tag:theconversation.com,2011:/africa/topics/cultural-evolution-7307/articlesCultural evolution – The Conversation2019-02-22T00:07:07Ztag:theconversation.com,2011:article/1111492019-02-22T00:07:07Z2019-02-22T00:07:07ZSexual selection in action: Birds that attract multiple mates change their songs more quickly<figure><img src="https://images.theconversation.com/files/260221/original/file-20190221-195883-15xmtnf.jpg?ixlib=rb-1.1.0&rect=984%2C342%2C3020%2C1987&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Male collared flycatcher, singing for multiple females.</span> <span class="attribution"><a class="source" href="https://www.shutterstock.com/image-photo/singing-beautiful-male-collared-flycatcher-ficedula-1113698822">Kennerth Kullman/Shutterstock.com</a></span></figcaption></figure><p>How do individuals choose their mates? Why are some more successful at attracting mates than others?</p>
<p>These age-old questions are broadly relevant to all animals, including human beings. <a href="http://darwin-online.org.uk/content/frameset?pageseq=1&itemID=F376&viewtype=side">Darwin’s theory of natural selection</a> offers one way to answer them. Sometimes phrased as “survival of the fittest,” the theory can also apply to mate choice, predicting that it’s <a href="https://www.amnh.org/exhibitions/darwin/evolution-today/how-does-natural-selection-work">beneficial to choose the mate who’s best adapted</a> to surviving in its environment — the fastest runner, the best hunter, the farmer with the highest yields.</p>
<p>That’s a bit simplistic as a summary of human sexuality, of course, since people pair up in the context of complex social norms and gender roles that are uniquely human. Researchers like us do think, though, that mate choice in other animals is influenced by these kinds of perceived adaptations. It fits with scientists’ understanding of evolution: If females choose to mate with well-adapted males, their offspring might have a better chance of surviving as well. Advantageous traits wind up <a href="https://evolution.berkeley.edu/evolibrary/article/evo_25">passed down and preserved in future generations</a>.</p>
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<a href="https://images.theconversation.com/files/260223/original/file-20190221-195879-1sg1s5j.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/260223/original/file-20190221-195879-1sg1s5j.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/260223/original/file-20190221-195879-1sg1s5j.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/260223/original/file-20190221-195879-1sg1s5j.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/260223/original/file-20190221-195879-1sg1s5j.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/260223/original/file-20190221-195879-1sg1s5j.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/260223/original/file-20190221-195879-1sg1s5j.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/260223/original/file-20190221-195879-1sg1s5j.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
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<span class="caption">A peacock’s tail’s only advantage is that females love it.</span>
<span class="attribution"><a class="source" href="https://www.shutterstock.com/image-photo/portrait-beautiful-peacock-feathers-out-304866848">PrimePhoto/Shutterstock.com</a></span>
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<p>But in many species, males try to attract mates by displaying characteristics that <a href="https://evolution.berkeley.edu/evolibrary/article/side_0_0/runawayselec_01">seem to be decidedly non-adaptive</a>. These signals – such as a dazzling tail on a peacock or a beautiful tune from a songbird – were originally a big wrench thrown into Darwin’s theory of natural selection. Traits like these seem to do the opposite of making an animal more likely to survive in its environment. A flashy tail display or a showy melody is cumbersome, and it announces you to predators as well as love interests. Darwin got so upset by this inconsistency that he said “The sight of a feather in a peacock’s tail, whenever I gaze at it, <a href="https://www.darwinproject.ac.uk/letter/DCP-LETT-2743.xml">makes me sick</a>.” </p>
<p>Thinking about this conundrum <a href="http://darwin-online.org.uk/content/frameset?pageseq=1&itemID=F937.1&viewtype=side">led Darwin to another major theory</a>: <a href="https://evolution.berkeley.edu/evolibrary/article/evo_28">sexual selection</a>. Instead of directly displaying adaptations, males might need to produce costly, non-adaptive signals if females prefer those features when choosing mates. For the females, these signals might indirectly communicate that a male would be a good mate because he’s able to survive and succeed — in spite of the ornament, not because of it. Under this model, the costliest traits are the most attractive.</p>
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<a href="https://images.theconversation.com/files/260008/original/file-20190220-148520-1nycy7f.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/260008/original/file-20190220-148520-1nycy7f.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/260008/original/file-20190220-148520-1nycy7f.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=729&fit=crop&dpr=1 600w, https://images.theconversation.com/files/260008/original/file-20190220-148520-1nycy7f.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=729&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/260008/original/file-20190220-148520-1nycy7f.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=729&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/260008/original/file-20190220-148520-1nycy7f.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=916&fit=crop&dpr=1 754w, https://images.theconversation.com/files/260008/original/file-20190220-148520-1nycy7f.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=916&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/260008/original/file-20190220-148520-1nycy7f.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=916&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
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<span class="caption">Red-winged blackbirds are polygynous, with males angling to mate with multiple females.</span>
<span class="attribution"><a class="source" href="https://www.audubon.org/birds-of-america/red-winged-starling-or-marsh-blackbird">John James Audubon Center at Mill Grove in Audubon, Pennsylvania and the Montgomery County Audubon Collection</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
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<p>But what if the stakes are raised, as in species that are polygynous, with males trying to attract and form bonds with multiple females? A logical next step to this theory might predict that the pressure to produce beautiful signals would skyrocket, compounding the rewards for individuals with elaborate ornaments. If the most successful males have the most extraordinary traits, an ensuing arms race over many generations could shift the population toward more extreme characteristics. <a href="http://darwin-online.org.uk/content/frameset?pageseq=282&itemID=F937.1&viewtype=side">This is an intuitive theory</a> – increased competition for mates would lead to increasingly elaborate sexually selected traits – but it hasn’t been tested across the tree of life.</p>
<p>Do non-monogamous mating systems truly increase sexual selection in real animals? As the strength of sexual selection increases, do sexually selected characteristics become more extreme? Do tails get longer? Songs, more beautiful? <a href="http://creanzalab.com">As two biologists</a> with <a href="https://scholar.google.com/citations?user=vwQdgAYAAAAJ&hl=en&oi=ao">expertise in computational methods</a>, <a href="https://scholar.google.com/citations?user=hScDPxkAAAAJ&hl=en">the evolution of behaviors</a> and songbirds, <a href="https://doi.org/10.1038/s41467-019-08621-3">we decided to investigate</a>.</p>
<h2>Building up the bird database</h2>
<p>Evolution is as complex as life itself. New computational abilities allow researchers like us to go beyond testing whether certain traits simply tend to occur together. Instead, we can delve into the past and try to discern the path that species have traveled through history to arrive where they are today.</p>
<p><a href="https://doi.org/10.1038/s41467-019-08621-3">To test the theory</a> that males trying to attract multiple mates would amplify sexual selection and drive the evolution of increasingly elaborate displays, we needed both a new dataset and innovative methods.</p>
<p>Songbirds are an excellent system with which to study this question. First, many species are socially (though not necessarily sexually) monogamous, <a href="http://crosstalk.cell.com/blog/10-examples-of-monogamy-in-the-animal-kingdom">which is otherwise</a> <a href="https://www.audubon.org/news/monogamy-rare-wild">exceedingly rare</a> in the animal kingdom, but there have been numerous independent transitions to polygyny over the course of their history. That makes it easy for us to compare the songs of birds searching for a single partner to the songs of those looking for multiple mates. Songbirds also have an incredible diversity of song, from the <a href="https://www.allaboutbirds.org/guide/house_sparrow">simple tweets of the house sparrow</a> to the <a href="https://www.allaboutbirds.org/guide/Northern_Mockingbird/">elaborate cadenzas of the mockingbird</a>.</p>
