Who Bears the Burden of a Pandemic? COVID-19 and the Transfer of Risk to Digital Platform Workers

In this paper, we analyze the recessionary effects of the COVID-19 pandemic on digital platform workers. The crisis has been described as a great work-from-home experiment, with platform ecosystems positing as its most advanced form. Our analysis differentiates the direct (health) and indirect (economic) risks incurred by workers, to critically assess the portrayal of platforms as buffers against crisis-induced layoffs. We submit that platform-mediated labor may eventually increase precarity, without necessarily reducing health risks for workers. Our argument is based on a comparison of the three main categories of platform work—“on-demand labor” (gigs such as delivery and transportation), “online labor” (tasks performed remotely, such as data annotation), and “social networking labor” (content generation and moderation). We discuss the strategies that platforms deploy to transfer risk from clients onto workers, thus deepening existing power imbalances between them. These results question the problematic equivalence between work-from-home and platform labor. Instead of attaining the advantages of the former in terms of direct and indirect risk mitigation, an increasing number of platformized jobs drift toward high economic and insuppressible health risks.

Workflows for Construction of Spatio-Temporal Probabilistic Maps for Volcanic Hazard Assessment

Probabilistic hazard assessments for studying overland pyroclastic flows or atmospheric ash clouds under short timelines of an evolving crisis, require using the best science available unhampered by complicated and slow manual workflows. Although deterministic mathematical models are available, in most cases, parameters and initial conditions for the equations are usually only known within a prescribed range of uncertainty. For the construction of probabilistic hazard assessments, accurate outputs and propagation of the inherent input uncertainty to quantities of interest are needed to estimate necessary probabilities based on numerous runs of the underlying deterministic model. Characterizing the uncertainty in system states due to parametric and input uncertainty, simultaneously, requires using ensemble based methods to explore the full parameter and input spaces. Complex tasks, such as running thousands of instances of a deterministic model with parameter and input uncertainty require a High Performance Computing infrastructure and skilled personnel that may not be readily available to the policy makers responsible for making informed risk mitigation decisions. For efficiency, programming tasks required for executing ensemble simulations need to run in parallel, leading to twin computational challenges of managing large amounts of data and performing CPU intensive processing. The resulting flow of work requires complex sequences of tasks, interactions, and exchanges of data, hence the automatic management of these workflows are essential. Here we discuss a computer infrastructure, methodology and tools which enable scientists and other members of the volcanology research community to develop workflows for construction of probabilistic hazard maps using remotely accessed computing through a web portal.

Application of Multivariate Techniques for Spatial Drought Modelling using Satellite Rainfall Estimate in Fiji

Monitoring hydrological extremes is essential for developing risk-mitigation strategies. One of the limiting factors for this is the absence of reliable on the ground monitoring networks that capture data on climate variables, which is highly evident in developing states such as Fiji. Fortunately, increasing global coverage of satellite-derived datasets is facilitating utilisation of this information for monitoring dry and wet periods in data sparse regions. In this study, three global satellite rainfall datasets (CHIRPS, PERSIANN-CDR and CPC) were evaluated for Fiji. All satellite products had reasonable correlations with station data, and CPC had the highest correlation with minimum error values. The Effective Drought Index (EDI), a useful index for understanding hydrological extremes, was then calculated. Thereafter, a canonical correlation analysis (CCA) was employed to forecast the EDI using sea surface temperature anomaly (SSTa) data. A high canonical correlation of 0.98 was achieved between the PCs of mean SST and mean EDI, showing the influence of ocean–atmospheric interactions on precipitation regimes in Fiji. CCA was used to perform a hind cast and a short-term forecast. The training stage produced a coefficient of determinant (R2) value of 0.83 and mean square error (MSE) of 0.11. The results in the testing stage for the forecast were more modest, with an R2 of 0.45 and MSE of 0.26. This easy-to-implement system can be a useful tool used by disaster management bodies to aid in enacting water restrictions, providing aid, and making informed agronomic decisions such as planting dates or extents.

Wind Turbines, Public Acceptance, and Electoral Outcomes

Despite a widespread public support for wind energy in general, wind turbine proposals attract a considerable amount of public opposition. At a time of political commitments to building more wind turbines for climate risk mitigation, we study the potential causes of this opposition and their electoral effects. Our analysis draws on a survey experiment in Switzerland, where the number of wind turbines will grow from a couple of dozens to many hundreds in the next three decades. We find that exposure to wind turbines increases public acceptance, but this affect does not translate into electoral turnout or vote choice. Moreover, locality or politicisation does not seem to have an effect at all—neither on acceptance nor on electoral outcomes. Our results suggest that voters do not reward or punish political parties for their positions on wind energy, even when turbines might soon be rising in their local area.

