Default Assumption Research Articles

Skepticism and Virtue Epistemology: Wittgenstein and Sosa

Ernest Sosa has long been a leading advocate of a virtue-theoretic approach to the traditional problems of epistemology. However, in a recent book his thoughts take a striking new turn. Appealing to our epistemic competencies, he argues, will not suffice to meet the skeptical challenge to our claim to have knowledge of the world around us. We must recognize that our epistemic competencies are exercised against a background of “proper default assumptions”: commitments concerning the world and our place in it that we cannot justify but can rely on without incurring epistemic fault. Sosa finds anticipations of this idea in Wittgenstein’s appeal to propositions “hinge” propositions which, though not known, “stand fast”. However, mere fast-standing beliefs, “unhinged from any broader virtue epistemology”, cannot explain how we come to have knowledge of a world whose character is independent of what we happen to think about it. I argue that the claim that our everyday knowledge of the world rests on a body of assumptions is a serious concession to skepticism, which Wittgenstein shows we need not make. Hinge propositions are not mere “standfast” beliefs: they are known with certainty. Wittgenstein offers a way of thinking about knowledge that Sosa does not consider. He also poses a challenge to commonly held views about how epistemology, to the extent that there is such a subject, should be pursued.

Revising the null model in language evolution research.

We comment on the consequences of the target article for language evolution research. We propose that the default assumption should be that of language-readiness in extinct hominins, and the integration of different types of available evidence from multiple disciplines should be used to assess the likely extent of the realization of this readiness. The role of archaeological evidence should be reconsidered.

Round-Robin Beyond Additive Agents: Existence and Fairness of Approximate Equilibria

Fair allocation of indivisible goods has attracted extensive attention over the last two decades, yielding numerous elegant algorithmic results and producing challenging open questions. The problem becomes much harder in the presence of strategic agents. Ideally, one would want to design truthful mechanisms that produce allocations with fairness guarantees. However, in the standard setting without monetary transfers, it is generally impossible to have truthful mechanisms that provide nontrivial fairness guarantees. Recently, Amanatidis et al. [Amanatidis G, Birmpas G, Fusco F, Lazos P, Leonardi S, Reiffenhäuser R (2023) Allocating indivisible goods to strategic agents: Pure Nash equilibria and fairness. Math. Oper. Res., ePub ahead of print November 30, https://doi.org/10.1287/moor.2022.0058 ] suggested the study of mechanisms that produce fair allocations in their equilibria. Specifically, when the agents have additive valuation functions, the simple Round-Robin algorithm always has pure Nash equilibria, and the corresponding allocations are envy-free up to one good (EF1) with respect to the agents’ true valuation functions. Following this agenda, we show that this outstanding property of the Round-Robin mechanism extends much beyond the above default assumption of additivity. In particular, we prove that for agents with cancelable valuation functions (a natural class that contains, e.g., additive and budget-additive functions), this simple mechanism always has equilibria, and even its approximate equilibria correspond to approximately EF1 allocations with respect to the agents’ true valuation functions. Furthermore, we show that the approximate EF1 fairness of approximate equilibria surprisingly holds for the important class of submodular valuation functions as well, even though exact equilibria fail to exist. Funding: This work was supported by the Horizon 2020 European Research Council Advanced Grant “AMDROMA: Algorithmic and Mechanism Design Research in Online Markets” [Grant 788893], the Ministero dell’Università e della Ricerca Research project of national interest (PRIN) “ALGADIMAR: Algorithms, Games, and Digital Markets,” the Nederlandse Organisatie voor Wetenschappelijk Onderzoek Veni Project “Algorithmic Fair Division in Dynamic, Socially Constrained Environments” [Grant VI.Veni.192.153], and the National Recovery and Resilience Plan Greece 2.0 funded by the European Union under the NextGenerationEU Program [Grant MIS 5154714].

