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Multiple goals, multiple solutions, plenty of second-guessing and revising − here’s how science really works

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theconversation.com – Soazig Le Bihan, Professor of Philosophy, of Montana – 2024-08-07 07:34:12

If your mental image of a scientist looks like this, you’re due for an update.

aluxum/E+ via Getty Images

Soazig Le Bihan, University of Montana

A man in a lab coat bends under a dim light, his strained eyes riveted onto a microscope. He’s powered only by caffeine and anticipation.

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This solitary scientist will stay on task until he unveils the truth about the cause of the dangerous disease quickly spreading through his vulnerable . Time is short, the stakes are high, and only he can save everyone. …

That kind of romanticized picture of science was standard for a long time. But it’s as far from actual scientific practice as a ‘s choreographed martial arts battle is from a real fistfight.

For most of the 20th century, philosophers of science like me maintained somewhat idealistic claims about what good science looks like. Over the past few decades, however, many of us have our views to better mirror actual scientific practice.

An update on what to expect from actual science is overdue. I often worry that when the public science to unrealistic standards, any scientific claim failing to up to them arouses suspicion. While public trust is globally strong and has been for decades, it has been eroding. In November 2023, Americans’ trust in scientists was 14 points lower than it had been just prior to the COVID-19 pandemic, with its flurry of confusing and sometimes contradictory science-related messages.

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When people’s expectations are not met about how science works, they may blame scientists. But modifying our expectations might be more useful. Here are three updates I think can help people better understand how science actually works. Hopefully, a better understanding of actual scientific practice will also shore up people’s trust in the process.

The many faces of scientific research

First, science is a complex endeavor involving multiple goals and associated activities.

Some scientists search for the causes underlying some observable effect, such as a decimated pine forest or the Earth’s global surface temperature increase.

Others may investigate the what rather than the why of things. For example, ecologists build models to estimate gray wolf abundance in Montana. Spotting predators is incredibly challenging. Counting all of them is impractical. Abundance models are neither complete nor 100% accurate – they offer estimates deemed good enough to set harvesting quotas. Perfect scientific models are just not in the cards.

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It can be tough enough to find treatments that mitigate symptoms, let alone gain a complete understanding of a disorder.

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Beyond the what and the why, scientists may focus on the how. For instance, the lives of people living with chronic illnesses can be improved by research on strategies for managing disease – to mitigate symptoms and improve function, even if the true causes of their disorders largely elude current medicine.

It’s understandable that some patients may grow frustrated or distrustful of medical providers unable to give clear answers about what causes their ailment. But it’s important to grasp that lots of scientific research focuses on how to effectively intervene in the world to reach some specific goals.

Simplistic views represent science as solely focused on providing causal explanations for the various phenomena we observe in this world. The truth is that scientists tackle all kinds of problems, which are best solved using different strategies and approaches and only sometimes involve full-fledged explanations.

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Complex problems call for complex solutions

The second aspect of scientific practice worth underscoring is that, because scientists tackle complex problems, they don’t typically offer one unique, complete and perfect answer. Instead they consider multiple, partial and possibly conflicting solutions.

Scientific modeling strategies illustrate this point well. Scientific models typically are partial, simplified and sometimes deliberately unrealistic representations of a system of interest. Models can be physical, conceptual or mathematical. The critical point is that they represent target in ways that are useful in particular contexts of inquiry. Interestingly, considering multiple possible models is often the best strategy to tackle complex problems.

Scientists consider multiple models of biodiversity, atomic nuclei or climate change. Returning to wolf abundance estimates, multiple models can also fit the bill. Such models rely on various types of data, acoustic surveys of wolf howls, genetic methods that use fecal samples from wolves, wolf sightings and photographic evidence, aerial surveys, snow track surveys and more.

Weighing the pros and cons of various possible solutions to the problem of interest is part and parcel of the scientific process. Interestingly, in some cases, using multiple conflicting models allows for better predictions than to unify all the models into one.

