that is NDF, a key ruminant characteristic in human food production. Moreover, many interacting biological factors that are not measured directly, including digestion rate, passage rate, the rumen microbiome and rumen fermentation, may influence feed efficiency and CH4 emission. Elucidating these mechanisms may improve dairy farmers ability to select for feed efficiency and reduced CH4 emission.

Recognition that alien plants pose a significant threat to biodiversity has not always translated into effective management strategies, policy reforms, and systems to establish priorities. Thus, many alien plant management decisions for the protection of biodiversity occur with limited knowledge of what needs to be protected (other than biodiversity in a generalized sense) or the urgency of actions. To rectify this, we have developed a triage system that enables alien plant management decisions to be made based on (1) the urgency of control relative to the degree of threat posed to biodiversity, compared with (2) the likelihood of achieving a successful conservation outcome as a result of alien plant control. This triage system is underpinned by a two-step approach, which identifies the biodiversity at risk and assesses sites to determine priorities for control. This triage system was initially developed to manage the threat posed by bitou bush to native species in New South Wales (NSW), Australia. It has subsequently been improved with the national assessment of lantana in Australia, and the adaptation from a single to multiple alien plant species approach on a regional scale. This triage system identifies nine levels of priority for alien plant management aimed at biodiversity conservation, ranging from immediate, targeted action to limited or no action. The development of this approach has enabled long-term management priorities to be set for widespread alien plants that are unlikely to be eradicated. It also enables control to occur in a coordinated manner for biodiversity conservation at a landscape scale, rather than as a series of individual unconnected short-term actions.

We developed a protocol for categorizing nonnative plants according to their negative impacts on biodiversity in a large area such as a state, nation, or ecological region. Our objective was to provide a tool that makes the process of identifying, categorizing, and listing nonnative plants that cause negative impacts to biodiversity analytic, transparent, and equitable and that yields lists that are useful to researchers, land managers, regulators, consumers, and commercial interests such as the nursery industry. The protocol was designed to distinguish between species that cause high, medium, low, or insignificant negative impacts to native biodiversity within the state, region, or nation of interest. It consists of 20 multiple-choice questions grouped into four sections, which each address a major aspect of a species' total impact and when combined yield an overall “Invasive Species Impact Rank” or “I-Rank” (high, medium, low, or insignificant). The nonprofit organization NatureServe is now using this protocol to assess the estimated 3,500 nonnative vascular plant species that are established in the United States to create a national list prioritized by negative impact on biodiversity. The protocol and additional information are available on the Internet at http://www.natureserve.org/getData/plantData.jsp, and over 500 completed species assessments are available through NatureServe Explorer (http://www.natureserve.org/explorer/).

We sketch the history of spectral ranking—a general umbrella name for techniques that apply the theory of linear maps (in particular, eigenvalues and eigenvectors) to matrices that do not represent geometric transformations, but rather some kind of relationship between entities. Albeit recently made famous by the ample press coverage of Google's PageRank algorithm, spectral ranking was devised more than 60 years ago, almost exactly in the same terms, and has been studied in psychology, social sciences, bibliometrics, economy, and choice theory. We describe the contribution given by previous scholars in precise and modern mathematical terms: Along the way, we show how to express in a general way damped rankings, such as Katz's index, as dominant eigenvectors of perturbed matrices, and then use results on the Drazin inverse to go back to the dominant eigenvectors by a limit process. The result suggests a regularized definition of spectral ranking that yields for a general matrix a unique vector depending on a boundary condition.

In the social sciences, networks are used to represent relationships between social actors, be they individuals or aggregates. The structural importance of these actors is assessed in terms of centrality indices which are commonly defined as graph invariants. Many such indices have been proposed, but there is no unifying theory of centrality. Previous attempts at axiomatic characterization have been focused on particular indices, and the conceptual frameworks that have been proposed alternatively do not lend themselves to mathematical treatment.

We show that standard centrality indices, although seemingly distinct, can in fact be expressed in a common framework based on path algebras. Since, as a consequence, all of these indices preserve the neighbourhood-inclusion pre-order, the latter provides a conceptually clear criterion for the definition of centrality indices.