3D-printed model of a 500-year-old prosthetic hand hints at life of a Renaissance amputee
Technology is more than just mechanisms and design – it’s ultimately about people. Adriene Simon/College of Liberal Arts, Auburn University, CC BY-SAHeidi Hausse, Auburn University and Peden Jones, Auburn University To think about an artificial limb is to think about a person. It’s an object of touch and motion made to be used, one that attaches to the body and interacts with its user’s world. Historical artifacts of prosthetic limbs are far removed from this lived context. Their users are gone. They are damaged – deteriorated by time and exposure to the elements. They are motionless, kept on display or in museum storage. Yet, such artifacts are rare direct sources into thelives of historical amputees. We focus on the tools amputees used in 16th- and 17th-century Europe. There are few records written from amputees’ perspectives at that time, and those that exist say little about what everyday life with a prosthesis was like. Engineering offers historians new tools to examine physical evidence. This is particularly important for the study of early modern mechanical hands, a new kind of prosthetic technology that appeared at the turn of the 16th century. Most of the artifacts are of unknown provenance. Many work only partially and some not at all. Their practical functions remain a mystery. But computer-aided design software can help scholars reconstruct the artifacts’ internal mechanisms. This, in turn, helps us understand how the objects once moved.
Even more exciting, 3D printing lets scholars create physical models. Rather than imagining how a Renaissance prosthesis worked, scholars can physically test one. It’s a form of investigation that opens new possibilities for exploring the development of prosthetic technology and user experience through the centuries. It creates a trail of breadcrumbs that can bring us closer to the everyday experiences of premodern amputees. But what does this work, which brings together two very different fields, look like in action? What follows is a glimpse into our experience of collaboration on a team of historians and engineers, told through the story of one week. Working together, we shared a model of a 16th-century prosthesis with the public and learned a lesson about humans and technology in the process.
A historian encounters a broken model
THE HISTORIAN: On a cloudy day in late March, I walked into the University of Alabama Birmingham’s Center for Teaching and Learning holding a weatherproof case and brimming with excitement. Nestled within the case’s foam inserts was a functioning 3D-printed model of a 500-year-old prosthetic hand. Fifteen minutes later, it broke.This 3D-printed model of a 16th-century hand prosthesis has working mechanisms.Heidi Hausse, CC BY-SA For two years, my team of historians and engineers at Auburn University had worked tirelessly to turn an idea – recreating the mechanisms of a 16th-century artifact from Germany – into reality. The original iron prosthesis, the Kassel Hand, is one of approximately 35 from Renaissance Europe known today. As an early modern historian who studies these artifacts, I work with a mechanical engineer, Chad Rose, to find new ways to explore them. The Kassel Hand is our case study. Our goal is to learn more about the life of the unknown person who used this artifact 500 years ago. Using 3D-printed models, we’ve run experiments to test what kinds of activities its user could have performed with it. We modeled in inexpensive polylactic acid – plastic – to make this fragile artifact accessible to anyone with a consumer-grade 3D printer. But before sharing our files with the public, we needed to see how the model fared when others handled it. An invitation to guest lecture on our experiments in Birmingham was our opportunity to do just that. We brought two models. The main release lever broke first in one and then the other. This lever has an interior triangular plate connected to a thin rod that juts out of the wrist like a trigger. After pressing the fingers into a locked position, pulling the trigger is the only way to free them. If it breaks, the fingers become stuck.The thin rod of the main release lever snapped in this model.Heidi Hausse, CC BY-SA I was baffled. During testing, the model had lifted a 20-pound simulation of a chest lid by its fingertips. Yet, the first time we shared it with a general audience, a mechanism that had never broken in testing simply snapped. Was it a printing error? Material defect? Design flaw? We consulted our Hand Whisperer: our lead student engineer whose feel for how the model works appears at times preternatural.