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The public may be surprised and possibly suspicious when scientists push forward multiple models that rely on conflicting assumptions and make different predictions. People often think “real science” should provide definite, complete and foolproof answers to their questions. But given various limitations and the world’s complexity, keeping multiple perspectives in play is most often the best way for scientists to reach their goals and solve the problems at hand.

woman at podium with slides beside her, presenting to a room

Researchers present their work publicly at conferences and in journals so other scientists can learn from and critique it.

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Science as a collective, contrarian endeavor

Finally, science is a collective endeavor, where healthy disagreement is a feature, not a bug.

The romanticized version of science pictures scientists working in isolation and establishing absolute truths. Instead, science is a social and contrarian process in which the community’s scrutiny ensures we have the best available knowledge. “Best available” does not mean “definitive,” but the best we have until we find out how to improve it. Science almost always allows for disagreements among experts.

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Controversies are core to how science works at its best and are as old as Western science itself. In the 1600s, Descartes and Leibniz fought over how to best characterize the laws of dynamics and the nature of motion.

The long history of atomism provides a valuable perspective on how science is an intricate and winding process rather than a fast-delivery system of results set in stone. As Jean Baptiste Perrin conducted his 1908 experiments that seemingly settled all discussion regarding the existence of atoms and molecules, the questions of the atom’s properties were about to become the topic of decades of controversies with the birth of quantum physics.

The nature and structure of fundamental particles and associated fields have been the subject of scientific research for more than a century. Lively academic discussions abound concerning the difficult interpretation of quantum mechanics, the challenging unification of quantum physics and relativity, and the existence of the Higgs boson, among others.

Distrusting researchers for having healthy scientific disagreements is largely misguided.

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A very human practice

To be clear, science is dysfunctional in some respects and contexts. Current institutions have incentives for counterproductive practices, including maximizing publication numbers. Like any human endeavor, science includes people with bad intent, including some trying to discredit legitimate scientific research. Finally, science is sometimes inappropriately influenced by various values in problematic ways.

These are all important considerations when evaluating the trustworthiness of particular scientific claims and recommendations. However, it is unfair, sometimes dangerous, to mistrust science for doing what it does at its best. Science is a multifaceted endeavor focused on solving complex problems that typically just don’t have simple solutions. Communities of experts scrutinize those solutions in hopes of providing the best available approach to tackling the problems of interest.

Science is also a fallible and collective process. Ignoring the realities of that process and holding science up to unrealistic standards may result in the public calling science out and losing trust in its reliability for the wrong reasons.The Conversation

Soazig Le Bihan, Professor of Philosophy, University of Montana

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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The Conversation

a double shot of US history

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theconversation.com – Kyle G. Volk, Professor of History, of Montana – 2024-09-16 07:28:46

Having a beer in Raceland, La.

Russell Lee for Farm Security Administration/WPA

Kyle G. Volk, University of Montana

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Text saying: Uncommon Courses, from The Conversation

Uncommon Courses is an occasional from U.S. highlighting unconventional approaches to teaching.

Title of course:

“Intoxication Nation: Alcohol in American History”

What prompted the idea for the course?

I wanted to get excited about studying the past by learning about something that is very much a part of their own lives.

Alcohol – somewhat surprisingly to me at first – prominently in my own research on minority rights and U.S. democracy in the mid-19th century. As a result, I knew quite a bit about the temperance movement and conflicts over prohibition during that period. Designing this course me to broaden my expertise.

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What does the course explore?

Prohibition is a must-do subject. Students expect it. But I several hundred years of history: from the 17th-century invention of rum – as a byproduct of sugar produced by enslaved people – to the rise of craft beer and craft spirits in the 21st century.

A faded poster with an illustration of a person about to smash a huge bottle of alcohol, and the message 'Close the saloons' at the top.

A temperance poster from the World War I era.

