Category: The Conversation – USA

Source: The Conversation – USA – By Mark Louie Ramos, Assistant Research Professor of Health Policy and Administration, Penn State

Should you believe the findings of scientific studies? Amid current concerns about the public’s trust in science, old arguments are resurfacing that can sow confusion.

As a statistician involved in research for many years, I know the care that goes into designing a good study capable of coming up with meaningful results. Understanding what the results of a particular study are and are not saying can help you sift through what you see in the news or on social media.

Let me walk you through the scientific process, from investigation to publication. The research results you hear about crucially depend on the way scientists formulate the questions they’re investigating.

The scientific method and the null hypothesis

Researchers in all kinds of fields use the scientific method to investigate the questions they’re interested in.

First, a scientist formulates a new claim – what’s called a hypothesis. For example, is having some genetic mutations in BRCA genes related to a higher risk of breast cancer? Then they gather data relevant to the hypothesis and decide, based on the data, whether that initial claim was correct or not.

It’s intuitive to think that this decision is cleanly dichotomous – that the researcher decides the hypothesis is either true or false. But of course, just because you decide something doesn’t mean you’re right.

If the claim is really false but the researcher decides, based on the evidence, it’s true – a false positive – they commit what’s called a Type 1 error. If the claim is really true but the researcher fails to see that – a false-negative conclusion – then they commit a Type 2 error.

Moreover, in the real world, it gets a little messier. It’s really hard to decide about the truth or falsity of a claim just based on what’s observed.

For that reason, most scientists employ what is called the null hypothesis significance testing framework. Here’s how it works: A researcher first states a “null hypothesis,” something that’s contrary to what they want to prove. For instance, in our example the null hypothesis is that BRCA genetic mutations are not associated with increased breast cancer occurrence.

The scientist still gathers data and makes a decision, but the decision is not about whether the null is true. Instead, a researcher decides whether there’s enough evidence to reject the null hypothesis or not.

What rejecting the null does and doesn’t mean

Understanding this distinction is crucial. Rejecting the null is equivalent in practice to acting as though it is false – in the example, rejecting the null means claiming that those with some BRCA gene mutations do have a higher risk of breast cancer. Along with other evidence, such as the size of the increased risk, this outcome can justify recommending early breast cancer screening for people with the identified BRCA mutations.

But failing to reject the null hypothesis doesn’t imply that it’s true – in this case, it doesn’t mean there is no association between the BRCA mutations and breast cancer. Rather, such a result is inconclusive; there’s not enough evidence to claim there is an association. A negative result – inadequate evidence to say the null is false – does not necessarily invite the researcher to believe the null is true.

This is because null hypothesis significance testing is set up to control for Type 1 error (false positive) at a level defined in advance by the researcher but at the cost of having less control over Type 2 error (false negative).

A researcher’s chances of correctly rejecting the null if there is increased risk can depend on how much data they have, how complex the design of the study is and, most importantly, how large the effect actually is. It’s much easier to reject the null if BRCA mutations truly increase cancer risk many times than it is if the risk is only slightly elevated. A researcher can end up with a result that is not statistically significant but cannot rule out the possibility of an increased risk that is too small for the study to detect.

Which results are more often publicized

Once they have their result and the researchers want to disseminate their work, they typically do so through peer-reviewed publication. Journal publishers consider a researcher’s write-up of their study, send it out for other scientists to review, and then decide whether to publish it.

In this process, the publishers tend to favor studies that rejected their null hypothesis over those that failed to reject it. This is called positive publication bias.

It is natural for publishers to prefer studies that support new claims since they objectively carry more information than studies that failed to reject their null hypothesis. Journals want to publish something new and noteworthy.

Many sources flag this phenomenon as “bad science,” but is it really? Remember, the framework used to make decisions about scientific claims is intentionally only capable of either rejecting the null hypothesis – in other words, supporting the claim – or alternatively declaring inconclusive results.

The framework isn’t designed to be able to prove the null hypothesis. That said, researchers can reverse the design of a scientific investigation so that a previous claim becomes the null hypothesis in a new study with fresh data.

For instance, rather than a null hypothesis that there is no association between BRCA mutations and breast cancer, the null hypothesis becomes that the increased breast cancer risk from BRCA mutations is equal to or greater than some value the researcher settles on before gathering fresh data.

Rejecting the null this time would mean the increased risk is smaller than that set value, thus supporting the claim consistent with what had previously been the null hypothesis on prior data. In the example, rejecting the null means the effect of BRCA genes is small enough to be practically negligible in terms of developing breast cancer.

It’s critical for a researcher to structure their study so that what they’re interested in proving is aligned with the rejection of the null. Publishers are naturally less inclined to consider studies that failed to reject their null hypothesis, not because they do not want to publish studies that support negative statements but because null hypothesis significance testing does not actually support negative statements. Failure to reject the null just means your results are inconclusive – and may perhaps seem less newsworthy.

What positive publication bias does

So what does the practice of preferring to publish studies that reject their null hypothesis do?

While we can’t know for certain, we can see how this plays out under different circumstances. You can explore the scenarios in this app I made.

If scientists are acting in good faith, using null hypothesis significance testing appropriately, it turns out that positive publication bias on the part of scientific journal publishers will increase the proportion of true discoveries in their pages much more than it will increase the proportion of false positives.

If editors did not exercise any positive publication bias, journals would be almost entirely full of studies with inconclusive results.

Of course, if scientists are not acting in good faith and are just interested in getting published while ignoring proper use of statistical tests, that can lead to false-positive rates being as high or higher than the rate of true discoveries. But this possibility is true even without positive publication bias.

Mark Louie Ramos does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. Absence of evidence is not evidence of absence – and that affects what scientific journals choose to publish – https://theconversation.com/absence-of-evidence-is-not-evidence-of-absence-and-that-affects-what-scientific-journals-choose-to-publish-264854

Source: The Conversation – USA – By Gregory A. Daddis, Professor and Melbern G. Glasscock Endowed Chair in American History, Texas A&M University

In an unprecedented step, the Department of Defense announced online on Nov. 24, 2025, that it was reviewing statements by U.S. Sen. Mark Kelly, a Democrat, who is a retired Navy captain, decorated combat veteran and former NASA astronaut.

Kelly and five other members of Congress with military or intelligence backgrounds told members of the armed forces “You can refuse illegal orders” in a video released on Nov. 18, reiterating oaths that members of the military and the intelligence community swear to uphold and defend the Constitution. The legislators said they acted in response to concerns expressed by troops currently serving on active duty.

President Donald Trump called the video “seditious behavior, punishable by death.”

