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Shallow meritocracy
(2023)
Meritocracies aspire to reward hard work and promise not to judge individuals by the circumstances into which they were born. However, circumstances often shape the choice to work hard. I show that people's merit judgments are "shallow" and insensitive to this effect. They hold others responsible for their choices, even if these choices have been shaped by unequal circumstances. In an experiment, US participants judge how much money workers deserve for the effort they exert. Unequal circumstances disadvantage some workers and discourage them from working hard. Nonetheless, participants reward the effort of disadvantaged and advantaged workers identically, regardless of the circumstances under which choices are made. For some participants, this reflects their fundamental view regarding fair rewards. For others, the neglect results from the uncertain counterfactual. They understand that circumstances shape choices but do not correct for this because the counterfactual—what would have happened under equal circumstances—remains uncertain.
From 1963 through 2015, idiosyncratic risk (IR) is high when market risk (MR) is high. We show that the positive relation between IR and MR is highly stable through time and is robust across exchanges, firm size, liquidity, and market-to-book groupings. Though stock liquidity affects the strength of the relation, the relation is strong for the most liquid stocks. The relation has roots in fundamentals as higher market risk predicts greater idiosyncratic earnings volatility and as firm characteristics related to the ability of firms to adjust to higher uncertainty help explain the strength of the relation. Consistent with the view that growth options provide a hedge against macroeconomic uncertainty, we find evidence that the relation is weaker for firms with more growth options.
Uncertainty is a central theme in the illness experiences of older cancer patients throughout their illness trajectory. Mishel’s popular theory on uncertainty during illness approaches uncertainty as an outcome and is characterized by the patient’s inability to find meaning in illness events. This study used the concepts of liminality and subjunctivity to explore uncertainty throughout the illness trajectory of cancer patients. We interviewed 18 older (age range = 57–92 years) patients with breast cancer or gastro-intestinal cancer 3 to 4 years post diagnosis. Our analysis is based on the QUAGOL guide that draws on elements of grounded theory such as constant comparison. We found that liminality and subjunctivity provide a useful frame for understanding uncertainty with a specific focus on its productive potential and meaning making. Health care professionals should be open to acquiring a complete picture of patients’ diverse and dynamic experiences of uncertainty in the different stages of their illness trajectory.
The Earth's future depends on how we manage the manifold risks of climate change (CC). It is state-of-the-art to assume that risk reduction requires participatory management involving a broad range of stakeholders and scientists. However, there is still little knowledge about the optimal design of participatory climate change risk management processes (PRMPs), in particular with respect to considering the multitude of substantial uncertainties that are relevant for PRMPs. To support the many local to regional PRMPs that are necessary for a successful global-scale reduction of CC risks, we present a roadmap for designing such transdisciplinary knowledge integration processes. The roadmap suggests ways in which uncertainties can be comprehensively addressed within a PRMP. We discuss the concept of CC risks and their management and propose an uncertainty framework that distinguishes epistemic, ontological, and linguistic uncertainty as well as ambiguity. Uncertainties relevant for CC risk management are identified. Communicative and modeling methods that support social learning as well as the development of risk management strategies are proposed for each of six phases of a PRMP. Finally, we recommend how to evaluate PRMPs as such evaluations and their publication are paramount for achieving a reduction of CC risks.
This paper challenges widespread assumptions in trust research according to which trust and conflict are opposing terms or where trust is generally seen as a value. Rather, it argues that trust is only valuable if properly justified, and it places such justifications in contexts of social and political conflict. For these purposes, the paper suggests a distinction between a general concept and various conceptions of trust, and it defines the concept as a four-place one. With regard to the justification of trust, a distinction between internal and full justification is introduced, and the justification of trust is linked to relations of justification between trusters and trusted. Finally, trust in conflict(s) emerges were such relations exist among the parties of a conflict, often by way of institutional mediation.
The use of most if not all technologies is accompanied by negative side effects, While we may profit from today’s technologies, it is most often future generations who bear most risks. Risk analysis therefore becomes a delicate issue, because future risks often cannot be assigned a meaningful occurance probability. This paper argues that technology assessement most often deal with uncertainty and ignorance rather than risk when we include future generations into our ethical, political or juridal thinking. This has serious implications as probabilistic decision approaches are not applicable anymore. I contend that a virtue ethical approach in which dianoetic virtues play a central role may supplement a welfare based ethics in order to overcome the difficulties in dealing with uncertainty and ignorance in technology assessement.