Frames of systems change in sustainability transformations: Lessons from sociotechnical systems and circular economy case studies

Tackling the world's most complex challenges requires transforming systems purposefully, which involves reflecting on the directionality of ongoing systems transformations and the design of policy mixes capable of steering systems in more desirable directions. It is argued that a framing lens helps to advance understanding of this challenge by surfacing situated and heterogeneous perspectives on systems change. Frames are knowledge structures and default assumptions that help to guide action. This paper examines the frames of ‘systems change’ in purposeful sustainability transformations. To this end, a meta-synthesis of 155 case studies of sociotechnical systems change for sustainability and circular economy was conducted. Inductively coding these cases and comparing the emergent themes, four frames of systems change for sustainability were identified, varying depending on what they deem feasible and desirable change, the mechanisms and processes of change-making, and the different actor roles in these pursuits. A process model is developed to explain how explicit attention to frames can support opening up the directionality of purposeful systems transformations in ways that inform the design and implementation of more plural policy mixes. This contributes to the literature on directionality by providing insights on the boundaries of frames for systems change and the policy mix literature by identifying ways to engage directly with key assumptions guiding change-making efforts.

“Salute the strivers”: China’s Internet giant founders and the discursive construction of overwork

Scholarly inquiry into labor issues in the digital industry has primarily centered on workers, with less attention devoted to employers, or entrepreneurs. Turning the scrutiny toward tech entrepreneurs, this article reports the results from a critical discourse analysis of how China’s Internet giant founders are participating in the construction of a long-hours culture through discourse practices. It uncovers that the default assumptions related to tech work, tech workers, and tech firms are carefully designed, taught, and cultivated by tech founders to sustain the exploitative and unsustainable mode of technical production. Situated at the historical juncture of China’s “great reversal” since late 2020, this research examines the dynamic and uneven triangular relationship among the state, entrepreneurs, and workers in technical production. It enriches the analysis of entrepreneurial discourse in the digital industry beyond the Euro-American context and reflects on entrepreneurs’ ambivalent power in late-developing nations.

‘Women stay behind and grow the food’: Agricultural productivity and the interstices of petty commodity production and reproductive labour in Tanzania

AbstractInspired by the work of Carmen Diana Deere, this paper examines how an analysis of the work of rural production, even when gendered, is compromised if it does not incorporate reproductive labour. The paper presents estimates of the gender yield gap in agricultural crop productivity in Tanzania, along with the statistical causes of the gender yield gap, in order to demonstrate what is and why it matters. The paper then shows that the gender yield gap cannot be understood without interrogating how the reproductive labour of unpaid care and domestic work limits the time for productive activities available to women who have day‐to‐day decision‐making managerial control over plots of land. In this light, the paper suggests a way of rethinking the basic analytical frameworks of agrarian political economy in ways that are consistent with and incorporate the theoretical insights of Carmen Diana Deere. The implications of the analysis are stark: it should not be assumed that all members of an agrarian household share an identical class location, as remains far too often the default assumption in agrarian political economy.

Hinge normativity

The main purpose of this article is to anchor the basic principles of judgmental performances into reality, and thus, to capture the vertical axis of cognition. To this end, it is argued that the normative force of explicit, discursive self-knowledge is neither merely grounded in dialectical inescapability nor in default assumptions. The goal is to argue that the ultimate überhinge is so perfectly known that the questions of justification, truth-value and empirical cognoscibility lose any sense in regards to it. Hinge normativity, which can be reduced neither to epistemic (telic) normativity nor to practical normativity, emerges from this view. The shortcomings of neo-Kantian views of the sources of normativity in gnoseology are exposed and analysed.

Herbicides and pesticides synergistically interact at low concentrations in complex mixtures

Assessing a complex mixture of pesticides at the impacted sites has been challenging for risk assessors for 50 years. The default assumption is that at low concentrations, pesticides interact additively with one another; thus, the risk posed by each component of a complex mixture could be simply added up. The EPA interaction-based hazard index (HIInteraction) modifies this assumption using a binary weight-of-evidence (BINWOE). However, data gaps often preclude HIInteraction use at most sites. This study evaluated these assumptions using the BINWOE to estimate the hazard index (HI) of select pesticide mixtures. The lack of in vivo binary interaction data led us to use a cell line, SH-SY5Y, to obtain the data necessary for the BINWOE approach. In the risk assessment, we considered the most active exposure scenario inhaling a mixture of volatile pesticides from contaminated soil and groundwater. The potential interactions between pesticides in 15 binary mixtures were investigated using the MTT assay in SH-SY5Y cells. Our findings showed that 60% of the binary mixtures elicited synergism (in at least one concentration), 27% displayed antagonism, and 13% showed additive effects in SH-SY5Y cells. Combining human safety data with in vitro interaction data indicated that adults and toddlers were at the highest risk when considering industrial and commercial land use, respectively, compared to other subpopulations. Incorporating interaction data into the risk assessment either increased the risk by up to 20% or decreased the risk by 2%, depending on the mixture. Our results demonstrate the predominant synergistic interactions, even at low concentrations, altered risk characterization at the complex operating site. Most concerning, organochlorine pesticides with the same mechanism of action did not follow dose additivity when evaluated by SH-SY5Y cell lines. Based on our observations, we caution that current HI methods based on additivity assumptions may underestimate the risk of organochlorine mixtures.

