James' World 2

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Representative Don Bacon, Republican of Nebraska, has publicly accused President Trump of treating Russia with “velvet gloves,” criticized him for gutting AmeriCorps and questioned his power to impose tariffs without congressional approval.

He has described Defense Secretary Pete Hegseth’s use of Signal to share sensitive military operations as “unacceptable.” And he was the sole House Republican to vote “no” on a bill to rename the Gulf of Mexico as the “Gulf of America.” He said he thought it was stupid.

Mr. Bacon’s willingness to publicly disagree with the president make him an anomaly in the tribal House Republican Conference, where members tend to fall in line behind Mr. Trump’s agenda and actively seek out ways to demonstrate their loyalty to him. In a Republican-led Congress that has been reluctant to challenge Mr. Trump on almost anything, the Nebraskan is among the last of a disappearing breed in his party. And his recent statements and actions strongly suggest he may be headed for the exits.

While Mr. Bacon has shown an independent streak in his statements, he still often backs down from his “red lines” on policy and votes with his party. After telling the White House that he would not vote for a bill that included more than $500 billion in Medicaid cuts, he ultimately voted “yes” for legislation carrying Mr. Trump’s domestic agenda that included far more.

And after telling The New York Times and House Republican leaders that he was a firm “no” on any cuts to a global anti-AIDS program, he ultimately voted “yes” this week on a package that would claw back $9 billion in spending already approved by Congress and targeted by the Department of Government Efficiency for cuts, including to the President’s Emergency Plan for AIDS Relief.

Still, he is more independent than most of his colleagues. In an interview in his office last week, Mr. Bacon, at 61, serving his fifth term in Congress, would not say whether he voted for Mr. Trump last year. He also likened members of his party to people following someone off a cliff, compared himself to Winston Churchill speaking out against Adolf Hitler in the 1930s, and criticized the billionaire tech tycoon Elon Musk, who has bankrolled many of his Republican colleagues.

“I sort of blame him for that disaster,” he said of Mr. Musk, referring to Mr. Musk’s exhorting Republicans late last year to tank a spending deal that was intended to avert a government shutdown. On one level, Mr. Bacon is making a fairly obvious statement: Mr. Musk did play a crucial role in killing the spending bill. But it is the kind of obvious statement that most Republicans on Capitol Hill are not willing to make these days, for fear of jeopardizing their political futures as Mr. Musk has threatened retribution against anyone who fails to vote the way he believes they should.

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Kenny Holston/The New York Times

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Meeaaaoow rises like a question mark before dawn. Anyone living with a cat knows their sounds: broken chirrups like greetings, low growls that warn, purrs stitched into sleepy conversation. Ethologists have organized feline sounds that share acoustic and contextual qualities into more than 20 groupings, including the meow, the hiss, the trill, the yowl, and the chatter. Any individual meow belongs, academically speaking, to a broad “meow” category, which itself contains many variations. The house cat’s verbal repertoire is far greater than that of its largely silent wild cousins. Researchers have even begun to study whether cats can drift into regional dialects, the way human accents bend along the Hudson or the Thames. And just as humans gesticulate, shrug, frown, and raise their eyebrows, cats’ fur and whiskers write subtitles: a twitching tail declares excitement, flattened ears signal fear, and a slow blink promises peace. Felis catus is a chatty species that, over thousands of years of domestication, has pivoted its voice toward the peculiar primate that opens the fridge. Now imagine pointing your phone at that predawn howl and reading: “Refill bowl, please.” Last December, Baidu—a Chinese multinational company that

specializes in Internet services and artificial intelligence—filed a patent application for what it describes as a method for transforming animal vocalizations into human language. (A Baidu spokesperson told Reuters last month that the system is “still in the research phase.”) The proposed system would gather animal signals and process them: it would store kitten or puppy talk for “I’m hungry” as code, then pair it not only with motion-sensing data such as tail swishes but also with vital signs such as heart rate and core temperature. All of these data would get whisked through an AI system and blended before emerging as plain-language phrases in English, Mandarin, or any other tongue.

The dream of decoding cat speech is much older than deep learning. By the early 20th century, meows had been recorded on wax cylinders, and in the 1970s John Bradshaw, a British anthrozoologist, began more than four decades of mapping how domestic cats tell us—and each other—what they mean. By the 1990s, he and his then doctoral student Charlotte Cameron-Beaumont had established that the distinct domestic “meow,” largely absent between adults in feral colonies, is a bespoke tool for managing humans. Even domestic cats rarely use it with each other, though kittens do with their mothers. Yet for all that anecdotal richness, the formal literature remained thin: there were hundreds of papers on bird song and dozens on dolphin whistles, but only a scattering on feline phonology until machine learning revived the field in the past decade.

