Why do US voters allow politicians to hold the country’s economy hostage during debt ceiling negotiations? In this research note, we argue that ignorance and uncertainty over the consequences of a debt ceiling breach play a nontrivial role in public support for hard-line negotiating positions. In a pre-registered survey experiment, two weeks before the June 2023 deadline to raise the US debt ceiling, we show that providing credible information about the consequences of default increases support for concessions among both Democrats and Republicans. Further, more certain information about the consequences of a debt ceiling breach has a larger effect than less-certain information suggesting that the unpredictable consequences of the crisis also help explain voter reluctance to accept concessions. The findings have implications for understanding debt ceiling negotiations and other crisis bargaining situations where the public serves as a relevant third party.

This essay is in celebration of the contributions of Mario Rizzo. I argue that among contemporary economists in the Austrian School of Economics tradition it is Rizzo that advanced, more than his contemporaries, the scientific research program of rational choice as if the choosers were human beings; the dynamic subjectivism and the agony of choice and social interaction; the causal processes and the institutional dynamics that make up a complex social order; and the role of law, politics and civil society in shaping commercial life. In making this argument, I attempt to arbitrage the contributions of two essays of Rizzo’s: ‘Law Amid Flux’ and ‘The Genetic-Causal Tradition and Modern Economic Theory’.

We introduce stochastic loss into a gift exchange game to study how information on intentions affects reciprocity. In one treatment, the respondent observes the amount received and whether a loss occurred, so both the consequential outcome and the sender’s original intention are known. In the other two treatments, information about whether a loss occurred is hidden, and the respondent is only informed of the amount received (outcome) or the amount initially sent (intention). Using both regression-based approaches and non-parametric tests, we find greater reciprocity in the two treatments that reveal intentions. These differences arise even in a simple one-shot setting without reputational benefits and are economically meaningful; they are similar in magnitude to the difference attributable to a full point reduction in the amount received. Our findings show the impact of the information environment on reciprocity in settings with uncertainty and suggest that transparency is important to reciprocity.

When affirmative action policies target more than one disadvantaged group, they contain uncertainty as to whether an individual who belongs to one of these groups was actually favored. In a laboratory experiment, we study how this feature affects outcomes of affirmative action in the form of quotas, and compare it with two other conditions, namely affirmative action with a certain favored group and no affirmative action. We find that when a group is favored with certainty and the social identity that triggers affirmative action is made salient, affirmed individuals are wrongly perceived as less competent, both by themselves and by others. Consequently, their willingness to compete does not increase and they are selected less for teamwork post competition. Affirmative action with uncertain favored groups does not distort belief in competence, and thus does not induce such unintended consequences. In contrast, it increases competition entry of the affirmed groups and enhances their chances of being selected for teamwork.

Argon physisorption at 87 K is the new standard for texture analysis of microporous media recommended by the International Union of Pure and Applied Chemistry (IUPAC). However, geoscientists routinely use nitrogen (77 K) and carbon dioxide (273 K), both molecules with permanent polarization and the preference to interact with specific surface sites. In this work, N2, CO2, and Ar physisorption isotherms were measured and classical physisorption theories applied to investigate the suitability of Ar physisorption for the porosity assessment of mudrocks, clays, and (non)-porous analogs.

N2 and Ar physisorption isotherms are qualitatively similar with the most significant discrepancies in the submonolayer range. Textural parameters reveal linear relations but parameter ratios vary randomly, independent of the sorbent class. While N2 and CO2 (mostly) underestimate micropore volumes, nitrogen BET areas are consistently larger than argon BET areas. Those differences are probably associated with differences in polarization. But its effect on molecular orientation, for example, is presumably masked by microporosity and a narrow spacing of specific surface sites.

Mesopore size distributions and Gurvich (total) pore volumes agree well for N2 and Ar indicating similar pore size and pore volume access. Combining both parameters proves effective in identifying saturation pressure offsets which pose the largest uncertainty factor in the present study. Ar-based micropore size distributions reveal three distinct classes of mudrocks differing in organic matter maturity, and its contribution to microporosity. Empirical αs plots corroborate this classification underlining the discrepancies in the micropore range of mudrocks. Comparative hysteresis loop analysis indicated cavitation as one dominant evaporation mechanism in mudrocks and clays effecting a sample-specific compartmentalization of their pore networks.

