bower and clark 1969 experiment

• DOI: 10.1016/S0022-5371(69)80124-6
• Corpus ID: 15861544

Hierarchical retrieval schemes in recall of categorized word lists

• G. Bower , M. Clark , +1 author David Winzenz
• Published 1 June 1969
• Journal of Verbal Learning and Verbal Behavior

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Retrieval in cued recall, coding processes in the free recall of associated word lists, effects of input order and category cues on serial recall, effects of semantic list structure differences in free recall, limits of the retrieval-inhibition construct: list segregation in directed forgetting, a consolidated theoretical view of stimulus-list organization effects in free recall, emergence of hierarchical organization in memory for random material, encoding specificity and retrieval processes in episodic memory., proximity analysis and the structure of organization in free recall., inhibition in recall from cueing with recall targets, 31 references, availability versus accessibility of information in memory for words, clustering in free recall as a function of certain methodological variations., cued recall and free recall as a function of the number of items per cue, implicit responses and conceptual similarity, form and amount of internal structure as factors in free-recall learning of nonsense words, category names as cues for the recall of category instances, organization and memory, familiarity and free recall, grammatical intrusions in the free recall of structured letter pairs, some-or-none characteristics of coding behavior, related papers.

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Article Contents

Introduction: making science meaningful, story, narrative, and storytelling, how do we know that storytelling improves communication, story structure, essential elements of story, addressing common concerns, moving forward, acknowledgments.

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Making Science Meaningful for Broad Audiences through Stories

From the symposium “Science Through Narrative: Engaging Broad Audiences” presented at the annual meeting of the Society for Integrative and Comparative Biology, January 3–7, 2018 at San Francisco, California.

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Sara J ElShafie, Making Science Meaningful for Broad Audiences through Stories, Integrative and Comparative Biology , Volume 58, Issue 6, December 2018, Pages 1213–1223, https://doi.org/10.1093/icb/icy103

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Science is a search for evidence, but science communication must be a search for meaning. General audiences will only care about science if it is presented in a meaningful context. One of the most effective ways to do this is through storytelling. Stories are integral to all cultures. Studies indicate that stories even help audiences to process and recall new information. Scientists sometimes worry that storytelling will conflate empirical evidence with fabrication. But when telling non-fiction stories, it is a process of recognizing the story elements already present in the subject material and distilling the most concise and compelling account for a target audience. In this paper, I review literature, offer examples, and draw from my experience as a scientist and a communication trainer to explore how storytelling makes science comprehensible and meaningful for general audiences.

Allow me to begin this paper with a story …

When I began studying paleontology as an undergraduate, I felt like a black sheep in the family. My relatives all had occupations that dealt with everyday problems, like feeding and healing people. Every time a relative asked me, “So what is your research about?,” I got the same feeling of dread. I would try to explain my work (“I study fossil lizards that were abundant in the US Western Interior during the Paleogene!”), and they would nod politely and change the subject. Despite my passion for the field, I was inadvertently making it impossible for others to share my enthusiasm. It bothered me that I did not know how to convey the importance of my work to my own family.

I was now a year into my PhD program. As I began preparing for my qualifying examination, I decided that I needed to address my communication problem before I started my dissertation. But where to start? At family gatherings, my relatives swapped stories. I realized that I had learned a lot about their work through those stories. I needed to learn how to tell stories about my work that would appeal to them as well. If I could do that with my relatives, I could probably do that with anyone.

It just so happened that some masters of storytelling were located close to my university campus. I contacted Pixar Animation Studios to see if anyone there would be interested in coming to chat with a group of graduate students in my department. To my complete shock, I actually got a response. We started planning a seminar. I had loved Pixar movies since I was a kid, and now we were going to learn about storytelling from my childhood heroes! The timing was also perfect because I had just been invited to give a talk at a public paleontology festival called PaleoFest ( Burpee Museum of Natural History 2016 ). I already had a talk prepared from my Master’s thesis defense, but I was hoping to pick up a few tips to help tailor it for a public audience.

In our campus seminar, an artist from Pixar gave an entertaining and perceptive overview of basic storytelling tools that they use at the studio. I realized that I was already familiar with many of these terms and concepts. But I was surprised to realize that I had never thought about them in the context of communicating science. It had not occurred to me that telling a story with a protagonist and a plot could be just as useful in science as in fiction. I was also reminded by this artist that the most important rule in storytelling is to make your audience care. Even in stories about toys or monsters or superheroes, the story has to be emotionally compelling ( Pixar Animation Studios 2017 ). Otherwise, it won’t mean anything to the audience. Pixar’s filmmakers had a lot more in common with scientists than I thought. Whether empirical evidence or whimsical fantasy, the goal is to connect with the audience.

When I got home that night, I was exhilarated. Storytelling was clearly the best starting point to figure out how to connect with my family, and with the public! But as I began modifying my thesis slides for PaleoFest, I started to panic. I realized that I would have to change the entire talk. My slides focused too much on the specifics of my research and offered little meaning for a broad audience (“Body size and species richness change in Glyptosaurinae through climatic transitions of the North American Cenozoic” –that'll really get the kids inspired!). What might a bunch of families and fossil enthusiasts actually care about (beyond just “fossils are cool”)? How could I tie that to my particular research? I sat down and began to brainstorm.

The dilemma in the story above may sound familiar. Perhaps you too have struggled to explain your work to your family. I’m willing to bet that you have come across scientific reports or presentations that offered no clear relevance for a general audience. Scientists are trained to be objective when conducting research. A scientist’s personal perspective on his or her work blurs that objectivity, and thus technical scientific writing tends to be indifferent to the actual experience of doing science ( Olson 2009 , 2015 ; Baron 2010 ; Schimel 2012 ; Olson et al. 2013 ; Green et al. 2018 ; Padian 2018 ). Communication, in contrast, is about building understanding between different perspectives. To do this, we cannot assume that objectivity will be appealing ( Fiske and Dupree 2014 ) or that scientific evidence will speak for itself ( Dean 2009 ; Baron 2010 ; Schimel 2012 ; Fischhoff et al. 2013 , 2014 ; Luna 2013 ; National Academy of Sciences 2014 , 2017a , 2018 ). Broad audiences understand science when we make it meaningful to them ( Dean 2009 ; Olson 2009 , 2015 ; Baron 2010 ; Olson et al. 2013 ; Alda 2017 ; Rather 2017 ).