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<a href="https://images.theconversation.com/files/260086/original/file-20190221-148513-1nkx9sl.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/260086/original/file-20190221-148513-1nkx9sl.png?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/260086/original/file-20190221-148513-1nkx9sl.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=801&fit=crop&dpr=1 600w, https://images.theconversation.com/files/260086/original/file-20190221-148513-1nkx9sl.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=801&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/260086/original/file-20190221-148513-1nkx9sl.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=801&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/260086/original/file-20190221-148513-1nkx9sl.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=1007&fit=crop&dpr=1 754w, https://images.theconversation.com/files/260086/original/file-20190221-148513-1nkx9sl.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=1007&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/260086/original/file-20190221-148513-1nkx9sl.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=1007&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">A family tree of birds shows their evolutionary connections.</span>
<span class="attribution"><a class="source" href="https://doi.org/10.1038/s41467-019-08621-3">Kate T. Snyder & Nicole Creanza, Nature Communications, volume 10, Article number: 884 (2019)</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
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<p>By searching published literature and field guides, we gathered mating system data on almost 700 species and song data for over 350 species, <a href="https://www.nature.com/articles/s41467-019-08621-3#MOESM1">the largest database of its kind to date</a>. We obtained a <a href="http://birdtree.org">recently published phylogeny</a> – essentially a “family tree” that stretches all the way back to the ancestor of all birds – that covered all of avian evolutionary history. This would serve as our map through the songbird lineages.</p>
<p>We merged our trait data with the phylogeny to trace backwards in time, estimating how the ancestors of each group of songbirds might have sounded and behaved.</p>
<p>This approach is kind of like if we dropped in on a human family reunion and noticed that the vast majority of family members have blonde hair and were speaking Swedish – we’d guess that a long-gone matriarch of the family probably also had blonde hair and likely spoke Swedish. Then, we could visit another family reunion, distant relatives of the first, to find blonde people speaking mostly Norwegian. At yet another gathering, perhaps we’d see brown-haired people speaking Spanish. By doing this hundreds of times, researchers could figure out whether there was any association between hair color and language in these families’ histories.</p>
<p>Using similar methods with <a href="http://www.onezoom.org/OZtree/static/OZLegacy/EDGE_birds.htm">the bird family tree</a>, we were able to test not only how mating behavior correlates with the songs of living species, but also how these behaviors affected one another over thousands and even millions of years of songbird evolutionary history. By estimating the likely behaviors of the ancestors of modern-day songbirds, we could calculate the rate of evolution of these traits, including how rates of song evolution might be influenced by mating behavior, or vice versa.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/260224/original/file-20190221-195864-y2w5eg.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/260224/original/file-20190221-195864-y2w5eg.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/260224/original/file-20190221-195864-y2w5eg.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/260224/original/file-20190221-195864-y2w5eg.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/260224/original/file-20190221-195864-y2w5eg.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/260224/original/file-20190221-195864-y2w5eg.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/260224/original/file-20190221-195864-y2w5eg.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/260224/original/file-20190221-195864-y2w5eg.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Male house sparrows have simple songs, despite the fact that they are looking for multiple mates.</span>
<span class="attribution"><a class="source" href="https://www.shutterstock.com/image-photo/house-sparrow-sitting-outside-urban-birds-1245300223">ViktoriaIvanets/Shutterstock.com</a></span>
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<h2>Sexual selection, but not in one direction</h2>
<p>When we performed this deep analysis, the results surprised us. We did not find the expected relationship that songs became more elaborate in species where males were seeking multiple mates. Instead, we found an interesting evolutionary pattern: Songs seemed to be evolving faster polygynous lineages, but not in any particular direction.</p>
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<a href="https://images.theconversation.com/files/260043/original/file-20190220-148530-12huz5f.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/260043/original/file-20190220-148530-12huz5f.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/260043/original/file-20190220-148530-12huz5f.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=729&fit=crop&dpr=1 600w, https://images.theconversation.com/files/260043/original/file-20190220-148530-12huz5f.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=729&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/260043/original/file-20190220-148530-12huz5f.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=729&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/260043/original/file-20190220-148530-12huz5f.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=916&fit=crop&dpr=1 754w, https://images.theconversation.com/files/260043/original/file-20190220-148530-12huz5f.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=916&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/260043/original/file-20190220-148530-12huz5f.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=916&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Mockingbirds sing the complex songs the researchers expected would go along with polygynous mating strategies, but are generally socially monogamous.</span>
<span class="attribution"><a class="source" href="https://www.audubon.org/birds-of-america/mocking-bird">John James Audubon Center at Mill Grove in Audubon, Pennsylvania and the Montgomery County Audubon Collection</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
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<p>Instead of these ancestral males trying to outcompete one another with more elaborate songs, songs seemed to oscillate between simple and complex like a swinging pendulum over the generations – changing quickly in the moment, but not in a consistent direction over the long term. If these polygynous species’ songs got too simple or too elaborate, they started moving back towards the middle.</p>
<p>These results challenge our initial broad intuitions about reproductive success and evolutionary pressures. By studying the songs of many monogamous and polygynous bird species across the evolutionary tree, we found results that stood in contrast to the prevailing wisdom: Species that attract multiple mates did not have more complex songs overall, but their songs were evolving faster. This is a new piece of evidence that may alter classical hypotheses on non-monogamy and sexual selection in evolution. </p>
<p>Our work shows that when scientists study sexual selection in the future, we need to think not only about the magnitude of the traits being studied, but also how fast they change.</p><img src="https://counter.theconversation.com/content/111149/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Nicole Creanza has received funding from Vanderbilt University, the Ruth Landes Memorial Research Fund, the John Templeton Foundation, and the Stanford Center for Computational, Evolutionary, and Human Genomics.</span></em></p><p class="fine-print"><em><span>Kate Snyder receives funding from Vanderbilt University Department of Biological Sciences and the Vanderbilt University Graduate School. </span></em></p>Biologists investigated whether birds that search for multiple mates would evolve ever more elaborate songs to attract them. What they found might have surprised Darwin.Nicole Creanza, Assistant Professor of Biological Sciences, Vanderbilt UniversityKate Snyder, Ph.D. Candidate in Biological Sciences, Vanderbilt UniversityLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/918912018-03-02T11:42:41Z2018-03-02T11:42:41ZHow people talk now holds clues about human migration centuries ago<figure><img src="https://images.theconversation.com/files/208303/original/file-20180228-36680-1gzt1zc.jpg?ixlib=rb-1.1.0&rect=349%2C349%2C4132%2C2645&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">What can a modern-day Creole language tell us about its first speakers in the 1600s?</span> <span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:Paramaribo,_Suriname_(11987836025).jpg">M M</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span></figcaption></figure><p>Often, you can tell where someone grew up by the way they speak.</p>
<p>For example, if someone in the United States doesn’t pronounce the final “r” at the end of “car,” you might think they are from the Boston area, based on sometimes exaggerated stereotypes about American accents and dialects, such as “Pahk the cahr in Hahvahd Yahd.”</p>
<p>Linguists go deeper than the stereotypes, though. They’ve used <a href="http://www.tekstlab.uio.no/cambridge_survey/">large-scale surveys</a> to <a href="https://www.nytimes.com/interactive/2014/upshot/dialect-quiz-map.html">map out many features of dialects</a>. The more you know about how a person pronounces certain words, the more likely you’ll be able to pinpoint where they are from. For instance, linguists know that dropping the “r” sounds at the end of words is actually common in many English dialects; they can map in space and time how r-dropping is widespread in the London area and has become increasingly common in England over the years. </p>