Retired senior officers like Kelly can be recalled to duty at any time, which would make it possible for the Pentagon to put Kelly on trial under the Uniform Code of Military Justice, although the Defense Department announcement did not specify possible charges. Defense Secretary Pete Hegseth wrote online that “Kelly’s conduct brings discredit upon the armed forces and will be addressed appropriately.”

This threat to punish Kelly is just the latest move by the Trump administration against perceived enemies at home. By branding critics and opponents as disloyal, traitorous or worse, Trump and his supporters are resurrecting a playbook that hearkens back to Sen. Joseph McCarthy’s crusade against people he portrayed as domestic threats to the U.S. in the 1950s.

As a historian who studies national security and the Cold War era, I know that McCarthyism wrought devastating social and cultural harm across our nation. In my view, repeating what I believe constitutes social and political fratricide could be just as harmful today, perhaps even more so.

Targeting homegrown enemies

In the late 1940s and early 1950s, many Americans believed the United States was a nation under siege. Despite their victory in World War II, Americans saw a dangerous world confronting them.

The communist-run Soviet Union held Eastern Europe in an iron grip. In 1949, Mao Zedong’s communist troops triumphed in the bloody Chinese civil war. One year later, the Korean peninsula descended into full-scale conflict, raising the prospect of World War III – a frightening possibility in the atomic era.

Anti-communist zealots in the U.S., most notably Wisconsin Republican Sen. McCarthy, argued that treasonous Americans were weakening the nation at home. During a February 1950 speech in Wheeling, West Virginia, McCarthy asserted that “the traitorous actions of those who have been treated so well by this nation” were undermining the United States during its “final, all-out battle” against communism.

When communist forces toppled China’s government, critics such as political activist Freda Utley lambasted President Harry Truman’s administration for what they cast as its timidity, blundering and, worse, “treason in high places.” Conflating foreign and domestic threats, McCarthy claimed without evidence that homegrown enemies “within our borders have been more responsible for the success of communism abroad than Soviet Russia.”

As ostensible proof, the senator pointed to American lives being lost in Korea and argued that it was possible to “fully fight a war abroad and at the same time … dispose of the traitorous filth and the Red vermin which have accumulated at home.”

Political opponents might disparage McCarthy for his “dishonest and cowardly use of fractional fact and innuendo,” but the Wisconsinite knew how to play to the press. Time and again, McCarthy would bombastically lash out against his critics as he did with columnist Drew Pearson, calling him “an unprincipled liar,” “a fake” and the owner of a “twisted perverted mentality.”

While McCarthy focused on allegedly disloyal government officials and media journalists, other self-pronounced protectors of the nation sought to warn naive members of the public. Defense Department pamphlets like “Know Your Communist Enemy” alerted Americans against being duped by Communist Party members skilled in deception and manipulation.

Virulent anti-communists denounced what they viewed as inherent weaknesses of postwar American society, with a clearly political bent. Republicans asserted that cowardly, effeminate liberals were weakening the nation’s defense by minimizing threats both home and abroad.

Censure and worse

In such an anxiety-ridden environment, “red-baiting” – discrediting political opponents by linking them to communism – spread across the country, leaving a trail of wrecked lives. From teachers to public officials, anyone deemed un-American by McCarthyites faced public censure, loss of employment or even imprisonment.

Under the 1940 Smith Act, which criminalized promoting the overthrow of the U.S. government, hundreds of Americans were prosecuted during the Cold War simply for having been members of the Communist Party of the United States. The act also authorized the “deportation of aliens,” reflecting fears that communist ideas had seeped into nearly all facets of American society.

The 1950 Internal Security Act, widely known as the McCarran Act, further emphasized existential threats from within. “Disloyal aliens,” a term the law left purposefully vague, could have their citizenship revoked. Communist Party members were required to register with the government, a step that made them susceptible to prosecution under the Smith Act.

Immigrants could be detained or deported if the president declared an “internal security emergency.” Advocates called this policy “preventive detention,” while critics derided the act as a “Concentration Camp Law,” in the words of historian Masumi Izumi.

Scapegoating outsiders

The scaremongering wasn’t just about people’s political views: Vulnerable groups, such as gay people, were also targeted. McCarthy warned of links between “communists and queers,” asserting that “sexual perverts” had infested the U.S. government, especially the State Department, and posed “dangerous security risks.” Closeted gay or lesbian employees, the argument went, were vulnerable to blackmail by foreign governments.

Fearmongering also took on a decidedly racist tone. South Carolina Governor George Bell Timmerman, Jr., for instance, argued in 1957 that enforcing “Negro voting rights” would promote the “cause of communism.”

Three years later, a comic book titled “The Red Iceberg” insinuated that communists were exploiting the “tragic plight” of Black families and that the NAACP, a leading U.S. civil rights advocacy group, had been infiltrated by the Kremlin. Conservatives like Arizona Sen. Barry Goldwater criticized the growing practice of using federal power to enforce civil rights, calling it communist-style social engineering.

A new McCarthyism

While it’s never simple to draw neat historical parallels from past eras to the present, it appears McCarthy-like actions are recurring widely today. During the Red Scare, the focus was on alleged communists. Today, the focus is on straightforward dissent. Critics, both past and present, of President Donald Trump’s actions and policies are being targeted.

At the national level, Trump has called for using military force against “the enemy from within.” On Sept. 30, 2025, Trump told hundreds of generals and admirals who had been called to Quantico, Virginia, from posts around the world that the National Guard should view America’s “dangerous cities as training grounds.”

The Trump administration is making expansive use of the McCarran Act to crack down on immigrants in U.S. cities. White House adviser Stephen Miller has proposed suspending the constitutionally protected writ of habeas corpus, which entitles prisoners to challenge their detentions in court, in order to deport “illegal aliens,” alleging that the U.S. is “under invasion.”

In my home state of Texas, political fearmongering has taken on an equally McCarthyesque tone, with the Legislature directing the State Board of Education to adopt mandatory instruction on “atrocities attributable to communist regimes.”

Perhaps it is unsurprising, then, that right-wing activist Laura Loomer has unapologetically called for “making McCarthy great again.”

Disagreement is democratic

The history of McCarthyism shows where this kind of action can lead. Charging political opponents with treason and calling the media an “enemy of the people,” all without evidence, undercuts democratic principles.

These actions cast certain groups as different and dehumanize them. Portraying political rivals as existential threats, simply for disagreeing with their fellow citizens or political leaders, promotes forced consensus. This diminishes debate and can lead to bad policies.

Americans live in an insecure world today, but as I see it, demonizing enemies won’t make the United States a safer place. Instead, it only will lead to the kind of harm that was brought to pass by the very worst tendencies of McCarthyism.