Office of Naval Records and Library via National Archives Catalog

Along the way, I’m thrilled when students get excited about details that allow them to taste a more complicated historical cocktail. For example, they learn why white women’s production of hard cider was crucial to the survival of colonial Virginia. The short answer: Potable water was in short supply, alcoholic drinks were far healthier, and white – and their indentured and enslaved workforce – were busy raising tobacco. It fell to women to turn fruit into salvation.

Why is this course relevant now?

Alcohol remains a big and almost inescapable part of American society. But of late, Americans have been drinking differently – and thinking about drinking differently.

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Examples abound. Alcohol producers, we learn, now face competition from legalized weed. Drinking l evels rose during the COVID-19 pandemic, yet interest is declining among Gen Zers. The “wine mom” culture that brought some mothers together now faces mounting criticism.

And, of course, there’s the never-ending debate about the health benefits and risks of alcohol. Of late, the risks seem to be dominating headlines.

What’s a critical lesson from the course?

Alcohol has been a highly controversial, central aspect of the American experience, shaping virtually all sectors of our society – political and constitutional, business and economic, social and cultural.

What materials does the course feature?

What will the course prepare students to do?

Like any history course, this one aims to develop student’s analytical, written, research and verbal skills. In lots of ways, the topic is just a tool to get students to grow their brains. But I also seek to grow students’ critical awareness of the place of alcohol in their own lives. The course has also informed students’ paths after graduation – some who wound up working in the alcohol industry or recovery organizations.The Conversation

Kyle G. Volk, Professor of History, University of Montana

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The Conversation

Sunflowers make small moves to maximize their Sun exposure − physicists can model them to predict how they grow

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theconversation.com – Chantal Nguyen, Postdoctoral Associate at the BioFrontiers Institute, of Colorado Boulder – 2024-09-13 07:31:40

Sunflowers use tiny movements to follow the Sun’s path throughout the day.

AP Photo/Charlie Riedel

Chantal Nguyen, University of Colorado Boulder

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Most of us aren’t spending our days watching our houseplants grow. We see their signs of only occasionally – a new leaf unfurled, a stem leaning toward the window.

But in the summer of 1863, Charles Darwin lay ill in bed, with nothing to do but watch his plants so closely that he could detect their small movements to and fro. The tendrils from his cucumber plants swept in circles until they encountered a stick, which they proceeded to twine around.

“I am getting very much amused by my tendrils,” he wrote.

This amusement blossomed into a decadeslong fascination with the little-noticed world of plant movements. He compiled his detailed observations and experiments in a 1880 book called “The Power of Movement in Plants.”

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A zig-zagging line showing the movement of a leaf.

A diagram tracking the circumnutation of a leaf over three days.

Charles Darwin

In one study, he traced the motion of a carnation leaf every few hours over the course of three days, revealing an irregular looping, jagged path. The swoops of cucumber tendrils and the zags of carnation leaves are examples of inherent, ubiquitous plant movements called circumnutations – from the Latin circum, meaning circle, and nutare, meaning to nod.

Circumnutations vary in size, regularity and timescale across plant species. But their exact function remains unclear.

I’m a physicist interested in understanding collective behavior in living . Like Darwin, I’m captivated by circumnutations, since they may underlie more complex phenomena in groups of plants.

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Sunflower patterns

A 2017 study revealed a fascinating observation that got my colleagues and me wondering about the role circumnutations could play in plant growth patterns. In this study, researchers found that sunflowers grown in a dense row naturally formed a near-perfect zigzag pattern, with each plant leaning away from the row in alternating directions.

This pattern the plants to avoid shade from their neighbors and maximize their exposure to sunlight. These sunflowers flourished.

Researchers then planted some plants at the same density but constrained them so that they could grow only upright without leaning. These constrained plants produced less oil than the plants that could lean and get the maximum amount of sun.

While farmers can’t grow their sunflowers quite this close together due to the potential for disease spread, in the future they may be able to use these patterns to up with new planting strategies.