<p><a href="https://doi.org/10.1098/rstb.2017.0055">In a recent study</a>, we applied this concept to a different question: the formation of Creole languages. <a href="https://mona-uwi.academia.edu/ASherriah">As a linguist</a> and a <a href="https://scholar.google.com/citations?user=vwQdgAYAAAAJ&hl=en">biologist who studies cultural evolution</a>, we wanted to see how much information we could glean from a snapshot of how a language exists at one moment in time. Working with linguist <a href="https://www.mona.uwi.edu/dllp/jlu/staff/devonish.htm">Hubert Devonish</a> and psychologist <a href="https://profiles.stanford.edu/ewart-thomas">Ewart Thomas</a>, could we figure out the language “ingredients” that went into a Creole language, and where these “ingredients” originally came from?</p>
<h2>Mixing languages to make a Creole</h2>
<p>When a <a href="https://benjamins.com/#catalog/books/cll.25/main">Creole language forms</a>, it’s generally because <a href="http://www.ello.uos.de/field.php/Sociolinguistics/Theoriesofgenesis">two or more populations come together</a> without a common language to speak. Across history, this was often in the context of colonialism, indentured servitude and slavery. For example, in the U.S., <a href="http://www.afropedea.org/louisiana-creoles-people">Louisiana Creole</a> was formed by speakers of French and several African languages in the French slave colony of Louisiana. <a href="https://doi.org/10.1163/000000008792525228">As people mix</a>, a new language forms, and often the origins of individual words can be traced back to one of the source languages.</p>
<p>Our idea was that, if specific dialects were common among the migrants, the way they pronounce words might influence the pronunciations in the new Creole language. In other words, if English-derived words in a Creole exhibit r-dropping, we might hypothesize that the English speakers present when the Creole formed also dropped their r’s.</p>
<p><iframe id="tc-infographic-244" class="tc-infographic" height="400px" src="https://cdn.theconversation.com/infographics/244/d0929212fe8463b2bd63c88f0474e341fd78aee8/site/index.html" width="100%" style="border: none" frameborder="0"></iframe></p>
<p>Following this logic, we examined the pronunciation of Sranan, an English-based Creole still spoken in Suriname. We wanted to see if we could use language clues to identify where in England the original settlers came from. Sranan developed around the mid-17th century, due to contact between speakers of English dialects from England, migrants from elsewhere in Europe (such as Portugal and the Netherlands) and enslaved Africans who spoke a variety of West African languages.</p>
<p>As is the case with most English-based Creoles, the majority of the lexicon is English. Unlike most English Creoles, though, Sranan represents a linguistic fossil of the early colonial English that went into its development. In 1667, soon after Sranan was formed, the English ceded Suriname to the Dutch, and most English speakers moved elsewhere. So the indentured servants and other migrants from England had a brief but strong influence on Sranan.</p>
<h2>Using historical records to check our work</h2>
<p>We asked whether we could use features of Sranan to hypothesize where the English settlers originated and then corroborate these hypotheses via historical records.</p>
<figure class="align-left zoomable">
<a href="https://images.theconversation.com/files/208295/original/file-20180228-36700-182it7d.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/208295/original/file-20180228-36700-182it7d.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/208295/original/file-20180228-36700-182it7d.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=703&fit=crop&dpr=1 600w, https://images.theconversation.com/files/208295/original/file-20180228-36700-182it7d.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=703&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/208295/original/file-20180228-36700-182it7d.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=703&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/208295/original/file-20180228-36700-182it7d.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=883&fit=crop&dpr=1 754w, https://images.theconversation.com/files/208295/original/file-20180228-36700-182it7d.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=883&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/208295/original/file-20180228-36700-182it7d.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=883&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">The similarity of each English dialect to Sranan. The most similar dialect, Blagdon, is indicated by a red arrow.</span>
<span class="attribution"><a class="source" href="https://doi.org/10.1098/rstb.2017.0055">source</a>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>First, we compared a set of linguistic features of modern-day Sranan with those of English as spoken in 313 localities across England. We focused on things like the production of “r” sounds after vowels and “h” sounds at the start of words. Since some aspects of English dialects have changed over the last few centuries, we also consulted historical accounts of both English and Sranan.</p>
<p>It turned out that 80 percent of the English features in Sranan could be traced back to regional dialectal features from two distinct locations within England: a cluster of locations near the port of Bristol and a cluster near Essex, in eastern England. </p>
<figure class="align-right zoomable">
<a href="https://images.theconversation.com/files/208294/original/file-20180228-36696-1505m3l.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/208294/original/file-20180228-36696-1505m3l.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/208294/original/file-20180228-36696-1505m3l.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=822&fit=crop&dpr=1 600w, https://images.theconversation.com/files/208294/original/file-20180228-36696-1505m3l.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=822&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/208294/original/file-20180228-36696-1505m3l.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=822&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/208294/original/file-20180228-36696-1505m3l.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=1033&fit=crop&dpr=1 754w, https://images.theconversation.com/files/208294/original/file-20180228-36696-1505m3l.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=1033&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/208294/original/file-20180228-36696-1505m3l.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=1033&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Circles represent the origin locations listed in ship records. The area of the circle is proportional to the number of individuals from that location. Bristol is marked by a yellow star, London by a blue star.</span>
<span class="attribution"><a class="source" href="https://doi.org/10.1098/rstb.2017.0055">source</a>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>Then, we examined archival records such as the <a href="http://www.virtualjamestown.org/indentures/search_indentures.html">Bristol Register of Servants to Foreign Plantations</a> to see if the language clues we’d identified were backed up by historical evidence of migration. Indeed, these boat records indicate that indentured servants departing for English colonies were predominantly from the regions identified by our language analysis.</p>
<p><a href="https://doi.org/10.1098/rstb.2017.0055">Our research was proof of concept</a> that we could use modern information to learn more about the linguistic features that went into the formation of a Creole language. We can gain confidence in our conclusions because the historical record backed them up. Language can be a solid clue about the origins and history of human migrations. </p>
<p>We hope to use a similar approach to examine the African languages that have influenced Creole languages, since much less is known about the origins of enslaved people than the European indentured servants. Analyses like these might help us retrace aspects of forced migrations via the slave trade and paint a more complete linguistic picture of Creole formations.</p><img src="https://counter.theconversation.com/content/91891/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Nicole Creanza has received funding from the Ruth Landes Memorial Research Fund, the John Templeton Foundation, and the Stanford Center for Computational, Evolutionary, and Human Genomics. </span></em></p><p class="fine-print"><em><span>André Ché Sherriah 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.</span></em></p>New research suggests that hints left in Creole languages can identify where the original speakers came from – even hundreds of years after they migrated and mixed together.Nicole Creanza, Assistant Professor of Biological Sciences, Vanderbilt UniversityAndré Ché Sherriah, Postdoctoral Associate in Linguistics, University of the West Indies, Mona CampusLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/818892017-08-30T23:27:43Z2017-08-30T23:27:43ZWhat creativity really is - and why schools need it<figure><img src="https://images.theconversation.com/files/183880/original/file-20170829-5012-mu9wnk.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">In this time of global technological change and sustainability challenges, we need to increase creativity levels in the next generation, to ensure the innovations that will keep us afloat. </span> <span class="attribution"><span class="source">(Shutterstock)</span></span></figcaption></figure><p>Although educators claim to <a href="https://www.amazon.com/gp/product/1461451841/ref=as_li_qf_sp_asin_il_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=1461451841&linkCode=as2&tag=jackaphd-20">value creativity</a>, they don’t always prioritize it. </p>
<p>Teachers often have <a href="https://www.amazon.com/Killing-ideas-softly-creativity-classroom/dp/1623963648">biases against creative students</a>, fearing that creativity in the classroom will be disruptive. They devalue creative personality attributes such as risk taking, impulsivity and independence. They inhibit creativity by focusing on the reproduction of knowledge and obedience in class. </p>
<p>Why the disconnect between educators’ official stance toward creativity, and what actually happens in school? </p>