An engineer becomes a hand whisperer
THE ENGINEER: I was sitting at my desk in Auburn’s mechanical engineering 3D print lab when I heard the news. As a mechanical engineering graduate student concentrating on additive manufacturing, commonly known as 3D printing, I explore how to use this technology to reconstruct historical mechanisms. Over the two years I’ve worked on this project, I’ve come to know the Kassel Hand model well. As we fine-tuned designs, I’ve created and edited its computer-aided design files – the digital 3D constructions of the model – and printed and assembled its parts countless times.This view of the computer-aided design file of a strengthened version of the model, which includes ribs and fillets to reinforce the plastic material, highlights the main release lever in orange.Peden Jones, CC BY-SA Examining parts midassembly is a crucial checkpoint for our prototypes. This quality control catches, corrects and prevents any defects, such as misprinted or damaged parts. It’s crucial for creating consistent and repeatable experiments. A new model version or component change never leaves the lab without passing rigorous inspection. This process means there are ways this model has behaved over time that the rest of the team has never seen. But I have. So when I heard the release lever had broken in Birmingham, it was just another Thursday. While it had never snapped when we tested the model on people, I’d seen it break plenty of times while performing checks on components.Our model reconstructs the Kassel Hand’s original metal mechanisms in plastic.Heidi Hausse, CC BY-SA After all, the model is made from relatively weak polylactic acid. Perhaps the most difficult part of our work is making a plastic model as durable as possible while keeping it visually consistent with the 500-year-old original. The iron rod of the artifact’s lever can handle more force than our plastic version, at least five times the yield strength. I suspected the lever had snapped because people pulled the trigger too far back and too quickly. The challenge, then, was to prevent this. But redesigning the lever to be thicker or a different shape would make it less like the historical artifact. This raised the question: Why could I use the model without breaking the lever, but no one else could?
The team makes a plan
THE TEAM: A flurry of discussion led to growing consensus – the crux of the issue was not the model, it was the user. The original Kassel Hand’s wearer would have learned to use their prosthesis through practice. Likewise, our team had learned to use the model over time. Through the process of design and development, prototyping and printing, we were inadvertently practicing how to operate it. We needed to teach others to do the same. And this called for a two-pronged approach.Perspective on using the Kassel Hand, as a modern prosthetist. The engineers reexamined the opening through which the release trigger poked out of the model. They proposed shortening it to limit how far back users could pull it. When we checked how this change would affect the model’s accuracy, we found that a smaller opening was actually closer to the artifact’s dimensions. While the larger opening had been necessary for an earlier version of the release lever that needed to travel farther, now it only caused problems. The engineers got to work. The historians, meanwhile, created plans to document and share the various techniques to operating the model the team hadn’t realized it had honed. To teach someone at home how to operate their own copy, we filmed a short video explaining how to lock and release the fingers and troubleshoot when a finger sticks.
Testing the plan
Exactly one week after what we called “the Birmingham Break,” we shared the model with a general audience again. This time we visited a colleague’s history class at Auburn. We brought four copies. Each had an insert to shorten the opening around the trigger. First, we played our new instructional video on a projector. Then we turned the models over to the students to try.The team brought these four models with inserts to shorten the opening below the release trigger to test with a general audience of undergraduate and graduate students.Heidi Hausse, CC BY-SA The result? Not a single broken lever. We publicly launched the project on schedule. The process of introducing the Kassel Hand model to the public highlights that just as the 16th-century amputee who wore the artifact had to learn to use it, one must learn to use the 3D-printed model, too. It is a potent reminder that technology is not just a matter of mechanisms and design. It is fundamentally about people – and how people use it. Heidi Hausse, Associate Professor of History, Auburn University and Peden Jones, Graduate Student in Mechanical Engineering, Auburn University This article is republished from The Conversation under a Creative Commons license. Read the original article.
AI-induced cultural stagnation is no longer speculation − it’s already happening
AI-induced cultural stagnation. A 2026 study by researchers revealed that when generative AI operates autonomously, it produces homogenous content, referred to as “visual elevator music,” despite diverse prompts. This convergence leads to bland outputs and indicates a risk of cultural stagnation as AI perpetuates familiar themes, potentially limiting innovation and diversity in creative expression.
When generative AI was left to its own devices, its outputs landed on a set of generic images – what researchers called ‘visual elevator music.’ Wang Zhao/AFP via Getty Images
Generative AI was trained on centuries of art and writing produced by humans.
But scientistsand critics have wondered what would happen once AI became widely adopted and started training on its outputs.
A new study points to some answers.