Gregory A. Daddis does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. Pentagon investigation of Sen. Mark Kelly revives Cold War persecution of Americans with supposedly disloyal views – https://theconversation.com/pentagon-investigation-of-sen-mark-kelly-revives-cold-war-persecution-of-americans-with-supposedly-disloyal-views-265964

Source: The Conversation – USA – By Andrew Cowell, Professor of Linguistics, University of Colorado Boulder

I was hired at the University of Colorado Boulder in 1995 as a language professor. I relocated from Hawaii, where I had learned the Hawaiian language.

When I arrived in Colorado, I decided I needed to learn about the Indigenous language of the Boulder and Denver area, Arapaho. The Arapaho people had occupied the area for many years until they were forced to leave in the 1860s.

I first visited the Northern Arapaho people on the Wind River Reservation in Wyoming in 1999. At that time, there were hundreds of speakers of the Arapaho language.

Today, there are less than 100, and all are over the age of 70.

The Arapaho people in Wyoming and Colorado believe their language can still survive, and so do I. That’s why I am working to combine decades of language documentation with new technological approaches in order to help revive the language.

Loss of Native languages

Many Native American languages currently have few Native speakers, and the speakers are typically the oldest members of the community. The languages of the Wichita and Kansa people, for example, are among many that are no longer spoken at all.

Native American languages have been in decline in the face of Euro-American pressure for centuries.

On the Great Plains, this decline accelerated after World War II when Native soldiers came home after seeing prosperity off the reservation.

Arapaho elders tell me that bilingual parents decided to speak only English to their children to improve their chances of success in life. They were certain the tribal languages would come “later.”

But “later” didn’t happen. Boarding schools had already been suppressing the language, and now economic improvements brought cars, radios and televisions to Wind River, further promoting the use of English. Without language exposure in the home, children were not able to acquire good speaking abilities.

Today, however, tribal communities around the country increasingly want to maintain or reacquire their languages. Efforts to do this have been going on for several decades, with some successes, such as the Mohawk language of New York and Canada, Cherokee in Oklahoma and North Carolina and the Blackfoot language of northern Montana.

In most places however, numbers of Native speakers continue to decline, while learning among younger speakers progresses slowly.

Uses of data for curriculum

My early work focused on documenting the Arapaho language. Past linguists working with Native languages typically focused on traditional storytelling, as well as audio-recorded data. But my interest in anthropology led me to focus on conversation and everyday interaction. I also recorded on video to capture social settings, gestures and sign language. And to better understand the role of the language in daily use, I worked to become a good speaker myself.

I have compiled my documentation into a database that contains over 100,000 sentences of natural Arapaho speech. All of this has been transcribed, translated into English and accompanied by detailed linguistic analysis.

The database is further supported by an online learning site and an online dictionary of around 25,000 entries. They are among the largest such resources for an Indigenous language, though resources do exist for other languages, such as Yurok.

From documentation to curriculum

In response to the Arapaho people’s goal of language revitalization, my own work has shifted from documentation to assisting teachers, students and curriculum developers. The database turns out to have great value in this area.

Adult learners can watch the videos along with the Arapaho transcriptions or English translations, or both, and review the detailed grammatical analysis.

However, it is quite difficult for young learners to immediately benefit from listening to natural discourse. That’s why carefully graded curricula are crucial. Unlike for commonly taught languages such as French or Spanish, materials for most Native American languages are just being developed.

Arapaho can be challenging to learn because its structure is quite different from English. Many small chunks of meaning are combined to produce long, complex words. For example, an English speaker can start with “happy” and produce “un-happi-ness.” Arapaho speakers typically add three, four or even five prefixes, and multiple suffixes as well. A speaker can say the word “niibeetwonwoteekoohunoo” – which has six separate meaningful chunks. This translates to English, “I want to go and drive to town.”

There is little value in memorizing such complex words, just as English learners don’t memorize entire sentences. Instead, Arapaho learners need to understand the separate parts, and how they combine.

Previous efforts have succeeded in teaching children to speak basic Arapaho. The challenge now is to keep improving their Arapaho language abilities, using a graded curriculum that continues through all school levels.

The database can identify and label the individual chunks of words, and assign meanings to each chunk. A beginner’s dictionary of 1,300 entries has been created by calculating the overall frequency of base words in the 100,000 sentences, and then selecting only the most common ones.

The list has been broken down further to produce target vocabulary for each grade level. Smaller chunks of prefixes and suffixes are also measured, and sequential grammar-learning goals can be produced based on frequency and complexity.

A draft Arapaho learning sequence has been created, with 44 stages. It is now possible for the first time to produce a full, progressive language curriculum for Arapaho. The next step is to develop more curricular materials and train teachers to use them.

The sequence of 44 stages is now being introduced at Wyoming Indian Elementary School, the first school on the Wind River Reservation to pioneer dual-language classrooms.

Limitations of technology

Technology is not a magic bullet, however. Only Native people can save their languages, by choosing to learn and speak them.

Because artificial intelligence works using large language models, it needs billions of words of discourse to be trained effectively in a language. No Indigenous language has nearly that amount of data, so the capacity of AI to address Native language endangerment is limited. Moreover, many Indigenous communities are wary of AI due to concerns over data sovereignty and cultural property rights.

My own old-fashioned experience as a learner and teacher has proved crucial. I can see where difficulties lie for learners, and how to fine-tune computational measurements and predictions. I’ve learned that success in helping revitalize Native languages depends on researchers building long-term relationships with Native peoples and, ideally, speaking Native languages. Only then can new technologies be applied most productively.

Andrew Cowell currently receives funding from National Science Foundation. Past funding related to the work described here has come from the American Council of Learned Societies and Hans Rausing Endangered Language Documentation Programme.

He has received compensation from elements of the Northern Arapaho Tribe and the Southern Cheyenne and Arapaho Tribe for some of his assistance and consultation.

– ref. A database could help revive the Arapaho language before its last speakers are gone – https://theconversation.com/a-database-could-help-revive-the-arapaho-language-before-its-last-speakers-are-gone-269592

Source: The Conversation – USA (3) – By Joslyn Brenton, Assistant Professor of Sociology, Ithaca College

The 2025 government shutdown drew widespread attention to how many Americans struggle to get enough food. For 43 days, the more than 42 million Americans who receive Supplemental Nutrition Assistance Program benefits had to find other ways to stock their cupboards.

When asked how she felt about her benefits being suspended, one woman in West Virginia told a New York Times reporter, “We’re angry. Because we do count!”

Her sentiment reflects an often underappreciated fact about food. Food is not just a matter of survival. What and how you eat is also a symbol of your social status. Being unable to reliably feed your family healthy and nutritious foods in a way that aligns with your values can feel undignified. It can make people feel unseen and less important than others.

As researchers who study food inequality, nutrition and food justice, we have spent decades surveying and interviewing Americans about how they eat. We have witnessed firsthand how food assistance does help people meet their basic needs, but how it can also be stigmatizing and diminish their sense of dignity.