<p>How can teachers nurture creativity in the classroom in an era of rapid technological change, when human innovation is needed more than ever and children are more distracted and <a href="https://theconversation.com/how-the-smartphone-affected-an-entire-generation-of-kids-82477">hyper-stimulated</a>?</p>
<p>These are some of the questions we ask in my research lab at the Okanagan campus of the University of British Columbia. We <a href="https://people.ok.ubc.ca/lgabora/research.htm">study the creative process</a>, as well as how ideas evolve over time and across societies. I’ve written almost 200 scholarly papers and book chapters on creativity, and lectured on it worldwide. My research involves both computational models and studies with human participants. I also write fiction, compose music for the piano and do freestyle dance.</p>
<h2>What is creativity?</h2>
<p>Although creativity is often defined in terms of new and useful products, I believe it makes more sense to define it in terms of processes. Specifically, creativity involves cognitive processes that transform one’s understanding of, or relationship to, the world. </p>
<figure class="align-center ">
<img alt="" src="https://images.theconversation.com/files/183882/original/file-20170829-8679-1ws6eqx.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/183882/original/file-20170829-8679-1ws6eqx.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=416&fit=crop&dpr=1 600w, https://images.theconversation.com/files/183882/original/file-20170829-8679-1ws6eqx.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=416&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/183882/original/file-20170829-8679-1ws6eqx.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=416&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/183882/original/file-20170829-8679-1ws6eqx.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=523&fit=crop&dpr=1 754w, https://images.theconversation.com/files/183882/original/file-20170829-8679-1ws6eqx.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=523&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/183882/original/file-20170829-8679-1ws6eqx.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=523&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px">
<figcaption>
<span class="caption">A society thrives when individuals are given the space to create or imitate ideas.</span>
<span class="attribution"><span class="source">(Unsplash/Chris Barbalis)</span>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>There may be adaptive value to the seemingly mixed messages that teachers send about creativity. Creativity is the novelty-generating component of cultural evolution. As in any kind of evolutionary process, novelty must be balanced by preservation. </p>
<p>In biological evolution, the novelty-generating components are genetic mutation and recombination, and the novelty-preserving components include the survival and reproduction of “fit” individuals. In <a href="http://dx.doi.org/10.1016/j.plrev.2013.03.006">cultural evolution</a>, the novelty-generating component is creativity, and the novelty-preserving components include imitation and other forms of social learning.</p>
<p>It isn’t actually necessary for everyone to be creative for the benefits of creativity to be felt by all. We can reap the rewards of the creative person’s ideas by copying them, buying from them or simply admiring them. Few of us can build a computer or write a symphony, but they are ours to use and enjoy nevertheless. </p>
<h2>Inventor or imitator?</h2>
<p>There are also <a href="http://www.cambridge.org/ca/academic/subjects/psychology/social-psychology/dark-side-creativity?format=HB&isbn=9780521191715#UqdtxHOxfTEV0OGi.97">drawbacks to creativity</a>. Sure, creative people solve problems, crack jokes, invent stuff; they make the world pretty and interesting and fun. But generating creative ideas is time-consuming. A creative solution to one problem often generates other problems, or has unexpected negative side effects. </p>
<p>Creativity is correlated with rule bending, law breaking, social unrest, aggression, group conflict and dishonesty. Creative people often direct their nurturing energy towards ideas rather than relationships, and may be viewed as aloof, arrogant, competitive, hostile, independent or unfriendly.</p>
<figure class="align-center ">
<img alt="" src="https://images.theconversation.com/files/183881/original/file-20170829-5016-2gk88d.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/183881/original/file-20170829-5016-2gk88d.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/183881/original/file-20170829-5016-2gk88d.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/183881/original/file-20170829-5016-2gk88d.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/183881/original/file-20170829-5016-2gk88d.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/183881/original/file-20170829-5016-2gk88d.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/183881/original/file-20170829-5016-2gk88d.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px">
<figcaption>
<span class="caption">Teachers may fear creative mess, but time for reflection and interdisciplinary thinking can nurture innovation too.</span>
<span class="attribution"><span class="source">(Shutterstock)</span></span>
</figcaption>
</figure>
<p>Also, if I’m wrapped up in my own creative reverie, I may fail to notice that someone else has already solved the problem I’m working on. In an <a href="https://arxiv.org/pdf/1309.7524.pdf">agent-based computational model of cultural evolution</a>, in which artificial neural network-based agents invent and imitate ideas, the society’s ideas <a href="https://people.ok.ubc.ca/lgabora/papers/Gabora-Tseng-PACA2017.pdf">evolve most quickly</a> when there is a good mix of creative “inventors” and conforming “imitators.” Too many creative agents and the collective suffers. They are like holes in the fabric of society, fixated on their own (potentially inferior) ideas, rather than propagating proven effective ideas.</p>
<p>Of course, a computational model of this sort is highly artificial. The results of such simulations must be taken with a grain of salt. However, they suggest an adaptive value to the mixed signals teachers send about creativity. A society thrives when some individuals create and others preserve their best ideas. </p>
<p>This also makes sense given how creative people encode and process information. Creative people tend to <a href="https://arxiv.org/pdf/1308.5037.pdf">encode episodes of experience</a> in much more detail than is actually needed. This has drawbacks: Each episode takes up more memory space and has a richer network of associations. Some of these associations will be spurious. On the bright side, some may lead to new ideas that are useful or aesthetically pleasing. </p>
<p>So, there’s a trade-off to peppering the world with creative minds. They may fail to see the forest for the trees but they may produce the next Mona Lisa.</p>
<h2>Innovation might keep us afloat</h2>
<p>So will society naturally self-organize into creators and conformers? Should we avoid trying to enhance creativity in the classroom? </p>
<p>The answer is: No! The pace of cultural change is accelerating more quickly than ever before. In some biological systems, when the environment is changing quickly, the mutation rate goes up. Similarly, in times of change we need to bump up creativity levels — to generate the innovative ideas that will keep us afloat.</p>
<p>This is particularly important now. In our high-stimulation environment, children spend so much time processing new stimuli that there is less time to “go deep” with the stimuli they’ve already encountered. There is less time for thinking about ideas and situations from different perspectives, such that their ideas become more interconnected and their mental models of understanding become more integrated. </p>
<p>This “going deep” process has been <a href="https://arxiv.org/abs/1610.02478">modeled computationally</a> using a program called <em>Deep Dream</em>, a variation on the machine learning technique “Deep Learning” and used to generate images such as the ones in the figure below. </p>
<p>The images show how an input is subjected to different kinds of processing at different levels, in the same way that our minds gain a deeper understanding of something by looking at it from different perspectives. It is this kind of deep processing and the resulting <a href="https://arxiv.org/pdf/1610.02484v1.pdf">integrated webs of understanding</a> that make the crucial connections that lead to important advances and innovations.</p>
<h2>Cultivating creativity in the classroom</h2>
<p>So the obvious next question is: How can creativity be cultivated in the classroom? It turns out <a href="https://www.amazon.com/gp/product/1461451841/ref=as_li_qf_sp_asin_il_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=1461451841&linkCode=as2&tag=jackaphd-20">there are lots of ways</a>! Here are three key ways in which teachers can begin:</p>
<ol>
<li><p>Focus less on the reproduction of information and more on <a href="https://theconversation.com/how-to-help-kids-innovate-from-an-early-age-81891">critical thinking and problem solving</a>. </p></li>
<li><p>Curate activities that transcend traditional disciplinary boundaries, such as by painting murals that depict biological food chains, or acting out plays about historical events, or writing poems about the cosmos. After all, the world doesn’t come carved up into different subject areas. Our culture tells us these disciplinary boundaries are real and our thinking becomes trapped in them. </p></li>
<li><p>Pose questions and challenges, and follow up with opportunities for solitude and reflection. This provides time and space to foster the forging of new connections that is so vital to creativity.</p></li>
</ol><img src="https://counter.theconversation.com/content/81889/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Liane Gabora's research is supported by a grant (62R06523) from the Natural Sciences and Engineering Research Council of Canada.