In January 2026, artificial intelligence researchers Arend Hintze, Frida Proschinger Åström and Jory Schossau published a study showing what happens when generative AI systems are allowed to run autonomously – generating and interpreting their own outputs without human intervention.
The researchers linked a text-to-image system with an image-to-text system and let them iterate – image, caption, image, caption – over and over and over.
Regardless of how diverse the starting prompts were – and regardless of how much randomness the systems were allowed – the outputs quickly converged onto a narrow set of generic, familiar visual themes: atmospheric cityscapes, grandiose buildings and pastoral landscapes. Even more striking, the system quickly “forgot” its starting prompt.
The researchers called the outcomes “visual elevator music” – pleasant and polished, yet devoid of any real meaning.
For example, they started with the image prompt, “The Prime Minister pored over strategy documents, trying to sell the public on a fragile peace deal while juggling the weight of his job amidst impending military action.” The resulting image was then captioned by AI. This caption was used as a prompt to generate the next image.
The results show that generative AI systems themselves tend toward homogenization when used autonomously and repeatedly. They even suggest that AI systems are currently operating in this way by default.
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The familiar is the default
This experiment may appear beside the point: Most people don’t ask AI systems to endlessly describe and regenerate their own images. The convergence to a set of bland, stock images happened without retraining. No new data was added. Nothing was learned. The collapse emerged purely from repeated use.
But I think the setup of the experiment can be thought of as a diagnostic tool. It reveals what generative systems preserve when no one intervenes.Pretty … boring. Chris McLoughlin/Moment via Getty Images
This has broader implications, because modern culture is increasingly influenced by exactly these kinds of pipelines. Images are summarized into text. Text is turned into images. Content is ranked, filtered and regenerated as it moves between words, images and videos. New articles on the web are now more likely to be written by AI than humans. Even when humans remain in the loop, they are often choosing from AI-generated options rather than starting from scratch.
The findings of this recent study show that the default behavior of these systems is to compress meaning toward what is most familiar, recognizable and easy to regenerate.
Cultural stagnation or acceleration?
For the past few years, skeptics have warned that generative AI could lead to cultural stagnation by flooding the web with synthetic content that future AI systems then train on. Over time, the argument goes, this recursive loop would narrow diversity and innovation.
What has been missing from this debate is empirical evidence showing where homogenization actually begins.
The new study does not test retraining on AI-generated data. Instead, it shows something more fundamental: Homogenization happens before retraining even enters the picture. The content that generative AI systems naturally produce – when used autonomously and repeatedly – is already compressed and generic.
This reframes the stagnation argument. The risk is not only that future models might train on AI-generated content, but that AI-mediated culture is already being filtered in ways that favor the familiar, the describable and the conventional.
Retraining would amplify this effect. But it is not its source.
This is no moral panic
Skeptics are right about one thing: Culture has always adapted to new technologies. Photography did not kill painting. Film did not kill theater. Digital tools have enabled new forms of expression.
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But those earlier technologies never forced culture to be endlessly reshaped across various mediums at a global scale. They did not summarize, regenerate and rank cultural products – news stories, songs, memes, academic papers, photographs or social media posts – millions of times per day, guided by the same built-in assumptions about what is “typical.”
The study shows that when meaning is forced through such pipelines repeatedly, diversity collapses not because of bad intentions, malicious design or corporate negligence, but because only certain kinds of meaning survive the text-to-image-to-text repeated conversions.
This does not mean cultural stagnation is inevitable. Human creativity is resilient. Institutions, subcultures and artists have always found ways to resist homogenization. But in my view, the findings of the study show that stagnation is a real risk – not a speculative fear – if generative systems are left to operate in their current iteration.
They also help clarify a common misconception about AI creativity: Producing endless variations is not the same as producing innovation. A system can generate millions of images while exploring only a tiny corner of cultural space.
In my own research on creative AI, I found that novelty requires designing AI systems with incentives to deviate from the norms. Without it, systems optimize for familiarity because familiarity is what they have learned best. The study reinforces this point empirically. Autonomy alone does not guarantee exploration. In some cases, it accelerates convergence.