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Self-organization and randomness

This spontaneous pattern formation is a neat example of self-organization in nature. Self-organization refers to when initially disordered systems, such as a jungle of plants or a swarm of bees, achieve order without anything controlling them. Order emerges from the interactions between individual members of the system and their interactions with the .

Somewhat counterintuitively, noise – also called randomness – facilitates self-organization. Consider a colony of ants.

Ants secrete pheromones behind them as they crawl toward a food source. Other ants find this food source by the pheromone trails, and they further reinforce the trail they took by secreting their own pheromones in turn. Over time, the ants converge on the best path to the food, and a single trail prevails.

But if a shorter path were to become possible, the ants would not necessarily find this path just by following the existing trail.

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If a few ants were to randomly deviate from the trail, though, they might stumble onto the shorter path and create a new trail. So this randomness injects a spontaneous change into the ants’ system that allows them to explore alternative scenarios.

Eventually, more ants would follow the new trail, and soon the shorter path would prevail. This randomness helps the ants adapt to changes in the environment, as a few ants spontaneously seek out more direct ways to their food source.

A group of honeybees spread out standing on honeycomb.

Beehives are an example of self-organization in nature.

Martin Ruegner/Stone via Getty Images

In biology, self-organized systems can be found at a range of scales, from the patterns of proteins inside cells to the socially complex colonies of honeybees that collectively build nests and forage for nectar.

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Randomness in sunflower self-organization

So, could random, irregular circumnutations underpin the sunflowers’ self-organization?

My colleagues and I set out to explore this question by following the growth of young sunflowers we planted in the lab. Using cameras that imaged the plants every five minutes, we tracked the movement of the plants to see their circumnutatory paths.

We saw some loops and spirals, and lots of jagged movements. These ultimately appeared largely random, much like Darwin’s carnation. But when we placed the plants together in rows, they began to move away from one another, forming the same zigzag configurations that we’d seen in the previous study.

Five plants and a diagram showing loops and jagged lines that represent small movements made by the plants.

Tracking the circumnutations made by young sunflower plants.

Chantal Nguyen

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We analyzed the plants’ circumnutations and found that at any given time, the direction of the plant’s motion appeared completely independent of how it was moving about half an hour earlier. If you measured a plant’s motion once every 30 minutes, it would appear to be moving in a completely random way.

We also measured how much the plant’s leaves grew over the course of two weeks. By putting all of these results together, we sketched a picture of how a plant moved and grew on its own. This information allowed us to computationally model a sunflower and simulate how it behaves over the course of its growth.

A sunflower model

We modeled each plant simply as a circular crown on a stem, with the crown expanding according to the growth rate we measured experimentally. The simulated plant moved in a completely random way, taking a “step” every half hour.

We created the model sunflowers with circumnutations of lower or higher intensity by tweaking the step sizes. At one end of the spectrum, sunflowers were much more likely to take tiny steps than big ones, leading to slow, minimal movement on average. At the other end were sunflowers that are equally as likely to take large steps as small steps, resulting in highly irregular movement. The real sunflowers we observed in our experiment were somewhere in the middle.

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Plants require light to grow and have evolved the ability to detect shade and alter the direction of their growth in response.

We wanted our model sunflowers to do the same thing. So, we made it so that two plants that get too close to each other’s shade begin to lean away in opposite directions.

Finally, we wanted to see whether we could replicate the zigzag pattern we’d observed with the real sunflowers in our model.

First, we set the model sunflowers to make small circumnutations. Their shade avoidance responses pushed them away from each other, but that wasn’t enough to produce the zigzag – the model plants stayed stuck in a line. In physics, we would call this a “frustrated” system.

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Then, we set the plants to make large circumnutations. The plants started moving in random patterns that often brought the plants closer together rather than farther apart. Again, no zigzag pattern like we’d seen in the field.

But when we set the model plants to make moderately large movements, similar to our experimental measurements, the plants could self-organize into a zigzag pattern that gave each sunflower optimal exposure to light.

So, we showed that these random, irregular movements helped the plants explore their surroundings to find desirable arrangements that benefited their growth.