</span></em></p>Technology requires humanity to innovate at a faster pace, but it also hampers true creative thinking. The good news? Nurturing creativity in children is easier than most people think.Liane Gabora, Associate Professor of Psychology and Creative Studies, University of British ColumbiaLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/686412016-11-16T13:26:50Z2016-11-16T13:26:50ZRed, yellow, pink and green: How the world’s languages name the rainbow<figure><img src="https://images.theconversation.com/files/146234/original/image-20161116-13506-10ayrig.jpg?ixlib=rb-1.1.0&rect=307%2C71%2C3877%2C2628&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">How many colors in your language's rainbow?</span> <span class="attribution"><a class="source" href="http://www.shutterstock.com/pic-130215719.html">Eye image via www.shutterstock.com.</a></span></figcaption></figure><p>It is striking that English color words come from many sources. Some of the more exotic ones, like “vermilion” and “chartreuse,” were borrowed from French, and are named after the color of a particular item (a type of mercury and a liquor, respectively). But even our words “black” and “white” didn’t originate as color terms. “Black” comes from a word meaning “burnt,” and “white” comes from a word meaning “shining.” </p>
<p>Color words vary a lot across the world. Most languages have between two and 11 basic color words. English, for example, has the full set of 11 basic colors: black, white, red, green, yellow, blue, pink, gray, brown, orange and purple. In a 1999 survey by linguists <a href="http://www1.icsi.berkeley.edu/%7Ekay/">Paul Kay</a> and <a href="http://terralingua.org/">Luisa Maffi</a>, languages were <a href="http://wals.info/feature/133A#2/22.3/153.7">roughly equally distributed</a> between the basic color categories that they tracked.</p>
<p>In languages with fewer terms than this – such as the Alaskan language Yup'ik with its five terms – the range of a word expands. For example, for languages without a separate word for “orange,” hues that we’d call “orange” in English might be named by the same color that English speakers would call “red” or “yellow.” We can think of these terms as a system that together cover the visible spectrum, but where individual terms are centered on various parts of that spectrum.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=600&fit=crop&dpr=1 600w, https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=600&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=600&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=754&fit=crop&dpr=1 754w, https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=754&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=754&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Illustration of a color system with 20 hues.</span>
<span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:MunsellColorWheel.svg">Thenoizz</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>Does that mean that speakers of languages with fewer words for colors see less color? No, just as English speakers can see the difference between the “blue” of the sky and the “blue” of an M&M. Moreover, if language words limited our perception of color, words wouldn’t be able to change; speakers would not be able to add new distinctions. </p>
<p>My colleague <a href="http://hannahhaynie.com/">Hannah Haynie</a> and <a href="http://campuspress.yale.edu/clairebowern">I</a> were interested in how color terms might change over time, and in particular, in how color terms might change as a system. That is, do the words change independently, or does change in one word trigger a change in others? <a href="http://doi.org/10.1073/pnas.1613666113">In our research, recently published in the journal PNAS</a>, we used a computer modeling technique more common in biology than linguistics to investigate typical patterns and rates of color term change. Contrary to previous assumptions, what we found suggests that color words aren’t unique in how they evolve in language.</p>
<h2>Questioning common conceptions on colors</h2>
<p>Previous work (such as by anthropological linguists <a href="http://www.ucpress.edu/op.php?isbn=9780520076358">Brent Berlin and Paul Kay</a>) has suggested that the order in which new color terms are added to a language is largely fixed. Speakers begin with two terms – one covering “black” and dark hues, the other covering “white” and light hues. There are plenty of languages with only two color terms, but in all cases, one of the color terms is centered on “black” and the other on “white.”</p>
<p>When a language has three terms, the third is one is almost always centered on hues that English speakers would call “red.” There are no languages with three color terms where the named colors are centered on black, white and light green, for example. If a language has four color terms, they will be black, white, red and either yellow or green. In the next stage, both yellow and green are present, while the next color terms to be added are blue and brown (in that order). Cognitive scientists and linguists such as <a href="http://lclab.berkeley.edu/papers/tics2-published.pdf">Terry Regier</a> have argued that these particular parts of the color spectrum are most noticeable for people.</p>
<p>Berlin and Kay also hypothesized that language speakers don’t lose color terms. For example, once a language has a distinction between “red-like” hues (such as blood) and “yellow-like” ones (such as bananas), they wouldn’t collapse the distinction and go back to calling them all by the same color name again.</p>
<p>This would make color words quite different from other areas of language change, where words come and go. For example, words can <a href="http://dx.doi.org/10.1016/B0-08-044854-2/01105-6">change their meaning</a> when they are used metaphorically, but over time the metaphoric meaning becomes basic. They can broaden or narrow their meanings; for example, English “starve” used to mean “die” (generally), not “die of hunger,” as it primarily means now. “Starve” has also acquired metaphorical meanings.</p>
<p>That there’s something unique about the stability of color concepts is an assumption we wanted to investigate. We were also interested in patterns of color naming and where color terms come from. And we wanted to look at the rates of change – that is, if color terms are added, do speakers tend to add lots of them? Or are the additions more independent, with color terms added one at a time?</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Everyone sees them all, but languages divide them into different color terms.</span>
<span class="attribution"><a class="source" href="http://www.shutterstock.com/pic.mhtml?id=300363659&src=lb-29877982">Colors image via www.shutterstock.com.</a></span>
</figcaption>
</figure>
<h2>Modeling how a language tree grew</h2>
<p>We tested these ideas using color words in Australian Aboriginal languages. We worked with Australian languages (rather than European or other languages) for several reasons. Color demarcations vary in Indo-European, but the number of colors in each language is pretty similar; the ranges differ but the number of colors don’t vary very much. Russian has two terms that cover the hues that English speakers call “blue,” but Indo-European languages have many terms.</p>
<p>In contrast, Australian languages are a lot more variable, ranging from systems like Darkinyung’s, with just two terms (<em>mining</em> for “black” and <em>barag</em> for “white”), to languages like Kaytetye, where there are at least eight colors, or Bidyara with six. That variation gave us more points of data. Also, there are simply a lot of languages in Australia: Of the more than 400 spoken at the time of European settlement, we had color data for 189 languages of the Pama-Nyungan family, from the <a href="http://pamanyungan.net/chirila">Chirila</a> <a href="https://scholarspace.manoa.hawaii.edu/bitstream/handle/10125/24685/bowern.pdf">database</a> of Australian languages.</p>
<p>In order to answer these questions, we used techniques originally developed in biology. Phylogenetic methods use computers to study the remote past. In brief, we use probability theory, combined with a family tree of languages, to make a model of what the history of the color words might have been.</p>
<p>First, we construct a tree that shows how languages are related to one another. The <a href="https://en.wikipedia.org/wiki/Pama_nyungan">contemporary Pama-Nyungan languages</a> are all descended from a single ancestor language. Over 6,000 years, Proto-Pama-Nyungan split into different dialects, and those dialects turned into different languages: about 300 of them at the time of the European settlement of Australia. Linguists usually show those splits on a family tree diagram. </p>
<figure class="align-left zoomable">
<a href="https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=842&fit=crop&dpr=1 600w, https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=842&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=842&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=1059&fit=crop&dpr=1 754w, https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=1059&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=1059&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Family tree of Australian languages with their color terms and reconstructions of color systems for major subgroups.</span>
<span class="attribution"><span class="source">Haynie and Bowern (2016): Figure 3</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>Then, we build a model for that tree of how different features (in this case, color terms) are gained or lost, and how quickly those features might change. This is a complicated problem; we estimate likely reconstructions, evaluate that model for how well it fits our hypotheses, tweak the model parameters a bit to produce a different set of results, score that model, and so on. We repeat this many times (millions of times, usually) and then take a random sample of our estimates. This method is due originally to evolutionary biologists <a href="http://www.evolution.reading.ac.uk/">Mark Pagel and Andrew Meade</a>.</p>