One of the best ways to make an idea meaningful is through storytelling ( Avraamidou and Osborne 2009 ; Olson 2009 , 2015 ; Olson et al. 2013 ; Hadzigeorgiou 2016 ; Alda 2017 ; Rather 2017 ; Mazurkewich 2018 ; Padian 2018 ). Stories have always been integral to human culture ( Campbell 1949 ; Vogler 2007 ; Gottschall 2012 ; Harari 2015 ; Padian 2018 ), and are deeply rooted in our cognitive processing ( Bruner 1986 ; Falk and Dierking 2000 ; Kahneman 2011 ; Cron 2012 ; Sanford and Emmott 2012 ). Stories put new information into a familiar context, which both focuses attention ( Schank and Abelson 1995 ; Hasson et al. 2008 ; Stephens et al. 2010 ) and elicits emotion ( Barraza et al. 2015 ; Zak 2015 ). Stories help an audience to comprehend, recall, and care about the content presented ( Bower and Clark 1969 ; Graesser et al. 2002 ). Storytelling can therefore help scientists to engage with broad audiences and make even the most abstruse scientific concepts accessible ( Olson et al. 2013 ; Olson 2015 ).

The difference between “story” and “narrative” depends on whom you ask ( Avraamidou and Osborne 2009 ). Dictionary definitions often give reciprocal explanations of the terms—e.g., narrative: “something that is narrated; story, account” ( Merriam Webster 2015 ), versus story: “an oral or written narrative account of events” ( Oxford English Dictionary 2017 ). Sanford and Emmott (2012 ) offer a helpful review of literature on what constitutes a “narrative” versus a “story.” They find that, at minimum, there is some consensus that a “narrative” is a series of chronological, causal events. A “story,” according to their review, must include a setting (a main character, location, and time), a plot (in which the main character pursues a goal), and a resolution (outcome of that pursuit). A “narrative” tells a “story” when something unusual happens that sets the events of a plot in motion ( Hühn et al. 2009 ; Sanford and Emmott 2012 ; Olson 2015 ). For extensive discussion of these terms, see especially Bruner (1986 ), Simmons (2001 ), Norris et al. (2005 ), Avraamidou and Osborne (2009 ), McKee (2010 ), Gottschall (2012 ), Olson et al. (2013 ), Olson (2015 ), and the references cited under the “Story structure” section.

A good story cannot be devised. It has to be distilled. —Raymond Chandler, quoted by Schimel (2012)

This is true of fiction and especially of nonfiction storytelling. Some worry that science storytelling will misconstrue empirical evidence (e.g., Katz 2013 ), but the purpose of nonfiction storytelling is to offer a clear and compelling account of true events ( Simmons 2001 ; Vogler 2007 ; Baron 2010 ; Sachs 2012 ; Schimel 2012 ; Luna 2013 ; Olson et al. 2013 ; Olson 2015 ), not to alter facts. Science communication, like storytelling, is a process of distilling the most salient information from a complex body of work ( Dean 2009 ; Baron 2010 ; Schimel 2012 ; Luna 2013 ; COMPASS 2017 ). A science storyteller does not change the truth in the evidence; rather, she or he distills the story that the evidence tells. The appropriate information to include depends on the audience, the context of the communication, and the goals for that interaction ( Avraamidou and Osborne 2009 ; Dean 2009 ; Nisbet and Scheufele 2009 ; Olson 2009 , 2015 ; Baron 2010 ; Schimel 2012 ; Fischhoff et al. 2013 , 2014 ; Olson et al. 2013 ; National Academy of Sciences 2018 ). Every scientist does this when writing a manuscript or preparing a presentation. A scientist who understands the mechanics of story will be more effective at it ( Avraamidou and Osborne 2009 ; Olson 2015 ; Green et al. 2018 ; Padian 2018 ).

Beyond distilling information, a compelling story has enough emotional significance to be meaningful to the audience ( Simmons 2001 ; Vogler 2007 ; McKee 2010 ; Sachs 2012 ). Emotional significance is also critical for effective science communication—in this context, it is often called the “So What?” factor ( COMPASS 2017 ), “What’s the Big Idea?,” or something similar. Storytelling can therefore help scientists to consider the potential emotional impact of their work in addition to the scientific impact ( Avraamidou and Osborne 2009 ; Olson 2009 , 2015 ; Olson et al. 2013 ; Alda 2017 ; Green et al. 2018 ; Padian 2018 ).

Bruner (1985) claimed that “there are two irreducible modes of cognitive functioning” (p. 97). “Paradigmatic mode” is for rational thinking—logic and problem solving, regardless of context. The other, “narrative mode,” seeks meaningful explications that are sensitive to context. Years later, after extensive research, Kahneman (2011) used a similar dichotomy to describe human cognition. He characterized “System 1” as our default mode of mental processing, constantly creating stories out of new information. “System 2,” akin to Bruner’s “paradigmatic mode,” deals with complex problem solving and can only work in short bursts. Scientists would thus do well to speak to an audience’s System 1 by telling a story, rather than exhausting System 2 with technicalities.

Recent studies indicate that people are neurologically prone to focus on content with story structure. In one experiment, Hasson et al. (2008) monitored the brain activity of four groups of volunteers while showing each group a different type of footage. The footage ranged in story intensity from an Alfred Hitchcock film (strong story, strong suspense) to footage taken in a nearby park (no story, no suspense). The people watching the Hitchcock film had the highest similarity in brain activity relative to each other; the people watching park footage had no similarity at all. This result may not seem surprising, but the implications are profound. By using story structure, especially with high suspense, a storyteller can essentially sync the brainwaves of audience members. Without a story, an audience may as well be watching pigeons.

This phenomenon of brain waves syncing while processing stories is called neural coupling . In a follow up study ( Stephens et al. 2010 ), a speaker told a listener a story while scientists monitored the neural activity of both subjects. The brain activity of the listener mirrored that of the speaker. When that listener then recounted the same story to another listener, their respective brain activity still reflected that of the original storyteller. This study indicates that stories can align mental processing and memory in audiences. According to these conclusions, when you read my story in the prologue of this article, your brain activity would have resembled mine when I wrote the story. Likewise, if you retold that story to someone else, their brain activity would reflect yours.

Other research shows that stories not only facilitate information processing and recollection; they also elicit a hormonal response. In one study, Barraza et al. (2015) showed participants a short video about a father whose son is dying from cancer. In the video, the father describes his struggle to set aside his grief and make the most of his remaining time with his son. Barraza et al. (2015 ) found that people who watched this video had elevated blood levels of cortisol, which focuses attention, and oxytocin, which is associated with feelings of empathy (see Zak et al. 2004 , 2007 ). These participants also had activated areas of the brain that are rich in oxytocin receptors. Barraza et al. (2015) found that they could even predict with 80% accuracy which participants would donate money to a children’s cancer charity based on the levels of oxytocin in their blood after viewing the short film ( Barraza et al. 2015 ; Zak 2015 ). By comparison, a control group that watched a different video of the same father and son at a zoo, without the dramatic storyline, showed no hormonal or neurological response.

Stories clearly have a neurological and even physiological effect on us. This may explain why storytelling is ubiquitous in all cultures ( Campbell 1949 ; Gottschall 2012 ) and used in most media platforms ( Dean 2009 ; Baron 2010 ; Sachs 2012 ). Given this, and the fact that most people get their scientific information from mass media once they are out of school ( National Science Board 2012 ), the question is not whether we should be conveying science through stories, but how best to do it ( Dahlstrom 2014 ; Martinez-Conde and Macknik 2017 ).