MIsgivings about measurement invariance

This paper critically evaluates the conventional insistence on establishing measurement invariance (MI) in cross-cultural psychology. We argue that complex and seemingly arbitrary benchmarks for assessing MI can be unrealistic and effectively prohibit meaningful research. The widespread use of various MI criteria creates unnecessary and often unattainable hurdles for cross-cultural researchers who have made the effort to collect data in multiple cultural contexts. Additionally, the prohibitionist tone of discussions surrounding MI is unhelpful, unscientific, and discouraging. We argue that emerging findings that cultural differences might not be as widespread or profound as once assumed imply that significant cross-cultural differences in measurement should not be the default assumption. Additionally, we advocate a shift towards external validity as a more useful metric of measurement quality. Our overall message is that researchers who go to the considerable trouble of gathering data in more than one country should not be disadvantaged compared to researchers who avoid cross-cultural complications by gathering data only at their home campus.

A tasty solution to packaging waste? Life cycle assessment of edible coffee cups

Edible cups have been proposed as a solution to littering and plastic pollution arising from disposal of 500 billion beverage cups each year. We applied life cycle assessment and a littering indicator to benchmark the environmental performance of edible cups against mainstream cup types made from paper, polylactic acid (PLA), polystyrene (PS) and reusable cups made from polypropylene (PP) and steel. Various end-of-life treatment scenarios were analysed. Across most impact categories, edible cups incur the largest burdens, and reusable cups the smallest (if reused at least 54 times). Under default assumptions, per cup use, climate change burdens ranged from 0.004 to 0.1 kg CO2 equivalent, eutrophication burdens ranged from 6.26 × 10–6 to 4.21 × 10–4 kg N, fossil resource depletion burdens ranged from 0.05 to 0.284 MJ and water depletion burdens ranged from 0.002 to 0.437 m3. However, if edible cups are eaten after use and substitute a similar snack then their use could incur negligible environmental impact. Furthermore, edible cups demonstrate low littering potential and thus could play a role in transition towards more sustainable coffee consumption.

Comparison of Khorana Vs. Onkotev Predictive Score to Individualize Anticoagulant Prophylaxis in Ambulatory Patients with Cancer