We have also studied alternatives to typical charitable food programs that, despite good intentions, tend to induce shame. We have learned that it is possible to help people put food on the table while preserving their dignity.

Dignity and food assistance

Addressing the root causes of food insecurity – what happens when people lack steady access to the food they need for a nutritious diet that’s in keeping with their preferences – is a persistent problem in the United States.

Thus, the demand for SNAP benefits, which help Americans buy groceries, other government nutrition programs, and food banks and food pantries rarely declines much – even when the economy is strong. Yet relying on food assistance programs does not tend to support a healthy diet and can take a toll on mental health.

As interviewers and clinicians, we have heard mothers describe the shame they feel when SNAP benefits do not cover the entire grocery bill. We have witnessed the frustration that comes with walking down a food pantry aisle lined with signs instructing hungry people to “take only 1 item!”

“The stuff looks like almost trash, but they give it to you,” one woman we interviewed said of her experience with food pantries and the like.

These kinds of stories are not uncommon. Charitable food programs receive leftover items from grocery stores, donations from community food drives and local businesses, and sometimes surplus from local farms. Food is often damaged in transport or from being handled too many times. A review of the research found that many people who use food pantries described the food as unhealthy, moldy or inedible. Being given unhealthy and unappealing food in a time of need is a double burden.

While free food may fill the stomach, it does not satisfy the desire to feel fully human and worthy of nourishment.

People who visit food banks have told researchers that they have come to expect low-quality food and few choices. When food aid is provided that way, it can leave the people it is supposed to help feeling powerless and ashamed.

These indignities are compounded by the fact that people who visit food banks and food pantries routinely face suspicion and surveillance around what they buy and how they eat, intensifying the stress associated with food insecurity.

In our research, we saw cashiers hovering over mothers using SNAP EBT cards in the self-checkout line. Politicians routinely suggest that SNAP is corrupt, contributing to nationwide perceptions that people who rely on this program are unfairly gaming the system. One study found that more than two-thirds of the Americans people who get food assistance have been the target of hostile comments and interactions from strangers at the grocery store.

Minimizing stigma

Several studies have shown that food programs do not need to sacrifice dignity to offer help. Programs that offer opportunities for people with lower incomes to receive and give back are important.

In Canada, bulk-buying food cooperatives did just that. Food assistance programs confer dignity when they make people feel good. People seeking help feel more satisfied after visiting food pantries that keep convenient hours or offer fresh produce.

SNAP has also tried to promote client dignity by ensuring that benefits are accepted in major grocery stores and distributing the funds to debit cards, allowing people to look and feel like everyday shoppers.

Yet despite these efforts social stigma persists. People who are enrolled in the SNAP program are still routinely devalued and judged for being poor in a society that assigns social value and worth based on one’s position on the economic ladder.

Cultivating dignity in food assistance

Minimizing stigma improves food assistance. Intentionally cultivating food dignity may be the next step.

Our assessment of a nationwide meal kit program demonstrated how dignity can be cultivated when food assistance programs consider the nutritional, emotional, aesthetic and cultural dimensions of food and eating.

In 2021, we conducted 116 interviews with participants of a meal kit program called Pass the Love. The program was free and anyone could enroll, no questions asked. The meal kits contained the necessary food and recipes to make three vegetarian meals a week, such as sesame coconut noodle salad or carrot coconut dal with rice. The program ran for four consecutive weeks.

When we interviewed participants about their experiences during and after the program, we learned that while they were thankful for the free food, what mattered more was the high quality, how it was packaged and how it conveyed care and respect.

Most participants had incomes at or well below the poverty line. They described what we came to call a “high dignity food experience,” meaning that it generated positive feelings and a sense of worth.

Opening the nicely packaged meal kit boxes each week felt like “Christmas,” to some people and a “gift” to others. Many found the “thought and care” that went into the program remarkable. Offering high-quality food to make nutritious, complete meals symbolized that low-income or food-insecure people deserve to eat well and feel good.

Our research, like similar studies that others have conducted, shows that treating food as a basic human right requires more than just giving people something to eat. It means ensuring unconditional access to the culturally appropriate fresh and nutritious food people need to thrive not just physically, but psychologically and socially.

Joslyn Brenton received funding from Partnership for a Healthier America as an external research expert.

Dr. Virudachalam received funding from the Edna G. Kynett Memorial Foundation, Rite Aid Foundation, and Partnership for a Healthier America in the last 36 months. She is a member of The Food Trust Board of Directors, the National Produce Prescription Collaborative Steering Committee, and Philadelphia City Council’s Food and Nutrition Security Task Force.

Alyssa Tindall does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. How food assistance programs can feed families and nourish their dignity – https://theconversation.com/how-food-assistance-programs-can-feed-families-and-nourish-their-dignity-269171

Source: The Conversation – USA (3) – By Christina Hymer, Assistant Professor of Management and Entrepreneurship, University of Tennessee

When you picture Santa Claus, a white, bearded, overweight and jolly man who dashes around delivering gifts to children during the Christmas season probably comes to mind. Yet, not everyone who dons the red suit fits this stereotype.

That’s what Bethany Cockburn, Borbala Csillag and I learned when we teamed up to study professional Santas. For our study, we looked into how these professional Santas were able to “be” Santa, even if they didn’t fully fit the image.

As we explained in a forthcoming article in the Academy of Management Journal, many who do this work don’t see it as just a job – it’s a calling. For some professional Santas, it’s especially important that they look and feel like Santa to experience that sense of purpose in their work.

We surveyed 849 professional Santas who live across the U.S. and interviewed 53 of them, collecting data between 2018 and 2021. We identified three types of professional Santas: prototypical (64%), semi-prototypical (23%) and nonprototypical (13%).

Prototypical Santas look the part. They are white and overweight, have real beards and express confidence that they are the right fit.

Semi-prototypical Santas looked the part, too, but felt like they weren’t quite suitable for a range of reasons. They might be introverted or use a fake beard.

Nonprototypical Santas had characteristics at odds with the stereotype. They might be nonwhite, female or gay, or have a physical disability.

Whereas prototypical Santas could easily slide into the Santa role, the process was more complex for the others.

Semi-prototypical Santas did things like come up with stories they’d tell themselves or share with children to explain away their fake beards. Nonprototypical Santas had values aligned with the Santa image, such as being peaceful, loving and kind. But they still made a big effort to look like what people expect when they visit a Santa.

“Should it be a difference if you’re a Jewish Santa Claus or a Catholic Santa Claus?” asked an atheist professional Santa we called “Santa Aquila.” “No. You’re Santa Claus. What do you do? You’re not even supposed to preach anything.”

Another Santa whom we called “Santa Lynx” hid that she was female in part by flattening her chest.