This pattern already emerged in the real world: One study found that AI-generated lesson plans featured the same drift toward conventional, uninspiring content, underscoring that AI systems converge toward what’s typical rather than what’s unique or creative.AI’s outputs are familiar because they revert to average displays of human creativity. Bulgac/iStock via Getty Images
Lost in translation
Whenever you write a caption for an image, details will be lost. Likewise for generating an image from text. And this happens whether it’s being performed by a human or a machine.
In that sense, the convergence that took place is not a failure that’s unique to AI. It reflects a deeper property of bouncing from one medium to another. When meaning passes repeatedly through two different formats, only the most stable elements persist.
But by highlighting what survives during repeated translations between text and images, the authors are able to show that meaning is processed inside generative systems with a quiet pull toward the generic.
The implication is sobering: Even with human guidance – whether that means writing prompts, selecting outputs or refining results – these systems are still stripping away some details and amplifying others in ways that are oriented toward what’s “average.”
If generative AI is to enrich culture rather than flatten it, I think systems need to be designed in ways that resist convergence toward statistically average outputs. There can be rewards for deviation and support for less common and less mainstream forms of expression.
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The study makes one thing clear: Absent these interventions, generative AI will continue to drift toward mediocre and uninspired content.
Cultural stagnation is no longer speculation. It’s already happening.
A severe winter storm that brought crippling freezing rain, sleet and snow to a large part of the U.S. in late January 2026 left a mess in states from New Mexico to New England. Hundreds of thousands of people lost power across the South as ice pulled down tree branches and power lines, more than a foot of snow fell in parts of the Midwest and Northeast, and many states faced bitter cold that was expected to linger for days.
The sudden blast may have come as a shock to many Americans after a mostly mild start to winter, but that warmth may have partly contributed to the ferocity of the storm.
As atmospheric and climate scientists, we conduct research that aims to improve understanding of extreme weather, including what makes it more or less likely to occur and how climate change might or might not play a role.
To understand what Americans are experiencing with this winter blast, we need to look more than 20 miles above the surface of Earth, to the stratospheric polar vortex.On the morning of Jan. 26, 2026, the freezing line, shown in white, reached far into Texas. The light band with arrows indicates the jet stream, and the dark band indicates the stratospheric polar vortex. The jet stream is shown at about 3.5 miles above the surface, a typical height for tracking storm systems. The polar vortex is approximately 20 miles above the surface. Mathew Barlow, CC BY
What creates a severe winter storm like this?
Multiple weather factors have to come together to produce such a large and severe storm.
Winter storms typically develop where there are sharp temperature contrasts near the surface and a southward dip in the jet stream, the narrow band of fast-moving air that steers weather systems. If there is a substantial source of moisture, the storms can produce heavy rain or snow.
In late January, a strong Arctic air mass from the north was creating the temperature contrast with warmer air from the south. Multiple disturbances within the jet stream were acting together to create favorable conditions for precipitation, and the storm system was able to pull moisture from the very warm Gulf of Mexico.The National Weather Service issued severe storm warnings (pink) on Jan. 24, 2026, for a large swath of the U.S. that could see sleet and heavy snow over the following days, along with ice storm warnings (dark purple) in several states and extreme cold warnings (dark blue). National Weather Service
Where does the polar vortex come in?
The fastest winds of the jet stream occur just below the top of the troposphere, which is the lowest level of the atmosphere and ends about seven miles above Earth’s surface. Weather systems are capped at the top of the troposphere, because the atmosphere above it becomes very stable.
The stratosphere is the next layer up, from about seven miles to about 30 miles. While the stratosphere extends high above weather systems, it can still interact with them through atmospheric waves that move up and down in the atmosphere. These waves are similar to the waves in the jet stream that cause it to dip southward, but they move vertically instead of horizontally.A chart shows how temperatures in the lower layers of the atmosphere change between the troposphere and stratosphere. Miles are on the right, kilometers on the left. NOAA
You’ve probably heard the term “polar vortex” used when an area of cold Arctic air moves far enough southward to influence the United States. That term describes air circulating around the pole, but it can refer to two different circulations, one in the troposphere and one in the stratosphere.
The Northern Hemisphere stratospheric polar vortex is a belt of fast-moving air circulating around the North Pole. It is like a second jet stream, high above the one you may be familiar with from weather graphics, and usually less wavy and closer to the pole.