<p>Estimates that are very consistent (like reconstructing terms for “black,” “white” and “red”) are highly likely to be good reconstructions. Other forms were consistently reconstructed as absent (for instance, “blue” from many parts of the tree). A third set of forms were more variable, such as “yellow” and “green” in some parts of the tree; in that case, we have some evidence they were present, but it’s unclear. </p>
<p>Our results supported some of the previous findings, but questioned others. In general, our findings backed up Berlin and Kay’s ideas about the sequential adding of terms, in the order they proposed. For the most part, our color data showed that Australian languages also show the patterns of color term naming that have been proposed elsewhere in the world; if there are three named colors, they will be black, white and red (not, for example, black, white and purple). But we show that it is most likely that Australian languages have lost color terms, as well as gained them. This contradicts 40 years of assumptions of how color terms change – and makes color words look a lot more like other words. </p>
<p>We also looked at where the color words themselves came from. Some were old in the family, and seemed to go back as color terms. Others relate to the environment (like <em>tyimpa</em> for “black” in Yandruwandha, which is related to a word which means “ashes” in other languages) or to other color words (compare Yolŋu <em>miku</em> for “red,” which also sometimes means simply “colored”). So Australian languages show similar sources of color terms to languages elsewhere in the world: color words change when people draw analogies with items in their environment.</p>
<p>Our research shows the potential for using language change to study areas of science that have previously been more closely examined by fields such as psychology. Psychologists and psycholinguists have described how constraints from our vision systems lead to particular areas of the color spectrum being named. We show that these constraints apply to color loss as well as gain. Just as it’s a lot easier to see a chameleon when it moves, language change makes it possible to see how words are working.</p><img src="https://counter.theconversation.com/content/68641/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Claire Bowern receives funding from the National Science Foundation and the Australian Research Council. She is Vice-President of the Endangered Language Fund. </span></em></p>New research investigates how people sequentially add new color terms to languages over time – and the results hold surprises about assumptions linguists have made for 40 years.Claire Bowern, Associate Professor of Linguistics, Yale UniversityLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/656192016-09-21T00:01:46Z2016-09-21T00:01:46ZWhy isn’t science better? Look at career incentives<figure><img src="https://images.theconversation.com/files/138450/original/image-20160920-11131-1alomb3.jpg?ixlib=rb-1.1.0&rect=49%2C65%2C5289%2C3660&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Experiment design affects the quality of the results.</span> <span class="attribution"><a class="source" href="https://www.flickr.com/photos/iaea_imagebank/8147632150">IAEA Seibersdorf Historical Images</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span></figcaption></figure><p>There are often substantial gaps between the idealized and actual versions of those people whose work involves providing a social good. Government officials are supposed to work for their constituents. Journalists are supposed to provide unbiased reporting and penetrating analysis. And scientists are supposed to relentlessly probe the fabric of reality with the most rigorous and skeptical of methods. </p>
<p>All too often, however, what should be just isn’t so. In a number of scientific fields, <a href="https://www.washingtonpost.com/news/speaking-of-science/wp/2015/08/28/no-sciences-reproducibility-problem-is-not-limited-to-psychology/">published findings turn out not to replicate</a>, or to have smaller effects than, what was initially purported. Plenty of science does replicate – meaning the experiments turn out the same way when you repeat them – but the amount that doesn’t is too much for comfort.</p>
<p>Much of science is about identifying relationships between variables. For example, how might certain genes increase the risk of acquiring certain diseases, or how might certain parenting styles influence children’s emotional development? To our disappointment, there are no tests that allow us to perfectly sort true associations from spurious ones. Sometimes we get it wrong, even with the most rigorous methods.</p>
<p>But there are also ways in which scientists increase their chances of getting it wrong. Running studies with small samples, mining data for correlations and forming hypotheses to fit an experiment’s results after the fact are <a href="http://fivethirtyeight.com/features/science-isnt-broken/">just some of the ways</a> to <a href="http://doi.org/10.1038/526182a">increase the number of false discoveries</a>. </p>
<p>It’s not like we don’t know how to do better. Scientists who study scientific methods have known about <a href="http://doi.org/10.1086/288135">feasible remedies for decades</a>. Unfortunately, their advice often falls on deaf ears. Why? Why aren’t scientific methods better than they are? In a word: incentives. But perhaps not in the way you think. </p>
<h2>Incentives for ‘good’ behavior</h2>
<p>In the 1970s, <a href="https://en.wikipedia.org/wiki/Campbell%27s_law">psychologists</a> and <a href="https://en.wikipedia.org/wiki/Goodhart%27s_law">economists</a> began to point out the danger in relying on quantitative measures for social decision-making. For example, when public schools are evaluated by students’ performance on standardized tests, teachers respond by teaching “to the test” – at the expense of broader material more important for critical thinking. In turn, the test serves largely as a measure of how well the school can prepare students for the test.</p>
<p>We can see this principle – often summarized as “when a measure becomes a target, it ceases to be a good measure” – playing out in the realm of research. Science is a competitive enterprise. There are <a href="http://doi.org/10.1038/520144a">far more credentialed scholars and researchers</a> than there are university professorships or comparably prestigious research positions. Once someone acquires a research position, there is additional competition for tenure, grant funding, and support and placement for graduate students. Due to this competition for resources, scientists must be evaluated and compared. How do you tell if someone is a good scientist?</p>
<p>An oft-used metric is the number of publications one has in peer-reviewed journals, as well as the status of those journals (along with related metrics, such as the <a href="https://en.wikipedia.org/wiki/H-index"><em>h</em>-index</a>, which purports to measure the rate at which a researcher’s work is cited by others). Metrics like these make it straightforward to compare researchers whose work may otherwise be quite different. Unfortunately, this also makes these numbers susceptible to exploitation. </p>
<p>If scientists are motivated to publish often and in high-impact journals, we might expect them to actively try to game the system. And certainly, some do – as seen in recent high-profile cases of scientific fraud (including in <a href="https://en.wikipedia.org/wiki/Sch%C3%B6n_scandal">physics</a>, <a href="http://www.nytimes.com/2013/04/28/magazine/diederik-stapels-audacious-academic-fraud.html">social psychology</a> and <a href="http://onlinelibrary.wiley.com/doi/10.1111/bcp.12992/full">clinical pharmacology</a>). If malicious fraud is the prime concern, then perhaps the solution is simply heightened vigilance.</p>
<p>However, most scientists are, I believe, genuinely interested in learning about the world, and honest. The problem with incentives is they can shape cultural norms without any intention on the part of individuals. </p>
<h2>Cultural evolution of scientific practices</h2>
<figure class="align-right zoomable">
<a href="https://images.theconversation.com/files/138454/original/image-20160920-11090-684nc6.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/138454/original/image-20160920-11090-684nc6.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/138454/original/image-20160920-11090-684nc6.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=784&fit=crop&dpr=1 600w, https://images.theconversation.com/files/138454/original/image-20160920-11090-684nc6.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=784&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/138454/original/image-20160920-11090-684nc6.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=784&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/138454/original/image-20160920-11090-684nc6.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=986&fit=crop&dpr=1 754w, https://images.theconversation.com/files/138454/original/image-20160920-11090-684nc6.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=986&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/138454/original/image-20160920-11090-684nc6.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=986&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Scientists work within a culture of research.</span>
<span class="attribution"><a class="source" href="https://www.flickr.com/photos/iaea_imagebank/8199500456">IAEA</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span>
</figcaption>
</figure>