Why it matters

While anyone can take a turn being their neighborhood potluck’s Santa, the one you meet at the mall probably attended some combination of Santa schools, webinars and training.

For instance, the Charles W. Howard Santa Claus School was founded in 1937 and conducts an annual Santa training each year. National networks also exist, such as the Fraternal Order of Real Bearded Santas, which says it has 1,000 members, – and the IBRBS, formerly known as the International Brotherhood of Real Bearded Santas, offering meetups and professional support.

There are also local organizations, such as the Lone Star Santas network in Texas.

Although most professional Santas are paid for their work, many do this voluntarily.

It’s not uncommon for there to be some sort of expectation around who should have a particular occupation. Pilots tend to be male, most schoolteachers are female, and salespeople are often seen as extroverted.

But that doesn’t mean that women can’t be pilots, men can’t be teachers or that introverts can’t work in sales.

What’s next

I’m now looking at how broader institutional environments, current events and social movements can shape how people experience their callings and find meaning at work.

The Research Brief is a short take on interesting academic work.

Christina Hymer does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. What makes a true Santa is inside – and comes with the red suit – https://theconversation.com/what-makes-a-true-santa-is-inside-and-comes-with-the-red-suit-269569

Source: The Conversation – USA – By Ray Brescia, Associate Dean for Research and Intellectual Life, Albany Law School

A federal judge on Nov. 24, 2025, dismissed the indictments against former FBI Director James B. Comey and New York Attorney General Letitia James, blocking the Department of Justice’s efforts to prosecute two of President Donald Trump’s perceived adversaries.

But U.S. District Judge Cameron McGowan Currie qualified her dismissals, saying she did so “without prejudice.”

What does that legal term mean?

Unaddressed charges

In her ruling, Currie concluded that the appointment of interim U.S. Attorney Lindsey Halligan, who filed the cases against Comey and James, was unlawful. Currie wrote:

“Because Ms. Halligan had no lawful authority to present the indictment, I will grant Mr. Comey’s motion and dismiss the indictment without prejudice.”

She wrote the same about the case against James.

Currie’s “without prejudice” reference means the dismissal did not address what legal scholars like me call the merits or substance of the underlying criminal charges.

A “without prejudice” dismissal is legalese for “you can try again if you can fix the problems with your case.” Had the judge ruled that the dismissals were “with prejudice,” that would have meant the government could not have brought the cases again.

Here’s what prosecutors would need to fix to be able to bring cases against Comey and James again.

Federal law provides that whenever a U.S. attorney’s position is vacant, the attorney general may appoint an interim U.S. attorney for a period of 120 days. At the end of that period, it’s up to the federal judges of the district where that position is vacant to appoint someone to continue in that role unless and until the president nominates, and the Senate confirms, a U.S. attorney through the normal appointments process.

The Trump administration appointed Halligan’s predecessor, U.S. Attorney Erik Siebert, in that interim role in January 2025. And when the 120 days from his appointment lapsed, the district judges of the Eastern District of Virginia selected him to continue on in his interim role.

Currie found that when Siebert resigned after his reappointment, that did not empower the Trump administration to appoint a new interim prosecutor. The power still resided with the District Court judges. Because of that, Halligan’s appointment and her efforts to secure the Comey and James indictments were void.

The end of the beginning

The Department of Justice can certainly appeal these rulings and could get them reversed on appeal, or it could refile them after a new U.S. attorney is named in accordance with law.

It may be too late for the case against Comey, however, because the statute of limitations on those charges has already run out. As Currie noted in her Comey ruling, while the statute of limitations is generally suspended when a valid indictment has been filed, an invalid indictment, like the one against Comey, would not have the same effect on the statute of limitations.

That means the time has likely run out on the claims against the former FBI director.

If Currie’s rulings stand, the Justice Department can’t just file the cases again, with Halligan still in this role, unless the Trump administration follows the procedures set forth in the law for her proper appointment.

While this is not the beginning of the end for these prosecutions, it is, at least, the end of the beginning.

Ray Brescia does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. ‘Without prejudice’: What this 2-word legalese means for the dismissed charges against James Comey and Letitia James – https://theconversation.com/without-prejudice-what-this-2-word-legalese-means-for-the-dismissed-charges-against-james-comey-and-letitia-james-270559

Source: The Conversation – USA (2) – By Daniel V. McGehee, Professor of Industrial and Systems Engineering, University of Iowa

Across state legislatures and in Congress, debates are intensifying about the value of funding certain college degree programs – and higher education, more broadly.

The growing popularity of professional graduate degrees over the past several decades – including programs in business administration and engineering management – has reshaped the economics of higher education. Unlike traditional academic graduate programs, which are often centered on research and scholarship, these professionally oriented degrees are designed primarily for workforce advancement and typically charge much higher tuition.

These programs are often expensive for students and are sometimes described as cash-cow degrees for colleges and universities, because the tuition revenue far exceeds the instructional costs.

Some universities and colleges also leverage their brands to offer online, executive or certificate-based versions of these programs, attracting many students from the U.S. and abroad who pay the full tuition. This steady revenue helps universities subsidize tuition for other students who cannot pay the full rate, among other things.

Yet a quiet tension underlies this evolution in higher education – the widening divide between practical, technical training and a comprehensive education that perhaps is more likely to encourage students to inquire, reflect and innovate as they learn.

An overlooked factor

Some states, including Texas, track salary data for graduates of every program to measure worth through short-term earnings. This approach may strike many students and their families as useful, but I believe it overlooks a part of what makes higher education valuable.

A healthy higher education system depends not only on producing employable graduates but also on cultivating citizens and leaders who can interpret uncertainty, question assumptions and connect ideas across disciplines.

When assessing disciplines such as English, philosophy, history and world languages, I think that we should acknowledge their contributions to critical thought, communication and ethical reasoning.

These academic disciplines encourage students to synthesize ideas, construct arguments and engage in meaningful debate. Some law schools often draw their strongest students from these backgrounds because they nurture analytical and rhetorical skills essential for navigating complex civic and legal issues.

Historically, poets and writers have often been among the first to be silenced by authoritarian regimes. It’s a reminder of the societal power of inquiry and expression that I believe higher education should protect.

Why students stay on narrow professional paths

Students entering college today face significant pressure to choose what they might see as safe majors that will result in a well-paying career. For aspiring physicians and engineers, the path is often scripted early by steering them toward physical and biosciences. High test scores, internships and other stepping stones are treated as nonnegotiable. Parents and peers can reinforce this mindset.

Most colleges and universities do not reward a future medical student who wants to major in comparative literature, or an engineering student who is spending time on philosophy.

Students’ majors also typically place course requirements on them, in addition to a school’s general course requirements. This often does not leave a lot of room for students to experiment with different classes, especially if they are pursuing vocationally focused majors, such as engineering.