Story structure is remarkably consistent across stories from many cultures through history ( Campbell 1949 ). Stories often begin with an exposition to set the scene, present a conflict that launches the rising action, and resolve the conflict in the climax and falling action ( Figs. 1 and 2 ). German novelist and playwright Gustav Freytag first described this “dramatic arc” in 1863 based on an analysis of Aristotle’s Poetics (ca. 335 BCE; see the 1961 English translation) and Shakespearean dramas ( Freytag 1900 ). Propp (1925) found that many folktales have a common sequence in which a main character sets out on a quest and undergoes a series of tests (see Padian [2018 ] in this volume for further discussion). Campbell (1949) studied myths and stories from all over the world going back centuries and also found that many stories follow a common arc with similar elements. In this model, commonly known as “The Hero’s Journey,” a protagonist sets out to solve a problem, undergoes a series of trials, and emerges with new knowledge about the world and herself ( Fig. 2 ). This structure is the basis of almost every story ever produced for mass audiences, from Dante's Inferno (1320; see the 2002 English translation [ Alighieri 2002 ]) to Star Wars ( Lucas 1977 ; Vogler 2007 ). Therefore, following this structure, even loosely, can put science into a familiar context for many audiences ( Olson 2015 ).

Freytag’s “pyramid,” also known as the “dramatic arc,” showing a five-part story structure with rising and falling tension over time. Based on Freytag (1900) .

“The Hero’s Journey” story model. The protagonist, or hero, starts in a familiar context (for both him/her and the audience) and receives a “Call to Adventure” that initiates a journey into a new context. The protagonist undergoes a transformation and returns to the familiar context with a new perspective. Based on Campbell (1949) . See also Vogler (2007) and Olson (2015) for extensive discussion of The Hero’s Journey in the contexts of film and science communication, respectively.

Scientific manuscripts and presentations commonly follow a structure that actually reflects a dramatic arc, in a sense. A typical manuscript starts with an Introduction (Exposition), followed by Methods (Rising Action), Results (Climax), Analysis (Falling Action), and ends with Discussion and Conclusions (Denouement or Resolution; Fig. 1 ; see Schimel 2012 ; Luna 2013 ; Olson 2015 ). Note that this “IMRAD” format does not follow the actual sequence in which the events of the study took place (see Padian [2018 ] in this volume for further discussion). The resemblance of the IMRAD format to a dramatic arc may suffice as a narrative for many scientific audiences.

Although most audiences will recognize the structure of a dramatic arc, it is often necessary to start with the “So What?” aspect of the story to hook an audience’s attention ( Schimel 2012 ; Luna 2013 ; COMPASS 2017 ). Journalists typically start a story with the main point (the “lede”), then provide the most important details, and offer more background information toward the end of the piece ( Dean 2009 ; Baron 2010 ). This approach also works well in situations that require you to hook the audience immediately, such as research proposals or short-span contexts (e.g., elevator pitches, conversations, and interactions with guests at exhibits and festivals; Baron 2010 ; Schimel 2012 ). You can also start with a short, concise narrative that gets right to the point and captures interest before elaborating with a longer story (see Olson et al. [2013] and Olson [2015] for extensive discussion of the “And–But–Therefore” format).

The ingredients considered most essential to storytelling vary slightly depending on the author (e.g., see Forbes 1999 ; Vogler 2007 ; Avraamidou and Osborne 2009 ; McKee 2010 ; Schimel 2012 ; Olson et al. 2013 for various treatments). For the purpose of engaging broad audiences with science, I have found these five elements useful: protagonist, inciting incident, obstacle, stakes, and broad theme. If one of these items is poorly developed, the story often falls flat or falls apart.

Protagonist

Most stories follow a single main character, or protagonist. Clarifying the protagonist in a story, and the objectives that motivate the protagonist, can help the audience relate to him and follow the dynamics of the story ( Olson 2015 ). It will not always be essential to name the protagonist explicitly: if the story remains centered on that character, the protagonist should be apparent to the audience.

Ideally, the protagonist must be both appealing and flawed ( Vogler 2007 ; McKee 2010 ; Olson et al. 2013 ; Olson 2015 ). The protagonist needs to be likeable enough for the audience to want to hear the story. Storytellers often make their protagonists adept, resourceful, intelligent, funny, or coming from humble origins. These likeable qualities are balanced with empathetic flaws, such as stubbornness, overthinking, overreacting, fear of attachment, indifference, or hubris (see Dorie Barton's commentary in Olson et al. 2013 ). A protagonist’s flaw may even jeopardize his objective without him realizing it ( McKee 2010 ). Forgivable flaws allow the audience to empathize with the protagonist and make the story their own.

A balance of admirable traits and forgivable flaws evokes empathy with the protagonist. An audience will be more invested in the fate of that protagonist as a result ( McKee 2010 ; Olson et al. 2013 ; Olson 2015 ). If the protagonist is a scientist, for example, was she overconfident in her assumptions, or unaware of her own biases? Did this lead to a mistake or a setback in the investigation? It is possible to humanize scientists while emphasizing that science is an iterative process of reducing uncertainty (see https://undsci.berkeley.edu/ for more details).

It can also be useful to discuss flaws in nonhuman characters. For instance, an organism, molecule, or system may have a limitation for which it must somehow (unconsciously) compensate in order to be successful. Maybe it has a negative effect on its community, environment, or planet if left unchecked. In a story about nonhuman characters, the humans are participating in the story through the narration and the audience’s reaction. The protagonist might be a migrating shark, for example, but it is the narrator and the audience who will react emotionally to the shark’s story and learn something from it. The goal is not to ascribe intent to a nonhuman character in an inappropriate sense, but rather, to allow an audience member to find meaningful parallels between his own experience and that of the nonhuman character. For example, rather than saying, “the shark wanted to explore the ocean,” the narrator could say, “the shark needed to find food to survive.” The former might work for a children’s storybook, but in order to focus on empirical evidence, it is often best to avoid anthropomorphizing a nonhuman subject and instead use comparisons or analogies to make the subject accessible.

Every character needs an obstacle that stands in the way of her objective. Without an obstacle, the character does not change, and there is no story ( Vogler 2007 ; McKee 2010 ; Olson 2015 ). Fortunately for science storytellers, obstacles are part of science. Every scientific investigation confronts an obstacle, whether it is an unsolved problem or a logistical complication.

Obstacles can arise from other characters, from external forces, or from the self ( Campbell 1949 ; Vogler 2007 ; McKee 2010 ; Olson et al. 2013 ; Olson 2015 ). In most but not all stories, the protagonist must deal with an internal obstacle before she can overcome an external obstacle ( Vogler 2007 ; McKee 2010 ).