<p>In a <a href="http://rsos.royalsocietypublishing.org/lookup/doi/10.1098/rsos.160384">recent paper</a>, anthropologist <a href="http://xcelab.net/rm/">Richard McElreath</a> and I considered the incentives in science through the lens of <a href="http://www.oxfordbibliographies.com/view/document/obo-9780199766567/obo-9780199766567-0038.xml">cultural evolution</a>, an emerging field that draws on ideas and models from evolutionary biology, epidemiology, psychology and the social sciences to understand cultural organization and change.</p>
<p>In our analysis, we assumed that methods associated with greater success in academic careers will, all else equal, tend to spread. The spread of more successful methods requires no conscious evaluation of how scientists do or do not “game the system.” </p>
<p>Recall that publications, particularly in high-impact journals, are the currency used to evaluate decisions related to hiring, promotions and funding. Studies that show large and surprising associations tend to be favored for publication in top journals, while small, unsurprising or complicated results are more difficult to publish.</p>
<p>But <a href="http://dx.doi.org/10.1371/journal.pmed.0020124">most hypotheses are probably wrong</a>, and performing rigorous tests of novel hypotheses (as well as coming up with good hypotheses in the first place) takes time and effort. Methods that boost false positives (incorrectly identifying a relationship where none exists) and overestimate effect sizes will, on average, allow their users to publish more often. In other words, when novel results are incentivized, methods that produce them – by whatever means – at the fastest pace will become implicitly or explicitly encouraged.</p>
<p>Over time, those shoddy methods will become associated with success, and they will tend to spread. The argument can extend beyond norms of questionable research practices to norms of misunderstanding, if those misunderstandings lead to success. For example, despite over a century of common usage, the <em>p</em>-value, a standard measure of statistical significance, is still <a href="http://dx.doi.org/10.1080/00031305.2016.1154108">widely misunderstood</a>.</p>
<p>The cultural evolution of shoddy science in response to publication incentives requires no conscious strategizing, cheating or loafing on the part of individual researchers. There will always be researchers committed to rigorous methods and scientific integrity. But as long as institutional incentives reward positive, novel results at the expense of rigor, the rate of bad science, on average, will increase. </p>
<h2>Simulating scientists and their incentives</h2>
<p>There is ample evidence suggesting that publication incentives have been negatively shaping scientific research for decades. The frequency of the words <a href="http://dx.doi.org/10.1136/bmj.h6467">“innovative,” “groundbreaking” and “novel”</a> in biomedical abstracts increased by 2,500 percent or more over the past 40 years. Moreover, researchers often <a href="http://dx.doi.org/10.1126/science.1255484">don’t report when hypotheses fail to generate positive results</a>, lest reporting such failures hinders publication.</p>
<figure class="align-left zoomable">
<a href="https://images.theconversation.com/files/138455/original/image-20160920-11127-ntmb9h.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/138455/original/image-20160920-11127-ntmb9h.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/138455/original/image-20160920-11127-ntmb9h.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=736&fit=crop&dpr=1 600w, https://images.theconversation.com/files/138455/original/image-20160920-11127-ntmb9h.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=736&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/138455/original/image-20160920-11127-ntmb9h.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=736&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/138455/original/image-20160920-11127-ntmb9h.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=925&fit=crop&dpr=1 754w, https://images.theconversation.com/files/138455/original/image-20160920-11127-ntmb9h.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=925&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/138455/original/image-20160920-11127-ntmb9h.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=925&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">There doesn’t need to be anything nefarious going on for scientists to stick with the suboptimal methods that help them get ahead.</span>
<span class="attribution"><a class="source" href="https://www.flickr.com/photos/iaea_imagebank/8198415199">IAEA</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span>
</figcaption>
</figure>
<p>We reviewed <a href="http://www.statisticsdonewrong.com/power.html">statistical power</a> in the social and behavioral science literature. Statistical power is a quantitative measurement of a research design’s ability to identify a true association when present. The simplest way to increase statistical power is to increase one’s sample size – which also lengthens the time needed to collect data. Beginning in the 1960s, there have been <a href="http://datacolada.org/wp-content/uploads/2013/10/3416-Sedlmeier-Gigerenzer-Psych-Bull-1989-Do-studies-of-statistical-power-have-an-effect-on-the-power-of-studies.pdf">repeated outcries that statistical power is far too low</a>. Nevertheless, we found that statistical power, on average, <a href="http://rsos.royalsocietypublishing.org/lookup/doi/10.1098/rsos.160384">has not increased</a>.</p>
<p>The evidence is suggestive, but it is not conclusive. To more systematically demonstrate the logic of our argument, we built a computer model in which a population of research labs studied hypotheses, only some of which were true, and attempted to publish their results.</p>
<p>As part of our analysis, we assumed that each lab exerted a characteristic level of “effort.” Increasing effort lowered the rate of false positives, and also lengthened the time between results. As in reality, we assumed that novel positive results were easier to publish than negative results. All of our simulated labs were totally honest: they never cheated. However, labs that published more were more likely to have their methods “reproduced” in new labs – just as they would be in reality as students and postdocs leave successful labs where they trained and set up their own labs. We then allowed the population to evolve.</p>
<p>The result: Over time, effort decreased to its minimum value, and the rate of false discoveries skyrocketed. </p>
<p>And replication – while a crucial tool for generating robust scientific theories – isn’t going to be science’s savior. Our simulations indicate that more replication won’t stem the evolution of bad science.</p>
<h2>Taking on the system</h2>
<p>The bottom-line message from all this is that it’s not sufficient to impose high ethical standards (assuming that were possible), nor to make sure all scientists are informed about best practices (though spreading awareness is certainly one of our goals). A culture of bad science can evolve as a result of institutional incentives that prioritize simple quantitative metrics as measures of success. </p>
<p>There are indications that the situation is improving. Journals, organizations, and universities are increasingly emphasizing <a href="http://www.psychologicalscience.org/index.php/replication">replication</a>, <a href="https://royalsociety.org/journals/ethics-policies/data-sharing-mining/">open data</a>, <a href="http://blogs.plos.org/everyone/2015/02/25/positively-negative-new-plos-one-collection-focusing-negative-null-inconclusive-results/">the publication of negative results</a> and more <a href="https://www.idrc.ca/sites/default/files/sp/Documents%20EN/Research-Quality-Plus-A-Holistic-Approach-to-Evaluating-Research.pdf">holistic evaluations</a>. Internet applications such as <a href="https://twitter.com/lakens/status/774953862012755968">Twitter</a> and <a href="https://www.youtube.com/watch?v=WFv2vS8ESkk&list=PLDcUM9US4XdMdZOhJWJJD4mDBMnbTWw_z">YouTube</a> allow education about best practices to propagate widely, along with spreading norms of holism and integrity. </p>
<p>There are also signs that the old ways are far from dead. For example, one regularly hears researchers discussed in terms of how much or where they publish. The good news is that as long as there are smart, interesting people doing science, there will always be some good science. And from where I sit, there is still quite a bit of it.</p><img src="https://counter.theconversation.com/content/65619/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Paul Smaldino 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.</span></em></p>Embracing more rigorous scientific methods would mean getting science right more often than we currently do. But the way we value and reward scientists makes this a challenge.Paul Smaldino, Assistant Professor of Cognitive and Information Sciences, University of California, MercedLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/510922015-11-24T10:16:56Z2015-11-24T10:16:56ZWhy does culture sometimes evolve via sudden bursts of innovation?<figure><img src="https://images.theconversation.com/files/102907/original/image-20151123-18255-1kg56i6.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">A particularly fruitful moment for technological innovation?</span> <span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:Каменный_век_(1).jpg">Viktor M Vasnetsov</a></span></figcaption></figure><p>Human beings inherit many genetic traits directly from their parents. However, cultural traits – tools, beliefs and behaviors that are transmitted by learning – can be passed on not only by parents but also teachers and peers. Many animals have learned behaviors, but people are uniquely good at building on existing knowledge to innovate further. This capacity, known as <a href="http://doi.org/10.1111/brv.12053">cumulative culture</a>, was captured by Sir Isaac Newton when he said, “If I have seen further, it is by <a href="http://www.bbc.co.uk/worldservice/learningenglish/movingwords/shortlist/newton.shtml">standing on the shoulders of giants</a>.”</p>