As a result, I’ve seen many students trade curiosity for credentialing, believing that professional identity must come before intellectual exploration.

As someone who began my education in psychology and later transitioned into engineering, I have seen how different intellectual traditions approach the same human questions. Psychology teaches people to observe behavior and design experiments. Engineering trains students to model systems and optimize performance.

When combined, they help reveal how humans interact with technology and how technological solutions reshape human behavior.

In my view, these are questions neither field can answer alone.

Initiative is the missing ingredient

One of the most important and often overlooked ingredients in thriving high tech, medical and business environments is initiative. I believe students in the humanities routinely practice taking initiative by framing questions, interpreting incomplete information and proposing original arguments. These skills are crucial for scientific or business innovation, but they are often not emphasized in structured science, technology, engineering and mathematics – or STEM – coursework.

Initiative involves the willingness to move first and to see around corners, defining the next what-if, rallying others and building something meaningful even when the path is uncertain.

To help my engineering students practice taking initiative, I often give them deliberately vague instructions – something they rarely experience in their coursework. Many students, even highly capable ones, hesitate to take initiative because their schooling experience has largely rewarded caution and compliance over exploration. They wait for clarity or for permission – not because they lack ability, but because they are afraid to be wrong.

Yet in business, research labs, design studios, hospitals and engineering firms, initiative is the quality employers most urgently need and cannot easily teach. Broader educational approaches help cultivate this confidence by encouraging students to interpret ambiguity rather than avoid it.

How teaching can evolve

Helping all students develop a sense of initiative and innovation requires university leaders to rethink what success looks like.

Universities can begin with achievable steps, such as rewarding cross-disciplinary teaching and joint appointments in promotion and tenure criteria.

At the University of Iowa’s Driving Safety Research Institute, where our teams blend engineering, medicine, public health and psychology, students quickly learn that a safe automated vehicle is not just a technical system but also a behavioral one. Understanding how human drivers respond to automation is as important as the algorithms that govern the vehicle.

Other institutions are modeling this approach of integrating social, behavioral and physical sciences.

Olin College of Engineering, a school in Needham, Massachusetts, builds every project around both technical feasibility and human context. Courses are often co-taught by humanities and engineering professors, and projects require students to articulate not only what they built but why it matters.

Still, integrating liberal and technical education is difficult in practice. Professional curricula often overflow with accreditation requirements. Faculty incentives reward specialization more than collaboration. Students and parents, anxious about debt and job security, hesitate to spend credits outside of a student’s major.

Rethinking what success means

I believe that higher education’s purpose is not to produce uniform workers but adaptable thinkers.

It might not be productive to center conversations about defending the liberal arts or glorifying STEM. Rather, I think that people’s focus should be on recognizing that each field is incomplete without the other.

Education for a complex world must cultivate depth, initiative and perspective. When students connect disciplines, question assumptions and act with purpose, they are prepared not only for their first job but for a lifetime of learning and leadership.

Daniel V. McGehee does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. Colleges teach the most valuable career skills when they don’t stick narrowly to preprofessional education – https://theconversation.com/colleges-teach-the-most-valuable-career-skills-when-they-dont-stick-narrowly-to-preprofessional-education-270025

Source: The Conversation – USA – By Wei Zhai, Associate Professor of Public Affairs and Planning, University of Texas at Arlington

When city leaders talk about making a town “smart,” they’re usually talking about urban digital twins. These are essentially high-tech, 3D computer models of cities. They are filled with data about buildings, roads and utilities. Built using precision tools like cameras and LiDAR – light detection and ranging – scanners, these twins are great at showing what a city looks like physically.

But in their rush to map the concrete, researchers, software developers and city planners have missed the most dynamic part of urban life: people. People move, live and interact inside those buildings and on those streets.

This omission creates a serious problem. While an urban digital twin may perfectly replicate the buildings and infrastructure, it often ignores how people use the parks, walk on the sidewalks, or find their way to the bus. This is an incomplete picture; it cannot truly help solve complex urban challenges or guide fair development.

To overcome this problem, digital twins will need to widen their focus beyond physical objects and incorporate realistic human behaviors. Though there is ample data about a city’s inhabitants, using it poses a significant privacy risk. I’m a public affairs and planning scholar. My colleagues and I believe the solution to producing more complete urban digital twins is to use synthetic data that closely approximates real people’s data.“

The privacy barrier

To build a humane, inclusive digital twin, it’s critical to include detailed data on how people behave. And the model should represent the diversity of a city’s population, including families with young children, disabled residents and retirees. Unfortunately, relying solely on real-world data is impractical and ethically challenging.

The primary obstacles are significant, starting with strict privacy laws. Rules such as the European Union’s General Data Protection Regulation, or GDPR, often prevent researchers and others from widely sharing sensitive personal information. This wall of privacy stops researchers from easily comparing results and limits our ability to learn from past studies.

Furthermore, real-world data is often unfair. Data collection tends to be uneven, missing large groups of people. Training a computer model using data where low-income neighborhoods have sparse sensor coverage means the model will simply repeat and even magnify that original unfairness. To compensate for this, researchers can use the statistical technique of weighting the data in the models to make up for the underrepresentation.

Synthetic data offers a practical solution. It is artificial information generated by computers that mimics the statistical patterns of real-world data. This protects privacy while filling critical data gaps.

Synthetic data: Tool for fairer cities

Adding synthetic human dynamics fundamentally changes digital twins. It shifts them from static models of infrastructure to dynamic simulations that show how people live in the city. By generating synthetic patterns of walking, bus riding and public space use, planners can include a wider, more inclusive range of human actions in the models.

For example, Bogotá, Colombia, is using a digital twin to model its TransMilenio bus rapid transit system. Instead of relying only on limited or privacy-sensitive real-world sensor data, the city planners generated synthetic data to fill the digital twin. Such data artificially creates millions of simulated bus arrivals, vehicle speeds and queue lengths, all based on the statistical patterns – peak times, off-peak times – of actual TransMilenio operations.

This approach transforms urban planning in several crucial ways, making simulations more realistic and diverse. For example, planners can use synthetic pedestrian data to model how elderly and disabled residents would navigate a new urban design.

It also allows for risk-free testing of ideas. Planners can simulate diverse synthetic populations to see how a new flood evacuation plan would affect various groups, all without risking anyone’s safety or privacy in the real world.

Making digital twins trustworthy

For all the promises of synthetic data, it can only be helpful if planners can trust it. Since they base major decisions on these virtual worlds, the synthetic data must be proved to be a reliable replacement for real-world data. Planners can test this by checking to see if the main policy decisions they reach using the synthetic data are the same ones they would have made using real-world data that puts people’s privacy at risk. If the decisions match, the synthetic data is trustworthy enough to use for that planning task going forward.