One of the first hints that computers might crack the cat code came in 2018, when AI scientist Yagya Raj Pandeya and his colleagues released CatSound, a library of roughly 3,000 clips covering 10 types of cat calls labeled by the scientists, from hiss and growl to purr and mother call. Each clip went through software trained on musical recordings to describe a sound’s “shape”—how its pitch rose or fell and how long it lasted—and a second program cataloged them accordingly. When the system was tested on clips it hadn’t seen during training, it identified the right call type around 91 percent of the time. The study showed that the 10 vocal signals had acoustic fingerprints a machine can spot, giving researchers a proof of concept for automated cat-sound classification and eventual translation.

Momentum built quickly. In 2019 researchers at the University of Milan in Italy published a study focused on the one sound aimed squarely at Homo sapiens. The research sliced the meow into three situational flavors: “waiting for food,” “isolation in an unfamiliar environment,” and “brushing.” By turning each meow into a set of numbers, the researchers revealed that a “feed me” meow had a noticeably different shape from a “where are you?” meow or a “brush me” meow. After they trained a computer program to spot those shapes, the researchers tested the system much as Pandeya and colleagues had tested theirs: it was presented with meows not seen during training, all hand-labeled based on circumstances such as hunger or isolation. The system correctly identified the meows up to 96 percent of the time, and the research confirmed that cats really do tweak their meows to match what they’re trying to tell us.

The research was then scaled to smartphones, turning kitchen-table curiosity into consumer AI. Developers at software engineering company Akvelon, including a former Alexa engineer, teamed up with one of the study’s researchers to create the MeowTalk app, which they claim can translate meows in real time. MeowTalk has used machine learning to categorize thousands of user-submitted meows by common intent, such as “I’m hungry,” “I’m thirsty,” “I’m in pain,” “I’m happy,” or “I’m going to attack.” A 2021 validation study by MeowTalk team members claimed success rates near 90 percent. But the app also logs incorrect translation taps from skeptical owners, which serves as a reminder that the cat might be calling for something entirely different in reality. Probability scores can simply reflect pattern similarity, not necessarily the animal’s exact intent.

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People are not born racist. As former U.S. President Barack Obama, quoting Nelson Mandela, former president of South Africa, tweeted shortly after the tragic events in Charlottesville August 12, 2017 in which the university town was overtaken by white supremacists and hate groups, resulting in the killing of a counter protester, Heather Heyer, “No one is born hating another person because of the color of his skin or his background or his religion. People must learn to hate, and if they can learn to hate, they can be taught to love, for love comes more naturally to the human heart than its opposite.”

Very young children do not naturally choose friends based on the color of their skin. In a video created by the BBC children’s network CBeebies, Everyone’s Welcome, pairs of children explain the differences between themselves without referring to the color of their skin or ethnicity, even though those differences exist. As Nick Arnold writes in What Adults Can Learn About Discrimination From Kids, according to Sally Palmer, Ph.D., lecturer in the Department of Human Psychology and Human Development at University College London, it is not that they don’t notice the color of their skin, it is that the color of their skin is not what is important to them.

Racism is Learned

Racism is learned behavior. A 2012 study by Harvard University researchers showed that children as young as three years of age can adopt racist behavior when exposed to it, even though they may not understand “why.” According to renowned social psychologist Mazarin Banaji, Ph.D., children are quick to pick up on racist and prejudicial cues from adults and their environment. When white children were shown faces of different skin colors with ambiguous facial expressions, they showed a pro-white bias. This was determined by the fact that they ascribed a happy face to a perceived white skin color and an angry face to a face that they perceived to be black or brown. In the study, Black children who were tested showed no color-bias. Banaji maintains that racial bias can be unlearned, though, when children are in situations where they are exposed to diversity and they witness and are part of positive interactions between different groups of people acting as equals. 

Racism is learned by the example of one’s parents, caregivers, and other influential adults, through personal experience, and through the systems of our society that promulgate it, both explicitly and implicitly. These implicit biases permeate not only our individual decisions but also our societal structure. The New York Times has created a series of informative videos explaining implicit biases. 

There are Different Types of Racism

According to social science, there are seven main forms of racism: representational, ideological, discursive, interactional, institutional, structural, and systemic. Racism can be defined in other ways as well — reverse racism, subtle racism, internalized racism, colorism.

In 1968, the day after Martin Luther King was shot, the anti-racism expert and former third-grade teacher, Jane Elliott, devised a now-famous but then-controversial experiment for her all-white third-grade class in Iowa to teach the children about racism, in which she separated them by eye color into blue and brown, and showed extreme favoritism toward the group with blue eyes. She has conducted this experiment repeatedly for different groups since then, including the audience for an Oprah Winfrey show in 1992, known as The Anti-Racism Experiment That Transformed an Oprah Show. People in the audience were separated by eye color; those with blue eyes were discriminated against while those with brown eyes were treated favorably. The reactions of the audience were illuminating, showing how quickly some people came to identify with their eye color group and behave prejudicially, and what it felt like to be the ones who were being treated unfairly. 