<p>We can see evidence of this cumulative culture in the archaeological record; over time, there’s an accelerating increase in the number of tools people use. But the archaeological record reveals another pattern, too: there’s also evidence for large-scale <em>losses</em> of culture. For example, archaeological excavation suggests that Aboriginal populations in Tasmania <a href="http://doi.org/10.1038/273185a0">lost numerous technologies</a> over time, including nets, bone tools and warm clothing, even though these tools might still have been useful.</p>
<p>And it doesn’t seem like cultural accumulation just proceeds through time at a regular pace. The archaeological record shows some evidence of large bursts of innovation occurring after relatively long periods of little change. For example, the early human archaeological record is composed primarily of stone tools for approximately two million years. Then, from about 60,000 to 30,000 years ago, archaeologists find a burst of <a href="http://www.tandf.net/books/details/9781138007062/">creative activity</a>, such as burial sites, art forms including cave paintings and statues, and engraved bone and antler tools.</p>
<p>The process of change in the frequency and distribution of cultural traits over time is known as cultural evolution. But what drives it? Why would the inventory of tools expand at some times and diminish at others? These are questions that have intrigued archaeologists for decades. We propose a new model we think addresses some aspects of how cultural evolution happens – and, crucially, it’s based on the idea that not all innovations occur in the same way.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/102903/original/image-20151123-18225-1j5ciau.JPG?ixlib=rb-1.1.0&rect=44%2C340%2C4191%2C2689&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/102903/original/image-20151123-18225-1j5ciau.JPG?ixlib=rb-1.1.0&rect=44%2C340%2C4191%2C2689&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/102903/original/image-20151123-18225-1j5ciau.JPG?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=450&fit=crop&dpr=1 600w, https://images.theconversation.com/files/102903/original/image-20151123-18225-1j5ciau.JPG?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=450&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/102903/original/image-20151123-18225-1j5ciau.JPG?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=450&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/102903/original/image-20151123-18225-1j5ciau.JPG?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=566&fit=crop&dpr=1 754w, https://images.theconversation.com/files/102903/original/image-20151123-18225-1j5ciau.JPG?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=566&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/102903/original/image-20151123-18225-1j5ciau.JPG?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=566&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Sometimes our ancestors used the same kind of stone tools with no improvements for millennia.</span>
<span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:Кременева_індустрія_трипільців_рудковецьких_поселень.JPG">В Михайлюк</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<h2>Modeling how culture advances</h2>
<p>Since it’s not possible (or ethical) to experimentally manipulate large groups of people, scientists make mathematical models to try to understand how cultural traits evolve. A model of this kind is a set of rules that describe mechanisms that may underlie the process we’re interested in.</p>
<p>For example, a model of cultural evolution could use equations to describe the rate at which individuals invent new things, transmit their knowledge and learn from others. These equations would depend on a number of parameters – things like population size and the rates of invention and learning.</p>
<p>A model can be explored analytically, by calculating what patterns the set of equations predicts, or it could be explored using computer simulations. In our research we did both.</p>
<p>Most of the models of cultural evolution study the spread of technologies and behaviors that already exist in a population. In our recent PNAS paper, coauthored with Stanford’s Marcus Feldman, we introduce a new model of <a href="http://www.pnas.org/content/early/2015/11/18/1520492112.full.pdf">cultural evolution</a>. What’s different about our model is quite simple: we don’t assume all human innovations are created in the same way. </p>
<h2>Watching our model’s predictions unfold</h2>
<p>Working with a model is kind of like playing a scientifically minded game of <a href="https://www.thesims.com">The Sims</a>. On the computer, we simulate a human population of a certain size. We set the rules for a number of interdependent innovation processes to occur at different rates. For example, inventions that can be viewed as “strokes of genius” may be rare, while the invention of tools that are versions of existing ones might be more frequent.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/102905/original/image-20151123-18230-kodflr.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/102905/original/image-20151123-18230-kodflr.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/102905/original/image-20151123-18230-kodflr.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/102905/original/image-20151123-18230-kodflr.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/102905/original/image-20151123-18230-kodflr.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/102905/original/image-20151123-18230-kodflr.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/102905/original/image-20151123-18230-kodflr.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/102905/original/image-20151123-18230-kodflr.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Once people figure out how to fish with a net, additional improvements and combinations with existing technologies can come fast and furious.</span>
<span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:Kochi_chinese_fishing-net-20080215-01a.jpg">Hans A Rosbach</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span>
</figcaption>
</figure>
<p>We allow new “large leaps” in knowledge to occur at a certain rate per person. Once someone in the population has made one of these rare large leaps, other innovations might occur more readily. For example, the invention of a fishing net could lead to other related tools – maybe a weight to sink the net – or combinations with other tools, such as adding a pole to wield it. </p>
<p>These different processes of innovation – lightning-bolt ideas and incremental improvements – occur at different rates. The relationships between them determine whether the accumulation of tools occurs in a stepwise pattern. If large innovative leaps are fairly common, the number of tools in the population can show smooth, accelerating growth. On the other hand, if large-leap innovations are rare, but populations readily invent related tools and frequently combine existing technologies into novel tools, then each new large leap will lead to a rapid burst of cultural innovations in a punctuated pattern.</p>
<p>There are two other important contributors to cultural evolution that our model takes into account. The first is the differential distribution of knowledge in a population. We set our model’s “rules” so knowledge can be concentrated in a subset of the population, such as medicine-men or -women. When knowledge is restricted to a small group, there’s more risk that it <a href="http://www.jstor.org/stable/4128416">may be lost</a>.</p>
<p>Second, our model considers the impact of environmental change. Tools can be lost following a change in environment – think of a climate becoming warmer or cooler – or migration to a new place where existing tools aren’t particularly useful. Our model keeps track of the environments in which every tool is useful – a fishing net won’t be as useful in the savanna, for example. Tools are more likely to be lost when they’re not useful in the current environment.</p>
<h2>Real-life reasons for what the model predicts</h2>
<p>Researchers continue to debate reasons for the sudden bursts of cultural accumulation in the archaeological record. The general consensus attributes this pattern to external events. Human beings come up with a rush of new ideas due to a change in environment (a survival challenge caused by drought, for instance) or the evolution of new cognitive capacity (brains getting bigger and more powerful).</p>
<p>Our model demonstrates that this punctuated pattern of “cultural explosions” could actually be a feature of cultural evolution itself, playing a role alongside other evolutionary and environmental processes. As long as some innovations are dependent on the existence of other innovations – which is a fundamental feature of human culture – these kinds of bursts in new technology are to be expected.</p>
<p>Our research sheds new light on cultural evolution, deepening our understanding of ancient human evolution. It also reflects how innovation could lead to future technologies that are as yet unimagined.</p><img src="https://counter.theconversation.com/content/51092/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Nicole Creanza receives funding from the Stanford Center for Computational, Evolutionary, and Human Genomics and the Templeton Foundation. </span></em></p><p class="fine-print"><em><span>Oren Kolodny receives funding from the Stanford Center for Computational, Evolutionary, and Human Genomics and from the Templeton Fund. </span></em></p>Not all technologies are created equal. Researchers devised a new model to explain why, after eons of nothing much new, we sometimes see an explosion of innovation in the archaeological record.Nicole Creanza, Postdoctoral Research Fellow in Biology, Stanford UniversityOren Kolodny, Postdoctoral Research Fellow in Biology, Stanford UniversityLicensed as Creative Commons – attribution, no derivatives.