An obstacle only moves a story forward if it puts something at risk. What are the consequences if the protagonist fails to overcome that obstacle? The more the protagonist has to lose, the more compelling the story ( McKee 2010 ). The stakes should increase as the story unfolds ( Vogler 2007 ; Olson 2015 ). Stakes add weight to the protagonist’s actions and decisions, and get the audience invested in the story’s outcome.

This doesn’t mean that imminent disaster has to permeate every story. Stakes can be compelling even without a fatal threat. One failed experiment may not be a major setback in a scientist’s career, but what if he is working against a deadline? Against his own search for purpose? Several obstacles can even be in play at once.

Inciting incident

This is the event that catalyzes the story. Also known as the “Challenge,” “Call to Action,” or “Call to Adventure” ( Campbell 1949 ; Vogler 2007 ; Schimel 2012 ; Olson 2015 ), something must happen that changes the protagonist’s situation and presents a new opportunity or threat to her objective ( McKee 2010 ). From this point on, the protagonist is in unfamiliar territory—figuratively and/or literally—and the rest of the story is the protagonist’s journey to return to her realm of familiarity ( Fig. 2 ; see Campbell 1949 ; Vogler 2007 ; McKee 2010 ; Olson 2015 ).

Whether it is a story of a scientist on a quest for discovery, an organism on a “quest” for survival, or a natural system on a “quest” for equilibrium, an inciting incident signals to the audience that the story has begun. This both focuses their attention and promises a payoff at the end of the story ( Olson 2015 ). The rest of the story then unfolds through a series of actions taken by the protagonist, and the outcomes of those actions ( Campbell 1949 ; Vogler 2007 ; McKee 2010 ).

Broad theme

The broad theme of the story is something universal that goes beyond the specifics of the story. It is something that every audience member can understand. The broad theme might lie in the lessons the protagonist learns from his journey in the story. If the protagonist is nonhuman, the broad theme can emerge from the subtext of the story. The migrating shark itself may not have overcome an internal conflict, but what has the audience learned from following its journey? That we shouldn’t judge based on appearances? That we are all connected? Every audience member will extract his or her own meaning from the story, based on his or her own reactions and prior experiences. But if the storytelling is effective, the entire audience will arrive at a similar point.

As an applied example of these story elements, I now return to the story that I began in my prologue. Initially, I had thought that the “So What?” of my PaleoFest talk would be something like “science is a process of discovery.” But as I developed the story, I realized that the take-home message had to be deeper than that. Everyone in the audience at PaleoFest would already appreciate that science is about discovery. I needed a message that would be particularly relevant to the event, but also universal.

When I was a kid, I loved nature and animals. I wanted to save the planet from climate change. When I went to college, my interest in animals led to a summer job working in a fossil lab. I learned how to clean and prepare dinosaur bones, and I started studying the science of bringing them to life. It blew my mind! As I learned how to reconstruct past worlds using fossils, I realized that I was learning to address problems by thinking about changes over time and space. This also applied to climate change. I learned that climate change predictions today depend on accurate records of climate change in the past. We have a continuous record of past temperatures (paleotemperatures) in the ocean, but not on land. This is because fossil records on land are patchy and often have large gaps. Consequently, our record of paleotemperatures on land is incomplete. We need more sources of data to construct a more complete record of terrestrial paleotemperatures. I found that other studies had reconstructed past temperatures for a specific location and time based on the body size of a single squamate (snake or lizard; Head et al. 2009 , 2013 , respectively). What if we could do that for longer geologic time periods using fossil squamates? I searched for a suitable study group and came across Glyptosaurinae (Squamata: Anguidae), a group of lizards that was abundant in the Western Interior of North America through the Paleogene (66–23 million years ago). I decided to investigate whether I could use the fossil record of these lizards to reconstruct temperatures through the Paleogene. I would use maximum glyptosaurine body length in a mass-specific metabolic equation to estimate the minimum mean annual paleotemperature necessary to sustain that body size ( ElShafie 2014 ; ElShafie and Head, in review). There was only one problem: the known glyptosaurine record did not include any complete fossils. How was I going to measure body length without whole skeletons? Fortunately, I found that the anatomical proportions of fossil glyptosaurines are consistent with their living relatives. I was therefore able to build a regression model from measurements of living lizards and estimate glyptosaurine body length based on head length. I generated a paleotemperature curve for the Western Interior of North America through the Paleogene based on glyptosaurine body length. To my surprise, I found that the lizard-based temperatures were very consistent with other fossil proxies! These results suggest that fossil squamates can indeed be a useful proxy for reconstructing past temperatures over time and space. I was inspired by the results of this study to keep investigating past climate change events through the vertebrate fossil record. For my PhD, I am continuing to study the reptile fossil record of North America through the Paleogene, now with a focus on how climate change affects reptile communities over time and space. Paleontology trains you to think about how things are connected to a larger system, and how that system changes over time—a very useful skill. Whether you want to be a paleontologist, a farmer, a doctor, or just an informed citizen, studying paleontology can help prepare you for life!

The talk was a hit at PaleoFest. Kids, students, parents, and colleagues thanked me for an engaging story. Most important to me, however, was the reaction of my relatives, some of whom had come to hear my talk. They clearly understood, for the first time in my eight years of fossil research, why I chose this field. And, to be honest, so did I.

This story demonstrates two types of science stories: (1) stories about scientists as people, as in the personal account that bookends the story; and (2) stories about how science is conducted, as in the account from the PaleoFest talk nested within the personal story. Both of these stories have a dramatic arc, but the focus differs. See Fig. 3 for an example of a dramatic arc for a science story, as in the PaleoFest talk (see also Green et al. [2018] for variations on a dramatic arc that can apply to science stories). Note that while the broad theme of the PaleoFest talk was “Thinking about questions in time and space can help you solve problems,” the broad theme of the personal story would be something like “Connecting with others connects you with yourself.”

An example of a dramatic arc for a story about a scientific study. The story in the “PaleoFest” talk follows this progression. Note that in this figure, the “pyramid” of rising action and falling action seen in Fig. 1 has been broken into multiple peaks of increasing tension. A protagonist might take multiple actions and face multiple obstacles in the course of a story. Based on Freytag (1900) .

Will other scientists not take me seriously if I use storytelling to engage broad audiences?

I have heard this concern many times due to a phenomenon known as “The Sagan Effect.” This refers to the widely held belief that renowned science storyteller Carl Sagan was denied membership in the National Academy of Sciences because of his focus on popularizing science ( Martinez-Conde 2016 ; but see Loverd et al. [2018] in this volume for evidence of changing views on this matter at NAS). Unfortunately, that sort of attitude still exists in academia. Too often, I hear colleagues complain that they were undermined for explaining science in an accessible way to a museum-goer, or criticized for spending any time at all on public outreach.