Plants are much more dynamic than people give them credit for. By taking the time to follow them, scientists and farmers can unlock their secrets and use plants’ movement to their advantage.The Conversation

Chantal Nguyen, Postdoctoral Associate at the BioFrontiers Institute, University of Colorado Boulder

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Endometriosis pain leads to missed school and work in two-thirds of women with the condition, new study finds

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theconversation.com – Rasha Al-Lami, Researcher in Women’s , Yale University – 2024-09-13 07:30:43

Endometriosis affects about 10% of reproductive-age women worldwide.

Xavier Lorenzo/Moment via Getty Images

Rasha Al-Lami, Yale University

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More than two-thirds of women with endometriosis missed school or work due to pain from the , in a study of more than 17,000 women between the ages of 15 and 44 in the U.S. That is a key finding of new research published in the Journal of Endometriosis and Uterine Disorders.

Our study also found that Black and Hispanic women were less likely to be diagnosed with endometriosis with white women. Interestingly, women who identified as part of the LGBTQ community had a higher likelihood of receiving an endometriosis diagnosis than heterosexual women.

We used data from the National Health and Nutrition Examination Survey, which is administered by the Centers for Disease Control and Prevention, for the period 2011 to 2019. The survey data use adjusted weights to account for the racial composition of U.S. society, meaning our sample of 17,619 women represents 51,981,323 women of the U.S. population.

We specifically examined factors related to quality of , such as poverty, education and functional impairment, as well as race and sexual orientation.

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I am a physician-scientist and a researcher in women’s health, working together with specialists in OB-GYN from Yale and the University of .

Why it matters

Endometriosis is a chronic, often painful condition that affects approximately 10% of reproductive-age women worldwide. It occurs when tissues that would normally line the inner surface of the uterus instead occur outside the uterus, such as on the ovaries or even in distant organs such as the lungs or brain. These abnormally located lesions respond to hormonal changes during the menstrual cycle, causing pain when stimulated by the hormones that regulate the menstrual cycle.

Our study sheds light on how endometriosis, despite its prevalence, remains underdiagnosed and underresearched. We found that 6.4% of reproductive-age women in the U.S. had an endometriosis diagnosis. More than 67% reported missed work or school, or been unable to perform activities, due to pain associated with endometriosis.

Our study highlights disparities in the diagnosis and management of endometriosis among different racial groups. Black women had 63% lower odds of getting an endometriosis diagnosis, and Hispanic women had 55% lower odds compared with non-Hispanic white women. This disparity may reflect historical biases in health care, pointing to the need for more equitable practices.

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In addition, our study underscores the importance of considering women’s health across diverse population subgroups, with particular attention to sexual orientation. We found that non-heterosexual lesbian, gay, bisexual, transgender and queer women had 54% higher odds of receiving an endometriosis diagnosis compared with straight women. Our study was the first to examine endometriosis likelihood among non-heterosexual women at the national level in the U.S.

We found no significant association between endometriosis and other quality-of-life indicators such as poverty, education or employment status, which suggests that the condition affects women across various socioeconomic backgrounds.

A common theory about the cause of endometriosis is that women have menstrual blood that seeds outside of the uterus, but recent research supports inflammatory causes.

What other research is being done

Our work adds to the growing body of evidence that Black women are less likely to be diagnosed with endometriosis and that their reported pain symptoms are often overlooked.

Explanations for this inequity include health care bias against minority women and limited access to medical care among Black women. Research also shows that many medical professionals as well as medical and residents believe that Black women have a lower pain threshold compared with the white population.

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This is another possible reason that pain symptoms among Black women with endometriosis get neglected. Researchers from the U.K reported the same findings, attributing these disparities to systemic bias and inequitable medical care.

Another study estimates that the lifetime costs associated with having endometriosis are about US$27,855 per year per patient in the U.S., costing the country about $22 annually on health care expenditures.The Conversation

Rasha Al-Lami, Researcher in Women’s Health, Yale University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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