Beyond technical checks, it’s important to consider fairness. This means routinely auditing the synthetic models to check for any hidden biases or underrepresentation across different groups. For example, planners can make sure an emergency evacuation plan in the urban digital twin works for elderly residents with mobility issues.

Most importantly, I believe planners should include their communities. Establishing citizen advisory boards and designing the synthetic data and simulation scenarios directly with the people who live in the city helps ensure that their experiences are accurately reflected.

By moving beyond static infrastructure to dynamic environments that include people’s behavior, synthetic data is set to play a critical role in urban planning. It will shape the resilient, inclusive and human-centered urban digital twins of the future.

Wei Zhai receives funding from National Science Foundation.

– ref. From concrete to community: How synthetic data can make urban digital twins more humane – https://theconversation.com/from-concrete-to-community-how-synthetic-data-can-make-urban-digital-twins-more-humane-268847

Source: The Conversation – USA – By Deborah Lee, Professor and Director of Research Impact and AI Strategy, Mississippi State University

Three years ago, if someone needed to fix a leaky faucet or understand inflation, they usually did one of three things: typed the question into Google, searched YouTube for a how-to video or shouted desperately at Alexa for help.

Today, millions of people start with a different approach: They open ChatGPT and just ask.

I’m a professor and director of research impact and AI strategy at Mississippi State University Libraries. As a scholar who studies information retrieval, I see that this shift of the tool people reach for first for finding information is at the heart of how ChatGPT has changed everyday technology use.

Change in searching

The biggest change isn’t that other tools have vanished. It’s that ChatGPT has become the new front door to information. Within months of its introduction on Nov. 30, 2022, ChatGPT had 100 million weekly users. By late 2025, that figure had grown to 800 million. That makes it one of the most widely used consumer technologies on the planet.

Surveys show that this use isn’t just curiosity – it reflects a real change in behavior. A 2025 Pew Research Center study found that 34% of U.S. adults have used ChatGPT, roughly double the share found in 2023. Among adults under 30, a clear majority (58%) have tried it. An AP-NORC poll reports that about 60% of U.S. adults who use AI say they use it to search for information, making this the most common AI use case. The number rises to 74% for the under-30 crowd.

Traditional search engines are still the backbone of the online information ecosystem, but the kind of searching people do has shifted in measurable ways since ChatGPT entered the scene. People are changing which tool they reach for first.

For years, Google was the default for everything from “how to reset my router” to “explain the debt ceiling.” These basic informational queries made up a huge portion of search traffic. But these quick, clarifying, everyday “what does this mean” questions are the ones ChatGPT now answers faster and more cleanly than a page of links.

And people have noticed. A 2025 U.S. consumer survey found that 55% of respondents now use OpenAI’s ChatGPT or Google’s Gemini AI chatbots about tasks they previously would have asked Google search to help them with, with even higher usage figures for the U.K. Another analysis of more than 1 billion search sessions found that traffic from generative AI platforms is growing 165 times faster than traditional searches, and about 13 million U.S. adults have already made generative AI their go-to tool for online discovery.

This doesn’t mean people have stopped “Googling,” but it means ChatGPT has peeled off the kinds of questions for which users want a direct explanation instead of a list of links. Curious about a policy update? Need a definition? Want a polite way to respond to an uncomfortable email? ChatGPT is faster, feels more conversational and feels more definitive.

At the same time, Google isn’t standing still. Its search results look different than they did three years ago because Google started weaving its AI system Gemini directly into the top of the page. The “AI Overview” summaries that appear above traditional search links now instantly answer many simple questions – sometimes accurately, sometimes less so.

But either way, many people never scroll past that AI-generated snapshot. This fact combined with the impact of ChatGPT are the reasons the number of “zero-click” searches has surged. One report using Similarweb data found that traffic from Google to news sites fell from over 2.3 billion visits in mid-2024 to under 1.7 billion in May 2025, while the share of news-related searches ending in zero clicks jumped from 56% to 69% in one year.

Google search excels at pointing to a wide range of sources and perspectives, but the results can feel cluttered and designed more for clicks than clarity. ChatGPT, by contract, delivers a more focused and conversational response that prioritizes explanation over ranking. The ChatGPT response can lack the source transparency and multiple viewpoints often found in a Google search.

In terms of accuracy, both tools can occasionally get it wrong. Google’s strength lies in letting users cross-check multiple sources, while ChatGPT’s accuracy depends heavily on the quality of the prompt and the user’s ability to recognize when a response should be verified elsewhere.

Smart speakers and YouTube

The impact of ChatGPT has reverberated beyond search engines. Voice assistants, such as Alexa speakers and Google Home, continue to report high ownership, but that number is down slightly. One 2025 summary of voice-search statistics estimates that about 34% of people ages 12 and up own a smart speaker, down from 35% in 2023. This is not a dramatic decline, but the lack of growth may indicate a shift of more complex queries to ChatGPT or similar tools. When people want a detailed explanation, a step-by-step plan or help drafting something, a voice assistant that answers in a short sentence suddenly feels limited.

By contrast, YouTube remains a giant. As of 2024, it had approximately 2.74 billion users, with that number increasing steadily since 2010. Among U.S. teens, about 90% say they use YouTube, making it the most widely used platform in that age group. But what kind of videos people are looking for is changing.

People now tend to start with ChatGPT and then move to YouTube if they need the additional information a how-to video conveys. For many everyday tasks, such as “explain my health benefits” or “help me write a complaint email,” people ask ChatGPT for a summary, script or checklist. They head to YouTube only if they need to see a physical process.

You can see a similar pattern in more specialized spaces. Software engineers, for instance, have long relied on sites such as Stack Overflow for tips and pieces of software code. But question volume there began dropping sharply after ChatGPT’s release, and one analysis suggests overall traffic fell by about 50% between 2022 and 2024. When a chatbot can generate a code snippet and an explanation on demand, fewer people bother typing a question into a public forum.

So where does that leave us?

Three years in, ChatGPT hasn’t replaced the rest of the tech stack; it’s reordered it. The default search has shifted. Search engines are still for deep dives and complex comparisons. YouTube is still for seeing real people do real things. Smart speakers are still for hands-free convenience.

But when people need to figure something out, many now start with a chat conversation, not a search box. That’s the real ChatGPT effect: It didn’t just add another app to our phones – it quietly changed how we look things up in the first place.

Deborah Lee does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. The ChatGPT effect: In 3 years the AI chatbot has changed the way people look things up – https://theconversation.com/the-chatgpt-effect-in-3-years-the-ai-chatbot-has-changed-the-way-people-look-things-up-270143

Source: The Conversation – USA – By Alexey A. Petrov, Professor of physics and astronomy, University of South Carolina

Scientists working with the James Webb Space Telescope discovered three unusual astronomical objects in early 2025, which may be examples of dark stars. The concept of dark stars has existed for some time and could alter scientists’ understanding of how ordinary stars form. However, their name is somewhat misleading.