Economies of diversification and stochastic dominance analysis in French mixed sheep farms

Farm diversification is mainly driven by risk mitigation effects and economic gains related to complementarities between production activities. By combining these two aspects, we investigate diversification economies in a sample of French mixed sheep farming systems and rank these systems using stochastic dominance criteria. Partially diversified systems (Sheep-Grass, Sheep-Crop, Sheep-Landless) and fully diversified systems (Sheep-Grass-Crop-Landless) were evaluated. We find a high degree of diversification diseconomies in the sheep farming systems considered. The results also indicate that the fully diversified system is driven by its risk-reducing effects (including downside risk exposure) and that Sheep-Crop is the dominant system in terms of risk-adjusted returns.

International Pesticide Operator Safety Meeting 2021: hand-held application scenarios in low- and middle-income countries

An international web meeting on the topic of operator safety for pesticide operators was held on 20–21 September 2021. The meeting provided an opportunity for experts from regulatory agencies, pesticide industry, the Food and Agriculture Organization (FAO), and other organizations to discuss operator safety in low- and middle-income countries (LMIC). The meeting focused on risk assessment and risk mitigation, the first steps to address operator safety. The key message at the meeting was the need for an operator exposure model that includes common hand-held scenarios used in LMIC and consistent personal protective equipment communication. The experts supported a transparent collaborative process that will enable us to build on the past efforts.

Characterization and management of interaction risks between livestock and wild ungulates on outdoor pig farms in Spain

Background To control the transmission of relevant shared diseases, such as animal tuberculosis (TB) and African swine fever (ASF), it is essential to reduce the risk of interaction between livestock and wild ungulates. In Eastern and Central Europe, the current spread of ASF virus affecting wild boar and domestic pigs (especially those raised outdoors and/or in backyards) has devastated the pig sector in affected regions and is seriously threatening other exporting countries. Here, we evaluated the risk of wildlife-livestock interactions on 45 outdoor pig farms in Spain, the second largest pork producer in the EU and then proposed biosecurity-related actions. An integrated, systematic wildlife risk mitigation protocol based on interviews, questionnaires and field audits was developed and applied on each farm. Results Most of the interaction risk points were associated with water sources (84.2%; 701/832), mainly springs and ponds, which accounted for almost all the specific points with high or very high risk scores. The risk of interaction at feeding points (6.9%; 57/832) and those associated with facilities for livestock and/or game management (8.9%; 74/832) were rated as low and very low risk, respectively. Wild boar were present and hunted on 69% of the farms. Supplementary feeding for wild ungulate species (mainly wild boar) was provided on almost half (48.9%; 22/45) the surveyed farms. Risk mitigation actions were categorised to target water access, waterers, food, other livestock species, grazing, wildlife, and offal disposal. Of the total number of actions (n = 2016), 82.7% were identified as priority actions while 17.3% represented alternative options which were identified less cost-effective. On average, 37.1 (median: 32; range 14–113) action proposals per study farm were made and 2.0 (median: 1; range 0–4) per risk point. The mean estimated cost of implementing the proposed priority actions was 14,780 €/farm (25.7 €/hectare and 799.4 €/risk point). Conclusions This study expands the knowledge of interaction risks between domestic pigs and wild ungulates in outdoor pig farming systems and highlights the importance of considering local risks and management practices when designing and prioritising adapted wildlife risk mitigation and biosecurity actions. This practical and feasible protocol developed for Mediterranean ecosystems is easily transferable to professionals and can be adapted to extensive (outdoor) production or epidemiological systems in other European regions.

LGBT-supportive corporate policies, risk aversion and mitigation and economic policy uncertainty

PurposeThe paper aims to investigate the effect of uncertain times on LGBT-supportive corporate policies, exploiting a novel text-based measure of economic policy uncertainty (EPU) that was recently constructed by Baker et al. (2016). LGBT-supportive policies have attracted a great deal of attention in the media lately. There is also a rapidly growing area of the literature that addresses LGBT-supportive policies specifically.Design/methodology/approachThe authors execute a regression analysis and several other robustness checks including propensity score matching (PSM) and an instrumental-variable analysis to mitigate endogeneity.FindingsThe authors' results show that companies significantly raise their investments in LGBT-supportive policies in times of greater uncertainty, reinforcing the risk mitigation view where LGBT-supportive policies create moral capital with an insurance-like effect that mitigates adverse consequences during uncertain times. The effect of EPU on LGBT-supportive policies is above and beyond its effect on corporate social responsibility (CSR) in general.Originality/valueThe authors' study is the first to explore the effect of uncertain times on LGBT-supportive corporate policies. The authors contribute to a crucial area of the literature that examines how firms respond to EPU. In addition, the authors enrich the literature on LGBT-friendly policies by showing that EPU is one of the significant determinants of LGBT-friendly policies.