Background: The current guidelines [ J Clin Oncol. 2020;38(5):496] recommend using the risk assessment model (RAM) Khorana score ≥2 [ Blood. 2008;111(10):4902-4907] for primary anticoagulant prophylaxis (PP) of venous thromboembolism (VTE) in patients treated for cancer in an outpatient setting. Recently, a novel RAM, the ONKOTEV score [ JAMA Network Open 2023;6(2):e230010] has been prospectively externally validated with good predictive performance. Like all other established RAMs, the Khorana Score and ONKOTEV models aim to assess the incidence of VTE accurately but do not integrate the expected benefits and potential harms of treatment to determine the clinical utility of the competing management alternatives. We set out to compare the clinical utility of the Khorana Score vs. the ONKOTEV predictive model to guide the PP of VTE in patients receiving anticancer treatment. Methods: We used the ONKOTEV validation dataset (n=425). The ONKOTEV score included the Khorana Score (dichotomized as Khorana score >2 vs. ≤ 2) and three readily available clinical information (also dichotomized): history of previous VTE, the presence of metastatic disease, and clinical or radiological assessment of vascular or lymphatic compression by tumor. After assessing the models' performance (discrimination, calibration), we applied a generalized decision curve analysis (gDCA) to integrate the effects of treatments with the models' predictive accuracy. This, in turn, allowed us to develop individualized recommendations for using PP for VTE in patients receiving anticancer treatment. We calculated net benefits (NB) to compare three management strategies: don't provide any treatment vs. administer prophylaxis to all patients receiving anticancer treatment for VTE vs. use the Khorana or ONKOTEV model to guide PP of VTE. According to gDCA, the best treatment is the one with the highest NB. We obtained data on treatment effects from the meta-analysis of published randomized trials comparing direct oral anticoagulants (DOAC) and low-molecular-weight heparins (LMWH) vs. placebo [ Annals of Palliative Medicine. 2020;9(5):2970]. We estimated that DOAC reduced the risk of VTE by 57% [relative risk reduction (RRR) =0.57 (95%CI: 0.13 to 0.79)] and LMWH by 48% [RRR=0.48 (95%CI: 0.42 to 0.66)]. We assessed the major bleeding rate on DOAC as 0.01 (95%CI: 0.006 to 0.04) and 0.02 (95%CI: 0.01 to 0.03) for LMWH. Results: Both RAMs had a satisfactory performance. Harell's C discrimination statistics was 0.71 for ONKOTEV and 0.66 for Khorana Score with good calibration properties (with intercept and the slope not statistically significantly different from 0 and 1, respectively). Fig 1A shows the results based on the default assumptions: if the patient values avoiding the morbidity of VTE 1.6 to 5 times more (0.2<RV<0.6) than the major bleeding, then offering DOAC to all patients receiving PP for VTE represents the most optimal management strategy. When the patients would rather avoid the consequences of the major bleeding by >2.5x more than the morbidity of VTE, using the ONKOTEV model to guide the administration of DOAC represents the best treatment strategy. If we assume that RRR ≤ 0.2, relying on the ONKOTEV model to guide the use of DOAC becomes the most optimal approach to PP of VTE in patients receiving anticancer treatment (Fig 1B). Conclusion: ONKOTEV model is superior to Khorana Score in guiding individualized PP for VTE in ambulatory patients with cancer. It is particularly helpful when the patient values avoiding major bleeding more than the morbidity of VTE. Our analysis provides new recommendations for PP of VTE receiving outpatient treatment for cancer, calling for updating the current guidelines for PP of VTE in this setting.

A comparison between field measurements of vapour concentrations of plant protection products and predictions by the BROWSE model

A database of field measurements of air concentrations of pesticide active ingredients has previously been compiled by CropLife Europe with an aim to revise the default air concentration values and assumptions applied in assessing vapour exposure in the risk assessment of bystanders and residents. The BROWSE model, released in 2014, which is a regulatory risk assessment model that includes the exposure of residents and bystanders has a component relating to post-application vapour inhalation. Predictions of concentration deduced from exposures obtained using the BROWSE model were compared with field measurements of 24-h and 7-day average concentrations. The methodology for obtaining concentration estimates from the BROWSE model is described, and the criteria for including field studies in the comparison are given. The field data were adjusted to account for differences between the field experiment and the BROWSE scenario using factors derived from a separate plume dispersion model. This showed that BROWSE provides a satisfactory level of conservatism in determining potential exposures of residents and bystanders to vapour and could be a reliable alternative to replace the current EFSA approach for predicting vapour inhalation exposures for pesticides where no compound-specific data are available.

Analyzing the Temporal Variation in Macroseismic Intensity Rating Values and Predicting Macroseismic Intensity on the Tibetan Plateau

ABSTRACT China has relatively rich macroseismic isoseismal maps, which play an important role in seismic hazard analysis and the development of reliable earthquake loss models. The macroseismic intensity is assessed based on the Chinese Seismic Intensity Scale, which is constantly being revised as research progresses and the seismic defense capability is enhanced. To investigate whether intensity rating values show consistency across time in statistical significance, this study collected 543 isoseismal lines for 216 earthquakes on the Tibetan Plateau from 1960 to 2020. Taking intensity prediction equations (IPEs) as a reference, statistical tests of the residuals indicate that there is temporal variation in intensity rating values, which is inconsistent with the default assumption that intensity rating values are consistent for different time periods when developing IPEs. Therefore, we analyze the characteristics of intensity rating values by statistical tests and investigate the mechanism by which the temporal variation in intensity rating values affects IPEs by residual decomposition. The results show that despite the temporal variation in intensity rating values, they can still be used to develop IPEs, and that temporal variability can be reduced by adjustment. Finally, we obtain the regression process of IPEs based on the partially nonergodic assumption considering the temporal variation in intensity rating values, and perform a case study, using the Tibetan Plateau as an example.