Standard response formats such as rating or visual analogue scales require respondents to condense distributions of latent states or behaviors into a single value. Whereas this is suitable to measure central tendency, it neglects the variance of distributions. As a remedy, variability may be measured using interval-response formats, more specifically the dual-range slider (RS2). Given the lack of an appropriate item response model for the RS2, we develop the Dirichlet dual response model (DDRM), an extension of the beta response model (BRM; Noel & Dauvier in Appl Psychol Meas, 31:47–73, 2007). We evaluate the DDRM’s performance by assessing parameter recovery in a simulation study. Results indicate overall good parameter recovery, although parameters concerning interval width (which reflect variability in behavior or states) perform worse than parameters concerning central tendency. We also test the model empirically by jointly fitting the BRM and the DDRM to single-range slider (RS1) and RS2 responses for two Extraversion scales. While the DDRM has an acceptable fit, it shows some misfit regarding the RS2 interval widths. Nonetheless, the model indicates substantial differences between respondents concerning variability in behavior. High correlations between person parameters of the BRM and DDRM suggest convergent validity between the RS1 and the RS2 interval location. Both the simulation and the empirical study demonstrate that the latent parameter space of the DDRM addresses an important issue of the RS2 response format, namely, the scale-inherent interdependence of interval location and interval width (i.e., intervals at the boundaries are necessarily smaller).

Offline volunteering was faced with new challenges during the COVID-19 pandemic. Using a survey experiment with 1207 student participants, we test the impact of informing subjects about blood donation urgency (shortage information), and secondly, the effect of providing information about measures taken to reduce SARS-CoV-2 transmission at blood donation centers (hygiene information), on their inclination to donate during and after the COVID-19 lockdown. The results show that shortage information increases extensive-margin willingness to donate for non-donors by 15 percentage points (pp), on average, and increases the willingness to donate quickly for all respondents. Hygiene information, however, reduces prior donors’ intention to donate again by 8pp, on average, and reduces the willingness of non-donors to donate quickly.

Parceling—using composites of observed variables as indicators for a common factor—strengthens loadings, but reduces the number of indicators. Factor indeterminacy is reduced when there are many observed variables per factor, and when loadings and factor correlations are strong. It is proven that parceling cannot reduce factor indeterminacy. In special cases where the ratio of loading to residual variance is the same for all items included in each parcel, factor indeterminacy is unaffected by parceling. Otherwise, parceling worsens factor indeterminacy. While factor indeterminacy does not affect the parameter estimates, standard errors, or fit indices associated with a factor model, it does create uncertainty, which endangers valid inference.

What is epistemically required of the rationally hopeful? In this paper, I propose that, as a subject becomes hopeful that p, she also adopts an inquiring attitude toward the question of whether p. Moreover, remaining rationally hopeful requires maintaining an inquiring attitude toward those possibilities we are hopeful about. On top of being led by a particular practical goal (that of attaining p), I suggest that the hopeful agent is also led by the epistemic goal of knowing whether p. Adding the “inquiry” criteria to rational hopefulness helps explain our intuition that there is something wrong with being hopeful that p and not disposed to inquire into whether p. It also helps us further distinguish hopefulness from other positive attitudes we adopt in the face of uncertainty, such as optimism, and faith.

Recently, scholars have advanced an ideal of the entrepreneurial state in which industrial policy is pursued in a mission-directed manner. Crucially, this perspective does not merely call for the heavier use of industrial policy, but envisions the state as a central focal point, mobilising society around the pursuit of a common mission. Using the historical example of East Asia's developmental state, which closely resembles its contemporary variant, I demonstrate that mission-directionality – should it be consistently applied – tends towards the pursuit of a singular overarching mission, and could require the use of authoritarian and disciplinary mechanisms to sustain mission focus in an environment of uncertainty. In turn, this potential risk arises because mission-directionality seeks to transcend the otherwise directionless nature of market-based and democratic decision-making through the use of bureaucratic discretion, to align the behaviour of social actors in a cohesive and directional manner.

The performance and confidence in fault detection and diagnostic systems can be undermined by data pipelines that feature multiple compounding sources of uncertainty. These issues further inhibit the deployment of data-based analytics in industry, where variable data quality and lack of confidence in model outputs are already barriers to their adoption. The methodology proposed in this paper supports trustworthy data pipeline design and leverages knowledge gained from one fully-observed data pipeline to a similar, under-observed case. The transfer of uncertainties provides insight into uncertainty drivers without repeating the computational or cost overhead of fully redesigning the pipeline. A SHAP-based human-readable explainable AI (XAI) framework was used to rank and explain the impact of each choice in a data pipeline, allowing the decoupling of positive and negative performance drivers to facilitate the successful selection of highly-performing pipelines. This empirical approach is demonstrated in bearing fault classification case studies using well-understood open-source data.

Threat perception in international relations has received much academic attention and continues to do so. Other contributions to this special section on how leaders feel security dangers or perceive threats with radical uncertainty are closely intertwined with this article’s focus on threats that are vague and not immediately perceptible. Humans possess a capacity for thinking about and imagining the future known as prospection. Faced with threatening futures, can governments prepare their civil servants to systematically manage uncertainties and anticipate dangers? Drawing on empirical data from interviews with foresight practitioners in the United Kingdom and Singapore, this article examines how governments are nudging civil servants to deploy futures techniques as part of threat perception.