Many people would argue today that science communication is a critical skill for any scientist (e.g., Lubchenco 1998 ; Dean 2009 ; Baron 2010 ; Schimel 2012 ; Luna 2013 ; Olson et al. 2013 ; Olson 2015 ; Illingworth 2017 ; Mazurkewich 2018 ) and that efforts to engage the public with science are well worth the time (e.g., Olson 2009 ; Kuehne et al. 2014 ; Alda 2017 ; Rather 2017 ; Green et al. 2018 ). The National Science Foundation requires a substantial statement of “Broader Impacts” on every major grant proposal ( National Science Foundation 2002 ). The National Academy of Sciences itself now holds a regular colloquium on “The Science of Science Communication” and has published several volumes of research on the subject ( Fischhoff et al. 2013 , 2014 ; National Academy of Sciences 2014 , 2017a , 2017b , 2018 ). Some studies have even found that scientists who engage in public outreach are equally if not more academically productive than average ( Jensen et al. 2008 ; Russo 2010 ).

If I force empirical evidence into a story formula, won’t the story be biased?

If the outcome of a story is decided first, and evidence is then selected to support that outcome, then yes, that is a biased account ( Schimel 2012 ). But in science communication, the goal is to identify story elements that are already present in a study, and to use those elements to distill an accurate and compelling story of a study without introducing bias or fabrication. Story models such as “The Hero’s Journey” ( Fig. 2 ) offer a form, not a formula ( Vogler 2007 ; McKee 2010 ). Such models are useful for understanding aspects of stories that are universally recognizable to general audiences.

A scientific study is never communicated exactly the way it happened. The IMRAD template often used to write manuscripts takes things out of context ( Padian 2018 ). Scientists never have enough time or space to include all the details when presenting their work. They must select the most salient information, which will depend on the audience, the platform, and the main points they want to emphasize ( Avraamidou and Osborne 2009 ; Dean 2009 ; Nisbet and Scheufele 2009 ; Olson 2009 , 2015 ; Baron 2010 ; Schimel 2012 ; Fischhoff et al. 2013 , 2014 ; Olson et al. 2013 ; National Academy of Sciences 2018 ).

How can I deal with existing stories about science that conflict with the one I want to share?

Any audience will likely have some preconceptions about a topic from existing stories, especially if the topic is politically charged or ethically sensitive. For example, someone planning to tell a story that reveals the potential benefits of CRISPR Cas-9 gene editing technology (see Doudna and Charpentier 2014 ; Sternberg et al. 2014 ; Doudna and Sternberg 2017 ) should familiarize themselves with the plots of films depicting genetically enhanced humans (e.g., Blade Runner , Scott 1982 ) and animals (e.g., Rampage , Peyton 2018 ), as well as the anti-GMO narrative that the organic food industry uses in its marketing ( Clancy and Clancy 2016 ). Such narratives can be an opportunity to launch constructive and balanced discussions. In order to engage people with science, it is important to be candid about what science is, in its virtues and its limitations.

What if the experiment didn’t work, or the results are inconclusive? How is that a story?

It is okay if the protagonist does not overcome the obstacle by the end of the story. This may seem unsatisfying to the storyteller, but it can make the story more gripping for the audience. They will empathize even more with a protagonist who does not get exactly what she wants. In such a case, the revelation might be that the real goal of the protagonist was something she did not see before ( McKee 2010 ). For example, Jennifer Hofmeister studied movement and abundance patterns in the California Two Spot Octopus for her dissertation research ( Hofmeister 2015 ). After years of dedicated fieldwork and analyses, Hofmeister’s results were inconclusive. She found that it was not possible to explain patterns of abundance in this species through her study. However, her results revealed that the question was more complex than previously assessed: the octopus was highly mobile, which contradicted earlier studies. Hofmeister was inspired to continue her research on octopuses, and her hard work led to a job as an environmental scientist.

Stories are not just about solving problems: they are about discovery. In scientific pursuits, even null or negative results reveal something. A story does not necessarily have to end with a solution. It might end with a piece of the solution and more questions than answers. That’s how science works. Insights can be gained from the journey. Whether the problem is solved or not, those revelations are what allow the audience to find meaning in the story.

Storytelling is an iterative process. When developing a science story, it can be helpful to share a draft with people who represent the target audience and ask them what they got out of the story. Were the protagonist, obstacle, and stakes clear to them? What was the broad theme? The test audience might pick up on an emerging theme not yet considered.

Developing storytelling skills is a lifelong pursuit ( Vogler 2007 ; Olson 2015 ). The good news is that it does not take long to learn the basics of story development. Using those basics in science communication makes a huge difference. Reading the papers in this volume is an excellent start. The references in this paper, as well as those listed in the other articles in this volume, offer further reading. For a helpful and entertaining overview of storytelling basics, “Pixar in a Box, Season 3: The Art of Storytelling” ( Pixar Animation Studios (2017) is an open-access resource developed by Pixar with Khan Academy. Storytelling is not just a skillset; it’s a mindset that one can use and develop throughout a career.

I especially wish to thank K. Padian for his mentorship and guidance in this research. For helpful discussions, I thank L. White, J. Bean, C. Marshall, P. Holroyd, S. Sumida, R. Olson, J. Lovell, D. McCoy, A. Madison, J.-P. Vine, G. Dykstra, T. DeRose, E. Klaidman, K.C. Roeyer, M. Nolte, S. Pilcher, S. Christen, D. Campbell, R. Sullivan, P. Lin, A. Rutland, M. Coleman, C. Good, W. Trezevant, R. Dutra, K. Johnson, H. Sues, S. Sampson, C. Liu, F. Mundi, H. Kerby, R. Stockley, R. Holmes, E. Neeley, S. Ul-Hasan, and J. Hofmeister. Thank you to the UC Museum of Paleontology (UCMP) community for constructive feedback on this work. Special thanks to J. Schimel, J. Weddle, and three anonymous reviewers for their thoughtful and thorough comments on this manuscript. I thank the Society for Integrative and Comparative Biology for the opportunity to organize this symposium and publish this manuscript; my co-organizers, S. Sumida and B. Lutton; and all of my fellow symposium presenters for being part of this initiative.

I thank the Sakana Foundation, the Uplands Foundation, and the UCMP for supporting this work. I also thank Science Sandbox, an initiative of the Simons Foundation; the Society for Integrative and Comparative Biology (SICB); the Walt Disney Family Museum; Science World at TELUS World of Science; Coalition for the Public Understanding of Science; Spacetime Labs; and an anonymous donor for sponsoring the “Science Through Narrative” symposium at the 2018 SICB Meeting, which provided the opportunity to present this work and publish this paper.

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Narrative stories as mediators for serial learning

1969, Psychonomic Science

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Annual Review of Psychology

Volume 59, 2008, review article, the evolution of a cognitive psychologist: a journey from simple behaviors to complex mental acts.