Applying circular economy principles to intensification of livestock production in Sub-Saharan Africa

In the context of sustainable agricultural development, much has been made of the need to apply agroecology or regenerative principles to improve rural livelihoods and to align the sector with critical planetary health boundaries. This movement is a reaction to the perceived private and social costs arising from both production and consumption associated with industrialised agriculture, mostly in upper-income countries, with several default assumptions being apparent about applicability elsewhere. The notion of circularity, or the circular economy, is frequently conflated with agro ecological rhetoric, often overlooking a longer tradition of circular resource use efficiency in traditional mixed crop–livestock farming in low-income settings. This paper examines the concept and origins of circularity and reviews some examples of historic circular economy research within the international agricultural research system as applied to smallholder agriculture. These include (i) studies focusing on the impact of crop residue retention, (ii) work on residue incorporation and/or mulching and their effects on crop yields and soil fertility, (iii) research on the effects of manure use on crop yields and soil fertility and (iv) work on the feeding of crop residues to livestock. We consider some promising innovations or practices adhering to circular economy principles. Candidate innovations focus on the improvement of livestock feeding practices including the breeding of dual-purpose crops to enhance livestock nutrition, conversion of cereal straw residues to high-quality feed, use of cassava waste as livestock feed and use of insects as livestock feed. We conclude by considering how circular bio-economy principles might be maintained in the future evolution of food systems in Sub-Saharan Africa.

Tensorized topological graph learning for generalized incomplete multi-view clustering

The success of the current multi-view clustering lies in the default assumption of completeness on each view, while it is hardly satisfied for real-world applications. Incomplete multi-view clustering (IMC) studies clustering multi-view instances that are partially observed due to data corruption or sensor failure. Although making some progress, the current research suffers from the following obstacles: (1) Existing works are always built on pairwise similarity measurement, which cannot fully capture the topological structure of incomplete multi-view samples for precise clustering; (2) Due to the absence of partially-observed samples across multiple views, how could we recover and enhance the high-order similarities across different views becomes one of the main bottlenecks of IMC; (3) Current research mainly aims to handle specific dual-view IMC, which greatly limits the deployment in real-world applications. In this paper, we propose a novel Tensorized Topological Graph Learning (TTGL) for the generalized incomplete multi-view clustering, which jointly considers the topological graph construction, missing feature completion, and high-order uncertain correlation enhancement. Specifically, instead of using pairwise similarity measurement, we formulate a consensus topological graph construction module, which can coalesce affinity matrices to analyze the topological structure of incomplete multi-view data. Moreover, we build an iterative missing similarity imputation scheme for feature completion, which ensures the intrinsic similarity preservation on observed instances as well as an imputation on unobserved ones. Furthermore, a low-rank tensor structure is imposed to capture the high-order similarities via both feature and similarity enhancement and completion across different views. Our method can cluster incomplete data with an arbitrary number of views and any missing statuses. Extensive experiments on several benchmark datasets validate the effectiveness of our method when compared with a series of state-of-the-art IMC clustering algorithms. The source code of our TTGL is available at: https://github.com/DarrenZZhang/TTGL.

LandInG 1.0: a toolbox to derive input datasets for terrestrial ecosystem modelling at variable resolutions from heterogeneous sources

Abstract. We present the Land Input Generator (LandInG) version 1.0, a new toolbox for generating input datasets for terrestrial ecosystem models (TEMs) from diverse and partially conflicting data sources. While LandInG 1.0 is applicable to process data for any TEM, it is developed specifically for the open-source dynamic global vegetation, hydrology, and crop growth model LPJmL (Lund–Potsdam–Jena with managed Land). The toolbox documents the sources and processing of data to model inputs and allows for easy changes to the spatial resolution. It is designed to make inconsistencies between different sources of data transparent so that users can make their own decisions on how to resolve these should they not be content with the default assumptions made here. As an example, we use the toolbox to create input datasets at 5 and 30 arcmin spatial resolution covering land, country, and region masks, soil, river networks, freshwater reservoirs, irrigation water distribution networks, crop-specific annual land use, fertilizer, and manure application. We focus on the toolbox describing the data processing rather than only publishing the datasets as users may want to make different choices for reconciling inconsistencies, aggregation, spatial extent, or similar. Also, new data sources or new versions of existing data become available continuously, and the toolbox approach allows for incorporating new data to stay up to date.