Understanding the diverging opinions of academic experts, stakeholders and the public is important for effective conservation management. This is especially so when a consensus is needed for action to minimize future risks but the knowledge upon which to base this action is uncertain or missing. How to manage non-native, invasive species (NIS) is an interesting case in point: the issue has long been controversial among stakeholders, but publicly visible, major disagreement among experts is recent. To characterize the multitude of experts’ understanding and valuation of non-native, NIS we performed structured qualitative interviews with 26 academic experts, 13 of whom were invasion biologists and 13 landscape experts. Within both groups, thinking varied widely, not only about basic concepts (e.g., non-native, invasive) but also about their valuation of effects of NIS. The divergent opinions among experts, regarding both the overall severity of the problem in Europe and its importance for ecosystem services, contrasted strongly with the apparent consensus that emerges from scientific synthesis articles and policy documents. We postulate that the observed heterogeneity of expert judgments is related to three major factors: (1) diverging conceptual understandings, (2) lack of empirical information and high scientific uncertainties due to complexities and contingencies of invasion processes, and (3) missing deliberation of values. Based on theory from science studies, we interpret the notion of an NIS as a boundary object, i.e., concepts that have a similar but not identical meaning to different groups of experts and stakeholders. This interpretative flexibility of a concept can facilitate interaction across diverse groups but bears the risk of introducing misunderstandings. An alternative to seeking consensus on exact definitions and risk assessments would be for invasive species experts to acknowledge uncertainties and engage transparently with stakeholders and the public in deliberations about conflicting opinions, taking the role of honest brokers of policy alternatives rather than of issue advocates.
A common practice in empirical macroeconomics is to examine alternative recursive orderings of the variables in structural vector autogressive (VAR) models. When the implied impulse responses look similar, the estimates are considered trustworthy. When they do not, the estimates are used to bound the true response without directly addressing the identification challenge. A leading example of this practice is the literature on the effects of uncertainty shocks on economic activity. We prove by counterexample that this practice is invalid in general, whether the data generating process is a structural VAR model or a dynamic stochastic general equilibrium model.
This special issue explores how finance deploys time, structures the future, and interacts with actors and institutions that sometimes function according to very different temporal regimes. Finance capitalism’s logic of recurrence, repetitive cycles, and successive ruptures has long been with us, but the essays in this special issue are particularly interested in how recent decades of intensified financialization have restructured temporal experience. They interrogate the production and dissemination of agency in an age of acceleration, risk, and uncertainty, asking how the temporality inscribed in financial transactions emerges from and simultaneously shapes individual and social practice. Topics covered range from the logic of finance and foundational concepts of financial theory to the intersection between objective structures and social practice, the role of literature, and finally questions of social insecurity, political action, and the possibility of resistance within a context of competing temporalities. In this introduction, the editors delineate some fundamental concepts and questions for our financial times.
Representing uncertainty in a spatial invasion model that incorporates human-mediated dispersal
(2013)
Most modes of human-mediated dispersal of invasive species are directional and vector-based. Classical spatial spread models usually depend on probabilistic dispersal kernels that emphasize distance over direction and have limited ability to depict rare but influential long-distance dispersal events. These aspects are problematic if such models are used to estimate invasion risk. Alternatively, a geographic network model may be better at estimating the typically low likelihoods associated with human-mediated dispersal events, but it should also provide a reasonable account of uncertainties that could affect perception of its risk estimates. We developed a network model that assesses the likelihood of dispersal of invasive forest pests in camper-transported firewood in North America. We built the model using data from the U.S. National Recreation Reservation Service, which document visitor travel between populated places and federal campgrounds across the U.S. and Canada. The study area is depicted as a set of coarse-resolution map units. Based on repeated simulations, the model estimates the probability that each unit is a possible origin and destination for firewood-facilitated forest pest invasions. We generated output maps that summarise, for each U.S. state and Canadian province, where (outside the state or province) a camper-transported forest pest likely originated. Treating these output maps as a set of baseline scenarios, we explored the sensitivity of these “origin risk” estimates to additive and multiplicative errors in the probabilities of pest transmission between locations, as well as random changes in the structure of the underlying travel network. We found the patterns of change in the origin risk estimates due to these alterations to be consistent across all states and provinces. This indicates that the network model behaves predictably in the presence of uncertainties, allowing future work to focus on closing knowledge gaps or more sophisticated treatments of the impact of uncertainty on model outputs.