• Gordon H. Bower 1
• View Affiliations Hide Affiliations Affiliations: Department of Psychology, Stanford University, Stanford, California 94305; email: [email protected]
• Vol. 59:1-27 (Volume publication date January 2008) https://doi.org/10.1146/annurev.psych.59.103006.093722
• © Annual Reviews

The author summarizes his evolving interests from conditioning studies within a behaviorist orientation, thence to human memory, knowledge representation, and narrative understanding and memory. Arguing that the study of skilled reading provides a microcosm for revealing cognitive processes, he illustrates this by reviewing his research on the use of spatial priming to investigate readers’ on-line updating of their situational models of texts. Conceptual entities close to the reader's focus of attention within the model are readily retrieved. Retrieval speed from memory declines with the probed object's distance from the current focus and decays with time elapsed in the narrative since the item was last in focus. The focus effect varies with the character's perspective, his status in the story, his active goals, and other factors. The results are accommodated within an associative network model distinguishing just-read sentences in short-term memory from activated portions of long-term memory structures to which they refer.

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The aim of the investigation was to repeat the experiment carried out by Bower and Springston in 1970. A laboratory experiment was carried out to demonstrate how chunking could be used to increase the capacity of STM.

The aim of the investigation was to repeat the experiment carried out by Bower and Springston in 1970. A laboratory experiment was carried out to demonstrate how chunking could be used to increase the capacity of STM. Participants were presented with a letter sequence. The independent variable was the chunking and the dependent variable was how many letters the participants recalled. A repeated measures design was used and the participants were an opportunist sample of 20 students, between the ages of 16-18 years. The results were analysed using the Wilcoxon test.

Therefore the directional hypothesis that the participants remembered more of the acronyms than the non-related trigrams is significant. The graphs and the results extended this by showing that more acronyms were remembered than the non-related.

Introduction

Memory is the process of storing information and experiences for possible retrieval at

some point in the future. This ability to create and retrieve memories is fundamental to

all aspects of cognition and in a broader sense it is essential to our ability to function

properly as human beings. Our memories allow us to store information about the world

so that we can understand and deal with future situations on the basis of past

experience. The process of thinking and problem solving relies heavily on the use of

previous experience and memory also makes it possible for us to acquire language and

to communicate with others. Memory also plays a basic part in the process of

perception, since we can only make sense of our perceptual input by referring to our

store of previous experiences. Even our social interactions with others are dependent

upon what we remember. In a sense it can be said that our identity relies on an intact memory, and the ability to remember who we are and the things that we have done. Almost everything we do depends on our ability to remember the past.

Definitions of ‘Short term Memory’ vary between researchers. Typically this means memory for what has happened in about the last 20 seconds or less. Short term memory has a fairly small capacity. The figure normally quoted is that if we are given a list of words or numbers, then most people can remember somewhere between five and nine items. Miller (1956) coined the phrase the magical number seven plus or minus two to denote what people typically remember. There are ways of increasing how much can be remembered and Miller argued the ‘each item a person could remember consisted of a chunk of information. For example, consider the list ‘2014266977’. If one were attempting to remember this list simply as a set of individual numbers, then it would probably be beyond one’s memory span. However, suppose one recognised the numbers not as ten separate items to be remembered, but as two separate items (20142 was one such number and 66977 the other). This is an example of forming chunks – grouping items to be remembered into a smaller set of bigger items, which one finds easy to remember. This capacity for remembering can be taken to impressive lengths.

Ericsson et al. (1980) were interested in magic number 7 and worked with a participant (along distance runner), who had a normal memory span and average intelligence for an undergraduate. For 20 months he spend three to five hours a week on memory span tasks involving digits. By devising a strategy of recoding these in

  to running times, he could store lists of 12 digits as chunks of four digits each (for example, 3:49.2’near world record mile time’). He supplemented this with ages (89.3’very old man’) and dates (1944 ‘near the end of World WarII’). Using this system his memory span increased from seven to 28 digits. Then he organised the chunks into a hierarchy of ‘groups’ and ‘super groups’, until eventually he could retrieve an average of almost 80 digits. However, when tested on consonants his memory span reverted to about six items. It seems he was unable to increase his Short term Memory capacity through practice; his increase in digit span was due to the mnemonic associations. Thus, by chunking, the amount, which can be held in memory, can be increased.

Chaining material to be learned into narrative stories can also help remembering. Bower and Clark (1969) asked participants to make stories from lists of ten unrelated nouns. Subsequently, 93% showed correct recall, compared to only 13% for control participants who were asked to create stories but who had spent the time studying the lists. Another study by Bower and Springston, to demonstrate how chunking could be used to increase the capacity of Short term Memory. Participants were presented with a letter sequence. Letters were presented in a way that formed a well-known group (eg, fbi, PhD, IBM), and then the letters were presented in a way that did not form a well-known group (eg fb, iph, mr). Participants were then asked to recall as many of these letters as they could. Participants who were presented letters with a well-known group recalled more than the other letters that did not form a well-known group. It is this experiment by Bower and Springston which is most relevant to this study as the study hopes to investigate whether Chunking could be used to increase the capacity of Short term Memory.

This research aims to repeat the experiment by Bower and Springston. It aims to see whether participants recall more of the acronyms than the non-related trigrams. It also aims to see if Miller’s finding’s that the participants could only recall upto seven plus or minus two items.

Directional Hypothesis

There will be significantly more participants will remember more of the acronyms than the non-related trigrams., null hypothesis.

Any differences in the observed outcome if the participants recall more of the acronyms than the non-related trigrams will be due to chance alone.

To test the experimental hypothesis the following was carried out.

A lab experiment was carried out. This therefore allowed the highest possible level of control over variables. The independent variable is the capacity of memory and the dependent variable is the number of words correctly recalled. A repeated measures design was used as the same participants are used in both the conditions.

Participants

The participants were 20 students of both sexes who were between 16-18 years old. The experiment was conducted in the college and any student present in that area took part in the experiment- therefore an opportunity sample was used. The experimenter was a 17-year-old girl from A-level psychology class.

Participants were provided with A4 sheets of paper and a pen to write with. A stopwatch was also used so as to time how long it took for each participant to recall the trigrams. The experimenter also had a list of 15 acronyms and 15 non-related trigrams. Stimulus materials were randomly chosen; the experimenter also had a sheet with standardised instructions.

The experiment took place in the college. It was an opportunist sample, so selecting anyone who is available to take part in the experiment. Standardised instructions were followed like asking the participants if they would like to take part in a small experiment. At first the participants were presented with the acronyms, they were given time to recall and they were asked to write it down within 15 seconds. Later, they were provided with non-related trigrams and the above procedure was repeated again. Debriefing took place after the experiment was finished. A repeated measures design was used in both the experimental conditions.

Different participants have different states of mind or mood when participating in the experiment. Making the experiment as active and interesting as possible can control this. Timing could also be an extraneous variable as the participants may be better/worse at recalling at particular time. To avoid this stopwatch could be used so that the participants have equal amount of time when recalling letters.