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Sometimes the stratospheric polar vortex can stretch southward over the United States. When that happens, it creates ideal conditions for the up-and-down movement of waves that connect the stratosphere with severe winter weather at the surface.A stretched stratospheric polar vortex reflects upward waves back down, left, which affects the jet stream and surface weather, right. Mathew Barlow and Judah Cohen, CC BY
The forecast for the January storm showed a close overlap between the southward stretch of the stratospheric polar vortex and the jet stream over the U.S., indicating perfect conditions for cold and snow.
This is what was happening in late January 2026 in the central and eastern U.S.
If the climate is warming, why are we still getting severe winter storms?
Earth is unequivocally warming as human activities release greenhouse gas emissions that trap heat in the atmosphere, and snow amounts are decreasing overall. But that does not mean severe winter weather will never happen again.
One factor may be increasing disruptions to the stratospheric polar vortex, which appear to be linked to the rapid warming of the Arctic with climate change.The polar vortex is a strong band of winds in the stratosphere, normally ringing the North Pole. When it weakens, it can split. The polar jet stream can mirror this upheaval, becoming weaker or wavy. At the surface, cold air is pushed southward in some locations. NOAA
Additionally, a warmer ocean leads to more evaporation, and because a warmer atmosphere can hold more moisture, that means more moisture is available for storms. The process of moisture condensing into rain or snow produces energy for storms as well. However, warming can also reduce the strength of storms by reducing temperature contrasts.
A warmer environment also increases the likelihood that precipitation that would have fallen as snow in previous winters may now be more likely to fall as sleet and freezing rain.
There are still many questions
Scientists are constantly improving the ability to predict and respond to these severe weather events, but there are many questions still to answer.
Much of the data and research in the field relies on a foundation of work by federal employees, including government labs like the National Center for Atmospheric Research, known as NCAR, which has been targeted by the Trump administration for funding cuts. These scientists help develop the crucial models, measuring instruments and data that scientists and forecasters everywhere depend on.
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This article, originally published Jan. 24, 2026, has been updated with details from the weekend storm.
The science section of our news blog STM Daily News provides readers with captivating and up-to-date information on the latest scientific discoveries, breakthroughs, and innovations across various fields. We offer engaging and accessible content, ensuring that readers with different levels of scientific knowledge can stay informed. Whether it’s exploring advancements in medicine, astronomy, technology, or environmental sciences, our science section strives to shed light on the intriguing world of scientific exploration and its profound impact on our daily lives. From thought-provoking articles to informative interviews with experts in the field, STM Daily News Science offers a harmonious blend of factual reporting, analysis, and exploration, making it a go-to source for science enthusiasts and curious minds alike. https://stmdailynews.com/category/science/
What a bear attack in a remote valley in Nepal tells us about the problem of aging rural communities
A 71-year-old in Nepal’s Nubri valley survives repeated bear attacks as youth outmigration and rapid population aging leave fewer people to protect crops and homes—pushing bears closer to villages and raising urgent questions about safety, conservation rules, and rural resilience.
Dorje Dundul recently had his foot gnawed by a brown bear – a member of the species Ursus thibetanus, to be precise.
It wasn’t his first such encounter. Recounting the first of three such violent experiences over the past five years, Dorje told our research team: “My wife came home one evening and reported that a bear had eaten a lot of corn from the maize field behind our house. So, we decided to shoo it away. While my wife was setting up camp, I went to see how much the bear had eaten. The bear was just sitting there; it attacked me.”
Dorje dropped to the ground, but the bear ripped open his shirt and tore at his shoulder. “I started shouting and the bear ran away. My wife came, thinking I was messing with her, but when she saw the wounds, she knew what had happened.”
Researchers Dolma Choekyi Lama, Tsering Tinley and I spoke with Dorje – a 71-year-old resident of Nubri, a Buddhist enclave in the Nepalese highlands – as part of a three-year study of aging and migration.
Now, you may be forgiven for asking what a bear attack on a septuagenarian has to do with demographic change in Nepal. The answer, however, is everything.
In recent years, people across Nepal have witnessed an increase in bear attacks, a phenomenon recorded in news reports and academic studies.
Inhabitants of Nubri are at the forefront of this trend – and one of the main reasons is outmigration. People, especially young people, are leaving for education and employment opportunities elsewhere. It is depleting household labor forces, so much so that over 75% of those who were born in the valley and are now ages 5 to 19 have left and now live outside of Nubri.