Coupled biological and hydrological processes shape spatial food-web structures in riverine metacommunities

IntroductionUnderstanding how species are distributed in space and how they interact with each other is central for scientific and conservation purposes. Species' distributions and interactions result from a complex interplay of local trophic dynamics, dispersal processes, resource availability, and abiotic factors governed by the landscape matrix, which also determines the spatial connectivity for organisms' dispersal and resource fluxes. River networks not only exhibit universal spatial structures, but their dendritic landscape structure is tightly linked to species and metacommunity processes therein.MethodsHere, using a mechanistic model of spatially connected food webs integrating both essential biological and hydrological aspects, we investigate how food-web properties vary in space, and how these patterns are influenced by key model parameters. We then contrast our predictions with a suite of null models, where different aspects (such as spatial structure or trophic interactions) of the spatial food-web model are alternatively relaxed.ResultsWe find that species richness is highest in areas where local nutrient load is maximal (lowland headwaters, according to our default assumption). Overall, species richness is positively associated with link density, modularity and omnivory, and negatively related to connectance, nestedness, and niche overlap. However, for metrics such as connectance and omnivory, stochasticity of trophic interactions is a much stronger predictor than spatial variables such as distance to outlet and drainage area. Remarkably, relationships between species richness and food-web metrics do not generally hold in null models, and are hence the outcome of coupled biological and physical (i.e., hydrological) processes characteristic to river networks.DiscussionOur model generates realistic patterns of species richness and food-web properties, shows that no universal food-web patterns emerge as a result of the riverine landscape structure, and paves the way for future applications aimed at disentangling metacommunity dynamics in river networks.

Syntactic and semantic interference in sentence comprehension: Support from English and German eye-tracking data

A long-standing debate in the sentence processing literature concerns the time course of syntactic and semantic information processing in online sentence comprehension. The default assumption in cue-based models of parsing is that syntactic and semantic retrieval cues simultaneously guide dependency resolution. When retrieval cues match multiple items in memory, this leads to similarity-based interference. Both semantic and syntactic interference have been shown to occur in English. However, the relative timing of syntactic vs. semantic interference remains unclear. In this cross-linguistic investigation of the time course of syntactic vs. semantic interference, the data from two eye-tracking during reading experiments (English and German) suggest that the two types of interference can in principle arise simultaneously during retrieval. However, the data also indicate that semantic cues are evaluated with a small timing lag in German compared to English. This cross-linguistic difference between English and German may be due to German having richer morphosyntactic marking than English, resulting in syntactic cues dominating over semantic cues during dependency resolution. More broadly, our cross-linguistic results pose a challenge for the cue-based retrieval model’s default assumption that syntactic and semantic cues are used simultaneously during long-distance dependency formation. Our work also highlights the importance of collecting cross-linguistic data on psycholinguistic phenomena which can potentially advance theory development.

Modeling of age-dependent natural mortality rates for long-lived fishes based on the Richards model family

Natural mortality rates ( M) are poorly quantified and commonly identified as a key source of uncertainty in fish stock assessments. Increasingly, stock assessments account for size- and age-dependence in M instead of using a constant M for all sizes and ages, as has traditionally been the default assumption. Empirical studies show that M is approximately inversely proportional to body length in fish populations, and this generalization has been used together with a von Bertalanffy growth curve to derive an age-dependent M. Here we extend this approach to the three commonly used growth functions of the Richards family (i.e., Logistic, von Bertalanffy, and Gompertz growth models). These models allow flexible production of various growth curves with a sigmoid shape and an upper asymptote, making them useful for displaying diverse growth curves for various long-lived fishes. The influences of growth parameters on predicted M were investigated, and the outcomes were compared among the three growth models. Age-dependent M for blue sharks ( Prionace glauca) were estimated as an example.

Epistemic Explanations: A Theory of Telic Normativity, and What it Explains

<i>Epistemic Explanations: A Theory of Telic Normativity, and What it Explains</i>