Summary table of Acronyms and non-related trigrams

                         Acronyms                                  Non-related trigrams

Total                     172                                        78

 Mean                                 8.6                                           3.9

Standard deviation        3.08                                                            2.29

The summary table shows that participants recall more chunked letters than the non-chunked. The total, mean and the standard deviation agree with this. The mean for acronyms is much higher than the non-related trigrams.

Results Collected

Treatment of Results

Ordinal level of data was used, as the results are capable of being placed into rank order i.e., from lowest value to highest value or vice-versa. The scores can also be meaningfully compared. This experiment was a repeated measures design.

The Wilcoxon test was used.

        Observed value = 14.5

        Critical value at p 0.05 = 60

The experimental hypothesis was directional. The level of significance was set at 0.05. Therefore, as the observed value 14.5 is smaller than the critical value 60, so the results occurring through chance is less than 5%.  So the null hypothesis can be rejected.

This shows that the participants recall more of the acronyms than the non-related trigrams.  

Explanation of findings

The observed value 14.5 is less than the critical value at p 0.05- 60. This therefore meant that the results occurring through chance is less than 5%. Therefore the result is significant and the directional hypothesis was accepted. This means that more people remembered acronyms than the non-related trigrams. The summary table and the graphs extend the hypothesis by clearly showing that more participants remembered acronyms than the non-related. It therefore supports the hypothesis that chunking increases the capacity of Short term memory.

Relationship to background research

These results show that more people remember acronyms than non-related trigrams. In Bower and Springston’s experiment, they demonstrated that chunking increases the capacity of Short term Memory. This experiment also supports the study done by Bower and Clark in which the participants were asked to make stories from lists of ten unrelated nouns. 93% showed correct recall, compared to only 13% for control participants who were asked to create stories, but who had spent the time studying the lists. In another study by Ericsson who worked with a participant who had a normal memory span, spend three to five hours a week on memory span tasks involving digits. By devising a strategy of recoding these into running times, he could store 12 digits as chunks of four digits each. Using this system his memory span increased from seven to 28 digits. Then he organised the chunks into a hierarchy of ‘groups’ and ‘supergroups’, until eventually retrieve an average of almost 80 digits. However when tested on consonants his memory span reverted to about six items. His increase in digit span was due to the mnemonic associations. Even though it is due to the mnemonic association the study contradicts Miller, which suggests that most people recall only up to seven plus or minus two items.  

Limitations of the research and modifications made if repeated

This experiment was a laboratory experiment and it was carried out so that the researcher can have complete control over variables. It can be used to test theories, determine the conditions under which certain events occur or extend current research by proposing new research problems. There may be drawbacks of experimental designs; these include the potential for order effects resulting from the order of presentation of the experimental conditions or alternatively the effects of individual differences between participants. In capacity studies it is difficult to exclude the influence of Long term Memory. Capacity seems to be influenced by for example if the participants read the letters aloud recall is better.  

        A repeated measures design was used as it involves using the same participant in each of the experimental conditions. So order effects can confound experimental results in two ways, either negatively through the effects of fatigue or boredom or positively through the effects of learning or practice. There are ways in which the potential risk of order effects in a repeated measures design can be minimized. These are known as counterbalancing or randomisation.  

        If the experiment were to be repeated again, counterbalancing should be employed, it involves equal numbers of participants undertaking the tasks required of them in different orders. Randomisation can also be used; it involves adopting a random strategy for deciding the order of presentation of experimental conditions for example by drawing lots or tossing a coin. This experiment could be repeated as a natural experiment. Researcher can observe the participants in the real life and look at how they are remembering items which mean something to them than which is not. So it removes the drawback that it is not ecologically valid. This also removes the difficulty from generalising the results as in a natural experiment practically all ages are present.  

        A serious problem with experiments is that by establishing high levels of control and narrowly defining independent and dependent variable, an experimental condition may become artificial and recognizably different from real life situations. Demand characteristics also occur when participants try to make sense of the situation they find themselves in and act accordingly. These may seriously threaten the validity of an experiment. A further possible problem concerns the level of public knowledge (or the lack of it) about psychology- how an individual perceives psychology may affect their responses in the research setting. In this experiment the participants are mostly A-level students. This raises the question of the extent to which it is reasonable to generalize the results of such experimental studies to other groups of groups of people.

Implications of the research and future research that can be carried out

The results from this study show that more participants recall more acronyms than non-related trigrams. In Bower and Springston experiment, the findings were the same; participants remember more of the acronyms than the non-related trigrams.  These results have implications particularly the students. According to Bower and Springston participant recall more acronyms, but is it necessary to answer an exam essay question being as simple as running through the mnemonic in our mind? In this experiment participants recalled the trigrams better from the beginning and the end of the list than from the middle of the list. So this area could be explored in more detail.

The experimental hypothesis, that more participants recall more acronyms than the non-related trigrams has been accepted. So chunking increases the capacity of Short term Memory.

Ericsson, E.H (1980) Identity and the Life cycle, International University Press, New York.

Miller, G.A (1956) ‘the magical number seven, plus or minus two; Some Limits on our Capacity for Processing Information’, Psychological Review, 63, pp 81-97.

Bower, G and Winzenz, D. (1969) ‘Groups structure, coding and memory for digit series’, Journal of Experimental Psychology, Monograph 80 pp.1-17.

Rumelhart, D.E and Norman, D.A.(1983) ‘Representation in memory’, in R.C. Atkinson, R.J. Herrnstein, G. Lindsey and R>D. Luce(eds.) Handbook of Experimental Psychology, Chichester: Wiley.

Baddeley, A. (1992) Is memory all talk? The Psychologist, 5, 10(October).

Acronyms and the non-related trigrams, which was used in the recall

Acronyms        Non-related

RAC                                TPT

IBM                                        ACM

FBI                                          SOT

MIB                                         LMO

HIV                                         PLI

USA                                       QZE

UFO                                       ATX

LCD                               MVM

STM                                       ICL

PHD                                 SUA

AQA                                 PSN

VAT                                 CPG

MOT        GNB

TCP                                          LON

AOL                                         RPU              

To calculate the mean

        = 8.6

Non-related trigrams

  =  3.9

Add up the ranks corresponding to the +ve sign

3.5+3.5+7.5+10+10+12.5+14+14+16+16+16+16+16+17+19+19+21

Add up the ranks corresponding to the –ve sign

        3.5+3.5+7.5

               =14.5

The smallest of the rank is the observed value T = 14.5

 The critical value at p 0.05 is 60

Therefore the observed value is smaller than the critical value, so the results occurring through chance is less than 5%, so the null hypothesis can be rejected

To calculate standard deviation

   =

   =  3.08

=  2.29

        -                

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• Published: 21 November 2012

In Retrospect: The Origin of Life

• Tony Hyman 1 &
• Cliff Brangwynne 2  

Nature volume  491 ,  pages 524–525 ( 2012 ) Cite this article

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Clifford P. Brangwynne and Anthony A. Hyman celebrate the first book to plausibly suggest how life began.

