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1. Emotion, embodiment, and reproductive colonialism in the global human egg trade

   https://doi.org/10.1111/gwao.12637  

   Tober, Diane; Kroløkke, Charlotte (March 2021, Gender, Work & Organization)

   null (Ed.)

   In the transnational fertility industry, individuals have differently positioned bodies, ranked by race, class, education, socioeconomic status, gender, and citizenship. Different forms of labor support the transnational fertility market, bringing geopolitical, and social inequities to the fore. While some people need wombs, eggs, or sperm to create their families—and have the means to pay for third‐party reproductive services—others emerge as suppliers of reproductive labor, and still others as coordinators or service agents in the international fertility industry. Building upon contemporary feminist social science and postcolonial research on reproductive travel and labor, this article explores three intersecting components: the forces that influence reproductive travel and cross‐border egg donation; how emotion and meaning are framed in clinical settings to recruit a young, healthy, able‐bodied workforce; and the embodied experiences of women who travel across borders to provide eggs for pay. Drawing upon donor and professional interviews, and multisited online and ethnographic fieldwork in fertility clinics, we explore the linkages between emotional choreography and the creation of a bioavailable workforce for the global fertility trade. Here, we examine how local and cross‐border egg provision illuminate global reproductive hierarchies—what we call “reproductive colonialism”—in transnational reproduction. 

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2. Infrastructure and authority at the state’s edge: The Border Crossings of the World dataset

   https://doi.org/10.1177/00223433221145582  

   Kenwick, Michael_R; Simmons, Beth_A; McAlexander, Richard_J (April 2023, Journal of Peace Research)

   The Border Crossings of the World (BCW) dataset explores state authority spatially by collecting information about infrastructure built where highways cross internationally recognized borders. This geolocated information is recorded using high-altitude imagery from 1993 to 2020. We describe how the data were collected, demonstrate the dataset’s utility, and offer advice and best practices regarding use of the data. These data present clear evidence of visible and long-term state investments in authoritative displays of states’ intention to ‘filter’ entry into and exit out of their national jurisdiction. Researchers can use these data to test theories on the causes and consequences of border hardening for security outcomes, border management cooperation, political violence, terrorism, trade and migration flows, transnational crime patterns, and human rights conditions. Because the data are precisely geolocated, they are easy to combine with existing spatial datasets. 

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3. Multi-isotopes in human hair: A tool to initiate cross-border collaboration in international cold-cases

   https://doi.org/10.1371/journal.pone.0275902  

   Bataille, Clément P.; Ammer, Saskia T.; Bhuiyan, Shelina; Chartrand, Michelle M.; St-Jean, Gilles; Bowen, Gabriel J. (October 2022, PLOS ONE)

   Marzaioli, Fabio (Ed.)

   Unidentified human remains have historically been investigated nationally by law enforcement authorities. However, this approach is outdated in a globalized world with rapid transportation means, where humans easily move long distances across borders. Cross-border cooperation in solving cold-cases is rare due to political, administrative or technical challenges. It is fundamental to develop new tools to provide rapid and cost-effective leads for international cooperation. In this work, we demonstrate that isotopic measurements are effective screening tools to help identify cold-cases with potential international ramifications. We first complete existing databases of hydrogen and sulfur isotopes in human hair from residents across North America by compiling or analyzing hair from Canada, the United States (US) and Mexico. Using these databases, we develop maps predicting isotope variations in human hair across North America. We demonstrate that both δ 2 H and δ 34 S values of human hair are highly predictable and display strong spatial patterns. Multi-isotope analysis combined with dual δ 2 H and δ 34 S geographic probability maps provide evidence for international travel in two case studies. In the first, we demonstrate that multi-isotope analysis in bulk hair of deceased border crossers found in the US, close to the Mexico-US border, help trace their last place of residence or travel back to specific regions of Mexico. These findings were validated by the subsequent identification of these individuals through the Pima County Office of the Medical Examiner in Tucson, Arizona. In the second case study, we demonstrate that sequential multi-isotope analysis along the hair strands of an unidentified individual found in Canada provides detailed insights into the international mobility of this individual during the last year of life. In both cases, isotope data provide strong leads towards international travel. 

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4. Pandemic Response as Border Politics

   https://doi.org/10.1017/S0020818320000363  

   Kenwick, Michael R.; Simmons, Beth A. (December 2020, International Organization)

   null (Ed.)

   Abstract Pandemics are imbued with the politics of bordering. For centuries, border closures and restrictions on foreign travelers have been the most persistent and pervasive means by which states have responded to global health crises. The ubiquity of these policies is not driven by any clear scientific consensus about their utility in the face of myriad pandemic threats. Instead, we show they are influenced by public opinion and preexisting commitments to invest in the symbols and structures of state efforts to control their borders, a concept we call border orientation . Prior to the COVID-19 pandemic, border orientation was already generally on the rise worldwide. This trend has made it convenient for governments to “contain” the virus by externalizing it, rather than taking costly but ultimately more effective domestic mitigation measures. We argue that the pervasive use of external border controls in the face of the coronavirus reflects growing anxieties about border security in the modern international system. To a great extent, fears relating to border security have become a resource in domestic politics—a finding that does not bode well for designing and implementing effective public health policy. 

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5. MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction

   Jorge Quesada, Lakshmi Sathidevi (December 2022, Advances in neural information processing systems)

   There are multiple scales of abstraction from which we can describe the same image, depending on whether we are focusing on fine-grained details or a more global attribute of the image. In brain mapping, learning to automatically parse images to build representations of both small-scale features (e.g., the presence of cells or blood vessels) and global properties of an image (e.g., which brain region the image comes from) is a crucial and open challenge. However, most existing datasets and benchmarks for neuroanatomy consider only a single downstream task at a time. To bridge this gap, we introduce a new dataset, annotations, and multiple downstream tasks that provide diverse ways to readout information about brain structure and architecture from the same image. Our multi-task neuroimaging benchmark (MTNeuro) is built on volumetric, micrometer-resolution X-ray microtomography images spanning a large thalamocortical section of mouse brain, encompassing multiple cortical and subcortical regions. We generated a number of different prediction challenges and evaluated several supervised and self-supervised models for brain-region prediction and pixel-level semantic segmentation of microstructures. Our experiments not only highlight the rich heterogeneity of this dataset, but also provide insights into how self-supervised approaches can be used to learn representations that capture multiple attributes of a single image and perform well on a variety of downstream tasks. Datasets, code, and pre-trained baseline models are provided at: https://mtneuro.github.io/ 

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