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Abstract PurposeTo study the dosimetric impact of incorporating variable relative biological effectiveness (RBE) of protons in optimizing intensity‐modulated proton therapy (IMPT) treatment plans and to compare it with conventional constant RBE optimization and linear energy transfer (LET)‐based optimization. MethodsThis study included 10 pediatric ependymoma patients with challenging anatomical features for treatment planning. Four plans were generated for each patient according to different optimization strategies: (1) constant RBE optimization (ConstRBEopt) considering standard‐of‐care dose requirements; (2) LET optimization (LETopt) using a composite cost function simultaneously optimizing dose‐averaged LET (LET_d) and dose; (3) variable RBE optimization (VarRBEopt) using a recent phenomenological RBE model developed by McNamara et al.; and (4) hybrid RBE optimization (hRBEopt) assuming constant RBE for the target and variable RBE for organs at risk. By normalizing each plan to obtain the same target coverage in either constant or variable RBE, we compared dose, LET_d, LET‐weighted dose, and equivalent uniform dose between the different optimization approaches. ResultsWe found that the LETopt plans consistently achieved increased LET in tumor targets and similar or decreased LET in critical organs compared to other plans. On average, the VarRBEopt plans achieved lower mean and maximum doses with both constant and variable RBE in the brainstem and spinal cord for all 10 patients. To compensate for the underdosing of targets with 1.1 RBE for the VarRBEopt plans, the hRBEopt plans achieved higher physical dose in targets and reduced mean and especially maximum variable RBE doses compared to the ConstRBEopt and LETopt plans. ConclusionWe demonstrated the feasibility of directly incorporating variable RBE models in IMPT optimization. A hybrid RBE optimization strategy showed potential for clinical implementation by maintaining all current dose limits and reducing the incidence of high RBE in critical normal tissues in ependymoma patients. 

Abstract This article uses data from a natural experiment to address one of the most contentious issues in the on-demand platform economy—whether gig work is compatible with standard employment. We analyze a US-based package delivery platform that shifted a subset of its workers from independent contractors to employees, thereby creating a natural experiment that allowed us to exploit variation over time and across locations. We examine the impact of employment status on work scheduling practices, hours of work and the firm’s ability to match workers’ scheduled hours with the amount of time they were actively engaged in parcel delivery. We find that after the transition to employment, flexibility with respect to how work schedules were determined was maintained, and drivers’ total hours of work increased. We also find that the switch to employee status increased the firm’s ability to match scheduled and actual working time, indicating greater operational efficiency. We conclude, contrary to claims commonly made by platform firms, that employment status can coexist with the platform model. 

Abstract This paper explores a neglected aspect of platform work: how the spatial mobility that app-based couriers must perform requires them to violate taken-for-granted assumptions that define who belongs where. By assigning tasks during atypical hours and requiring gig workers to use their personal clothing, tools and vehicles, platforms strip delivery workers of signifiers that legitimate their presence in consumers’ neighbourhoods. The result is a condition we call ‘unbelonging’ – a liminal state in which their presence is considered problematic, exposing them to threats of physical and symbolic violence. Our findings, which draw on 45 interviews with parcel delivery workers, contribute to the developing literature on urban geography and the socio-spatial impacts of the platform revolution. 

Summer Youth Employment Programs are known to significantly impact youth outcomes based on lotteries from oversubscribed programs. But most cities cannot use a lottery design due to heterogeneity across youth and jobs. How can programs achieve efficiency and equity under alternative assignment mechanisms? Using hiring platform data, we study youth applications and employer selection behavior to explore these design challenges. We find large mismatches between the distribution of youth versus jobs, leaving 10% to 25% of positions unfilled. Moreover, employers were nearly twice as likely to select white youth relative to their representation in the applicant pool. This disparity persisted when controlling for other demographics, the number and timing of applications, and job readiness. Our findings reveal that workforce development programs may perpetuate inequities without simple random assignment. 

Expansion of the platform economy has given rise to a paradox in the literature on gig work: Given capital’s imposition of algorithmic controls, why do so many platform workers express support and appreciation for gig work, viewing it as enhancing their autonomy? Approaches toward this question have advanced numerous explanations, such as gamification, neoliberal norms, and entrepreneurial culture. We find these efforts only partially successful, as they fail to explain why ideological incorporation so readily succeeds. We argue that responses to gig work are a function of the class positions that gig workers hold in the wider society, which lead to distinct orientations that they bring to gig work. For workers with a foothold in the middle class, gig work provides access to job rewards that may no longer be available via the conventional economy alone. They consequently experience gig work as a labour of affirmation – a stark contrast with the experience of those gig workers who hold subordinate positions in the class structure. Interview data with 70 respondents in the ride-hail, grocery-shopping and food-delivery sectors supports this approach. Consent to gig work is strongest among our better-off respondents, who hold more secure positions in the conventional economy and use gig work as a culturally-sanctioned mechanism of class reproduction. The implication is that class-based divisions among the platform workforce warrant greater attention than labour process theory has allowed. 

Addressing the urgent global challenge of man-made greenhouse gas emissions and climate change necessitates collaborative action between shipping lines and government regulatory agencies. Aligning with the International Maritime Organization’s emissions reduction strategy, this paper presents a novel bi-level programming model that unifies these stakeholders. On the upper level of the proposed bi-level model, a number of shipping lines optimize retrofitting plans for their vessels to maximize economic benefits. On the lower level, the regulatory agency responds to the carbon reduction efforts by setting retrofitting subsidies and emission penalty rates. This framework represents a multi-leader–single-follower game involving shipping lines and the regulatory agency, and its equilibrium is determined through an equilibrium problem with equilibrium constraints (EPEC). The EPEC comprises multiple single-leader–follower problems, each of which can be formulated as a mathematical program with equilibrium constraints (MPEC). The diagonalization algorithm (DM) is employed for its solution. Simulation studies performed based on a ten-year planning period show that the proposed approach can effectively promote vessel retrofitting and the use of green fuels, which leads to an annual emission reduction of over 50%. 

How do gig workers respond to the various financial, physical, and legal risks their work entails? Answers to this question have remained unclear, largely because previous studies have overlooked structurally induced variations in the experience of platform work. In this article, we develop a theory of differential embeddedness to explain why workers’ orientations toward the risks of gig work vary. We argue further that because platforms define themselves merely as mediators of exchanges between workers and customers, they systematically expose workers to various forms of customer malfeasance, ranging from fraud and tip baiting to harassment and assault. We develop this perspective using interviews with 70 workers in the ride-hail, grocery shopping, and food delivery sectors. The structure of labor platforms indirectly invites workers to exhibit distinct normative orientations toward the risks that gig work entails while also multiplying the sources of these risks.