It means that many older people, like Dorje and his wife, Tsewang, are left alone in their homes. Two of their daughters live abroad and one is in the capital, Kathmandu. Their only son runs a trekking lodge in another village.
Scarcity of ‘scarebears’
Until recently, when the corn was ripening, parents dispatched young people to the fields to light bonfires and bang pots all night to ward off bears. The lack of young people acting as deterrents, alongside the abandonment of outlying fields, is tempting bears to forage closer to human residences.
Outmigration in Nubri and similar villages is due in large part to a lack of educational and employment opportunities. The problems caused by the removal of younger people have been exacerbated by two other factors driving a rapidly aging population: People are living longer due to improvements in health care and sanitation; and fertility has declined since the early 2000s, from more than six to less than three births per woman.
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These demographic forces have been accelerating population aging for some time, as illustrated by the population pyramid constructed from our 2012 household surveys in Nubri and neighboring Tsum.
A not-so-big surprise, anymore
Nepal is not alone in this phenomenon; similar dynamics are at play elsewhere in Asia. The New York Times reported in November 2025 that bear attacks are on the rise in Japan, too, partly driven by demographic trends. Farms there used to serve as a buffer zone, shielding urban residents from ursine intruders. However, rural depopulation is allowing bears to encroach on more densely populated areas, bringing safety concerns in conflict with conservation efforts.
Dorje can attest to those concerns. When we met him in 2023 he showed us deep claw marks running down his shoulder and arm, and he vowed to refrain from chasing away bears at night.
So in October 2025, Dorje and Tsewang harvested a field before marauding bears could get to it and hauled the corn to their courtyard for safekeeping. The courtyard is surrounded by stone walls piled high with firewood – not a fail-safe barrier but at least a deterrent. They covered the corn with a plastic tarp, and for extra measure Dorje decided to sleep on the veranda.
He described what happened next:
“I woke to a noise that sounded like ‘sharak, sharak.’ I thought it must be a bear rummaging under the plastic. Before I could do anything, the bear came up the stairs. When I shouted, it got frightened, roared and yanked at my mattress. Suddenly my foot was being pulled and I felt pain.”
Dorje suffered deep lacerations to his foot. Trained in traditional Tibetan medicine, he staunched the bleeding using, ironically, a tonic that contained bear liver.
Yet his life was still in danger due to the risk of infection. It took three days and an enormous expense by village standards – equivalent to roughly US$2,000 – before they could charter a helicopter to Kathmandu for further medical attention.
And Dorje is not the only victim. An elderly woman from another village bumped into a bear during a nocturnal excursion to her outhouse. It left her with a horrific slash from forehead to chin – and her son scrambling to find funds for her evacuation and treatment.A woman weeding freshly planted corn across the valley from Trok, Nubri. Geoff Childs, CC BY-SA
So how should Nepal’s highlanders respond to the increase in bear attacks?
Dorje explained that in the past they set lethal traps when bear encroachments became too dangerous. That option vanished with the creation of Manaslu Conservation Area Project, or MCAP, in the 1990s, a federal initiative to manage natural resources that strictly prohibits the killing of wild animals.
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Learning to grin and bear it?
Dorje reasons that if MCAP temporarily relaxed the regulation, villagers could band together to cull the more hostile bears. He informed us that MCAP officials will hear nothing of that option, yet their solutions, such as solar-powered electric fencing, haven’t worked.
Dorje is reflective about the options he faces as young people leave the village, leaving older folk to battle the bears alone.
“At first, I felt that we should kill the bear. But the other side of my heart says, perhaps I did bad deeds in my past life, which is why the bear bit me. The bear came to eat corn, not to attack me. Killing it would just be another sinful act, creating a new cycle of cause and effect. So, why get angry about it?”
It remains to be seen how Nubri’s residents will respond to the mounting threats bears pose to their lives and livelihoods. But one thing is clear: For those who remain behind, the outmigration of younger residents is making the perils more imminent and the solutions more challenging.
Dolma Choekyi Lama and Tsering Tinley made significant contributions to this article. Both are research team members on the author’s project on population in an age of migration.