Microaggressions are another expression of racism. As explained in Racial Microagressions in Everyday Life, “Racial microaggressions are brief and commonplace daily verbal, behavioral, or environmental indignities, whether intentional or unintentional, that communicate hostile, derogatory, or negative racial slights and insults toward people of color.” An example of microaggression falls under “assumption of criminal status” and includes someone crossing to the other side of the street to avoid a person of color. This list of microaggressions serves as a tool to recognize them and the messages they send. 

Unlearning Racism

Racism in the extreme is manifested by groups such as the KKK and other white supremacist groups. Christoper Picciolini is the founder of the group Life After Hate. Picciolini is a former member of a hate group, as are all the members of Life After Hate. On Face the Nation in Aug. 2017, Picciolini said that the people who are radicalized and join hate groups are “not motivated by ideology” but rather “a search for identity, community, and purpose.” He stated that “if there’s a brokenness underneath that person, they tend to search for those in really negative pathways.” As this group proves, even extreme racism can be unlearned, and the mission of this organization is to help counter violent extremism and to help those participating in hate groups find pathways out of them.

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Multi-ethnic young adults’ hands holding pieces from the same puzzle. Nullplus/E+/Getty Images

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Ole Ginnerup Schytz, an engineer in Denmark’s sleepy Vindelev agricultural area, had used a metal detector only a handful of times when he found a bent clump of metal in a friend’s barley field. He figured it was the lid from a container of tinned fish and tossed it in his junk bag with the other bits of farm trash that had set his metal detector beeping: rusty nails, screws, scrap iron. A few paces away he dug up another shiny circle. Someone had clearly enjoyed a lot of tinned fish here—into the sack it went. But when Ginnerup found a third metal round, he stopped to take a closer look. Wiping the mud from its surface, he suddenly found himself face-to-face with a Roman emperor. At that point he had to admit “they weren’t food cans,” Ginnerup recalls with a chuckle.

After a brief intermission for an online Teams meeting for work that December day in 2020, Ginnerup dug up 14 glittering gold disks—some as big as saucers—that archaeologists say were buried about 1,500 years ago, during a time of chaos after ash clouds from a distant volcanic eruption created a miniature ice age. Four medallions feature Roman emperors, and several bear intricate geometric patterns. But the real showstopper is an amulet called a bracteate with two stylized designs: a man in profile, his long hair pulled back in a braid, and a horse in full gallop. An expert in ancient runes says she was awestruck when she finally made out the inscription on top: “He is Odin’s man.”

These embossed runes are the oldest known written mention of Odin, the Norse god of war and ruler of Valhalla. Ginnerup’s bracteate, which archaeologists describe as the most significant Danish find in centuries, extended the worship of Odin back 150 years—and it’s all because Ginnerup received a metal detector as a birthday present from his father-in-law.

Many other European countries have prohibited or heavily restricted hobbyist metal detecting, but Denmark has embraced it, creating a system for members of the public to hand over finds to government archaeologists. The result has been an embarrassment of riches, with more than 20,000 items turned in annually in recent years. The curators assigned to identify and catalog the artifacts can’t dream of keeping up, but the fruits of their collective labor are clear: whereas neighboring countries have only vague sketches of the past, metal detectorists have filled in the ancient map of Denmark with temple complexes, trade routes and settlements that would have otherwise been lost to history.“

Private detectorists have rocketed Denmark ahead of its neighbors in archaeological research,” says Torben Trier Christiansen, curator of archaeology at Denmark’s North Jutland Museums. “There’s nothing ‘amateur’ about them.”

Denmark has been inhabited since the end of the last ice age, when nomadic hunter-gatherers from southern Europe arrived following the migration of reindeer and retreating glaciers as early as 12,500 years ago. The ancestors of modern ethnic Danes showed up some 5,000 years ago, journeying from the steppes of what is now Ukraine and southwestern Russia. Their descendants lived in small farming communities across Scandinavia for thousands of years, building megaliths and barrows for their honored dead and making human sacrifices in bogs to appease their gods.

In the early centuries of the common era, these farming communities coalesced into a series of Germanic tribes—the Cimbri, the Teutons, the Jutes, the Angles, and the Danes—who became skilled seafarers, explorers, and metalworkers. Because precious metals—including silver, gold, and the components of bronze—do not occur naturally in what is now Denmark, its denizens had to barter for or steal these metals from abroad. They traded extensively with the Roman Empire, which never reached as far north as Scandinavia.

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