“Dark stars” is one of those unfortunate names that, on the surface, does not accurately describe the objects it represents. Dark stars are not exactly stars, and they are certainly not dark.

Still, the name captures the essence of this phenomenon. The “dark” in the name refers not to how bright these objects are, but to the process that makes them shine — driven by a mysterious substance called dark matter. The sheer size of these objects makes it difficult to classify them as stars.

As a physicist, I’ve been fascinated by dark matter, and I’ve been trying to find a way to see its traces using particle accelerators. I’m curious whether dark stars could provide an alternative method to find dark matter.

What makes dark matter dark?

Dark matter, which makes up approximately 27% of the universe but cannot be directly observed, is a key idea behind the phenomenon of dark stars. Astrophysicists have studied this mysterious substance for nearly a century, yet we haven’t seen any direct evidence of it besides its gravitational effects. So, what makes dark matter dark?

Humans primarily observe the universe by detecting electromagnetic waves emitted by or reflected off various objects. For instance, the Moon is visible to the naked eye because it reflects sunlight. Atoms on the Moon’s surface absorb photons – the particles of light – sent from the Sun, causing electrons within atoms to move and send some of that light toward us.

More advanced telescopes detect electromagnetic waves beyond the visible spectrum, such as ultraviolet, infrared or radio waves. They use the same principle: Electrically charged components of atoms react to these electromagnetic waves. But how can they detect a substance – dark matter – that not only has no electric charge but also has no electrically charged components?

Although scientists don’t know the exact nature of dark matter, many models suggest that it is made up of electrically neutral particles – those without an electric charge. This trait makes it impossible to observe dark matter in the same way that we observe ordinary matter.

Dark matter is thought to be made of particles that are their own antiparticles. Antiparticles are the “mirror” versions of particles. They have the same mass but opposite electric charge and other properties. When a particle encounters its antiparticle, the two annihilate each other in a burst of energy.

If dark matter particles are their own antiparticles, they would annihilate upon colliding with each other, potentially releasing large amounts of energy. Scientists predict that this process plays a key role in the formation of dark stars, as long as the density of dark matter particles inside these stars is sufficiently high. The dark matter density determines how often dark matter particles encounter, and annihilate, each other. If the dark matter density inside dark stars is high, they would annihilate frequently.

What makes a dark star shine?

The concept of dark stars stems from a fundamental yet unresolved question in astrophysics: How do stars form? In the widely accepted view, clouds of primordial hydrogen and helium — the chemical elements formed in the first minutes after the Big Bang, approximately 13.8 billion years ago — collapsed under gravity. They heated up and initiated nuclear fusion, which formed heavier elements from the hydrogen and helium. This process led to the formation of the first generation of stars.

In the standard view of star formation, dark matter is seen as a passive element that merely exerts a gravitational pull on everything around it, including primordial hydrogen and helium. But what if dark matter had a more active role in the process? That’s exactly the question a group of astrophysicists raised in 2008.

In the dense environment of the early universe, dark matter particles would collide with, and annihilate, each other, releasing energy in the process. This energy could heat the hydrogen and helium gas, preventing it from further collapse and delaying, or even preventing, the typical ignition of nuclear fusion.

The outcome would be a starlike object — but one powered by dark matter heating instead of fusion. Unlike regular stars, these dark stars might live much longer because they would continue to shine as long as they attracted dark matter. This trait would make them distinct from ordinary stars, as their cooler temperature would result in lower emissions of various particles.

Can we observe dark stars?

Several unique characteristics help astronomers identify potential dark stars. First, these objects must be very old. As the universe expands, the frequency of light coming from objects far away from Earth decreases, shifting toward the infrared end of the electromagnetic spectrum, meaning it gets “redshifted.” The oldest objects appear the most redshifted to observers.

Since dark stars form from primordial hydrogen and helium, they are expected to contain little to no heavier elements, such as oxygen. They would be very large and cooler on the surface, yet highly luminous because their size — and the surface area emitting light — compensates for their lower surface brightness.

They are also expected to be enormous, with radii of about tens of astronomical units — a cosmic distance measurement equal to the average distance between Earth and the Sun. Some supermassive dark stars are theorized to reach masses of roughly 10,000 to 10 million times that of the Sun, depending on how much dark matter and hydrogen or helium gas they can accumulate during their growth.

So, have astronomers observed dark stars? Possibly. Data from the James Webb Space Telescope has revealed some very high-redshift objects that seem brighter — and possibly more massive — than what scientists expect of typical early galaxies or stars. These results have led some researchers to propose that dark stars might explain these objects.

In particular, a recent study analyzing James Webb Space Telescope data identified three candidates consistent with supermassive dark star models. Researchers looked at how much helium these objects contained to identify them. Since it is dark matter annihilation that heats up those dark stars, rather than nuclear fusion turning helium into heavier elements, dark stars should have more helium.

The researchers highlight that one of these objects indeed exhibited a potential “smoking gun” helium absorption signature: a far higher helium abundance than one would expect in typical early galaxies.

Dark stars may explain early black holes

What happens when a dark star runs out of dark matter? It depends on the size of the dark star. For the lightest dark stars, the depletion of dark matter would mean gravity compresses the remaining hydrogen, igniting nuclear fusion. In this case, the dark star would eventually become an ordinary star, so some stars may have begun as dark stars.

Supermassive dark stars are even more intriguing. At the end of their lifespan, a dead supermassive dark star would collapse directly into a black hole. This black hole could start the formation of a supermassive black hole, like the kind astronomers observe at the centers of galaxies, including our own Milky Way.

Dark stars might also explain how supermassive black holes formed in the early universe. They could shed light on some unique black holes observed by astronomers. For example, a black hole in the galaxy UHZ-1 has a mass approaching 10 million solar masses, and is very old – it formed just 500 million years after the Big Bang. Traditional models struggle to explain how such massive black holes could form so quickly.

The idea of dark stars is not universally accepted. These dark star candidates might still turn out just to be unusual galaxies. Some astrophysicists argue that matter accretion — a process in which massive objects pull in surrounding matter — alone can produce massive stars, and that studies using observations from the James Webb telescope cannot distinguish between massive ordinary stars and less dense, cooler dark stars.

Researchers emphasize that they will need more observational data and theoretical advancements to solve this mystery.

Alexey A Petrov receives funding from the US Department of Energy.

– ref. When darkness shines: How dark stars could illuminate the early universe – https://theconversation.com/when-darkness-shines-how-dark-stars-could-illuminate-the-early-universe-266971