The Origin of Life

• A. I. Oparin

“No religious or philosophical system, no outstanding thinker ever failed to give this question serious consideration.” So wrote Aleksandr Oparin more than 75 years ago, about the quintessential conundrum of how life self-assembled from inanimate components. The Soviet biochemist's answer is his book The Origin of Life (1936). Roughly based on a pamphlet he published in 1924, this book is an enormous contribution to our understanding of life's improbable beginnings. In it, Oparin argues that conditions on early Earth nurtured the synthesis of amino acids and their assembly into protocells.

Although he trained as a biochemist, Oparin studied the chemical make-up of Earth's crust, as well as other planets in the Solar System and the Sun. He realized that Earth's early atmosphere was a strongly reducing environment, rich in methane, water and ammonia. He posited that, with time and a supply of energy such as lightning or geothermal activity, these simple components would form the complex building blocks of life. And after an English translation was published in 1938, Oparin's ideas became well known in the West.

Nearly 20 years after the book's publication — and 60 years ago this year — Stanley Miller and Harold Urey tested Oparin's hypothesis in a lab at the University of Chicago in Illinois. They sent a continuous electric current through a glass vial containing water, hydrogen, methane and ammonia. Within a week, a substantial amount of the carbon had been converted into complex macromolecules, including many amino acids. This 'Miller–Urey' experiment confirmed the significance of Oparin's ideas, and Miller duly referenced The Origin of Life .

Oparin's work thus played a seminal part in the formulation of our modern ideas of life's conception. His ideas on the organization of cells and first stirrings of life continued to attract an important audience. In 1957, a large international meeting (attended by Miller) was held in Moscow to discuss the origin of life, the proceedings of which make it clear that Oparin's book had had a profound influence. And yet, despite his towering achievement, Oparin is today largely forgotten by the broader science community, particularly in the United States. Why?

Social struggle

There are two reasons. The first is that after the Second World War, biology in the West moved away from thinking of the cell in physicochemical terms, towards a reductionist molecular-biology approach, with a DNA-centric viewpoint.

The second lies in the cold-war collision between science and politics. Oparin graduated from Moscow State University in 1917, the year of Russia's October Revolution, and his ideas were forged within that radical context. He explains, for instance, that the question of life's origin “was always the focal point of a sharp philosophical struggle which reflected the underlying struggle of social classes”. As a prominent Soviet scientist with the full backing of the state, Oparin's thinking was rooted and framed in the Marxist philosophy that the origin of life is “merely one step in the course of its historical development”.

Not surprisingly, cold-war divisions led many US scientists to dismiss Oparin. The Nobel laureate Hermann Muller, who thought that life originated as a gene, criticized the poor status of DNA within Oparin's picture of early life. (Oparin apparently stated: “DNA is the end product of metabolism and the nucleus is the dustbin of the cell.”) The proceedings of the 1957 conference point to a growing split between US and Soviet perspectives. With less scientific interchange, the ideas in The Origin of Life became marginalized in the West.

After Stalin's death in 1953 — the year the Miller–Urey experiment was published — Oparin faced criticism within the Soviet Union. He was later forced to resign from the secretaryship of the academy of science because he, along with the rest of the country's scientific establishment, had supported the discredited agricultural pseudoscientist Trofim Lysenko. Oparin was later forgiven and, in 1979, shortly before his death, received the Lomonosov Gold Medal from the Soviet science academy for outstanding achievement in the natural sciences. His book retained a small but dedicated following.

Today, the primary legacy of The Origin of Life is the Miller–Urey experiment, but the synthesis of amino acids took up just part of the book. Oparin went on to describe a mechanism by which macromolecules would self-assemble into large liquid-like structures that he called “complex coacervates” — what today might be called colloidal assemblies. He suggested that these protocells were a key step in the origin of life. However, given the uncertainty at that time about the nature of biological macromolecules, it was unclear exactly how these colloids might form.

This hypothesis of colloidal assembly has largely been displaced by other concepts of life's origins. For example, some hold that membranes must have come first, arguing that the prebiotic soup contained molecules with water-attracting and water-repelling ends capable of self-assembling into cell-like structures (liposomes). Interestingly, later in life, Oparin himself expressed regret at having focused on colloids instead of liposomes.

However, current cell and molecular biology provides a new perspective on the feasibility of life beginning from liquid-like macromolecular assemblies, suggesting that Oparin might have been more correct than he thought. Many macromolecules have weak multivalent interactions with other macromolecules, which means they have several sites at which interaction can occur. RNA itself is a flexible, extended, dynamic molecular chain; the interactions between it and other molecules are typically numerous and weak. These properties are sufficient for macromolecules to self-assemble into liquid-phase droplets, like Oparin's coacervates. Recent work on RNA compartmentalization and catalysis in liquid droplets provides additional support for Oparin's concept of primitive protocells in a primordial 'RNA world'.

Oparin belongs in the pantheon of the twentieth century's greatest scientists for providing a foundation for understanding early molecular evolution. He believed that natural selection had “completely wiped off the face of the Earth all the intermediate forms of organization of primary colloidal systems and of the simplest living things”. Three-quarters of a century before Oparin, Charles Darwin noted that such primitive life forms would be a poor match for contemporary, highly evolved ones. But Darwin also wrote that relatively less-evolved species — “anomalous forms ... living fossils” — often come down through the ages, against all the odds.

Like the ancient mitochondrial organisms found in each of our cells, intracellular RNA droplets could reflect a still more ancient lineage in the assembly of complex cellular structure. Oparin's coacervates may still be alive and well, safe within our cells, like flies in life's evolving amber.

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Is It Possible to Measure Science? V. V. Nalimov's Research in Scientometrics

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This article is devoted to the scientometric research of Professor V.V. Nalimov (1910–1997) of Moscow State University. His first scientometric article was published in 1959: mathematical models of world science growth were examined and logical grounds for the applicability of these models were also given. In his further works, V.V. Nalimov continued to stress the importance of quantitative studies of science development. In 1969, the monograph on scientometrics by V. V. Nalimov and his co-author Z. M. Mulchenko was published. This book reflected his earlier publications on scientometrics and the solutions of new tasks. In 1970, Nalimov published articles on the comparison of science and the biosphere, the geographic distribution of scientific information, and changes in the demand of scientific staff. In later articles in philosophy of science, he stressed the necessity of a combination of the scientometric approach with works on the logic of science development. One of the latest works by Nalimov was an analysis of articles published by The Journal of Transpersonal Psychology : Here the scientometric approach was used to study the origin and development of a new scientific branch.

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YU. V. Granovsky , Is it possible to measure science? Nalimov's research in scientometrics, Naukovedenie (Science of Science), (2000) 1:160–183.

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Granovsky, Y.V. Is It Possible to Measure Science? V. V. Nalimov's Research in Scientometrics. Scientometrics 52 , 127–150 (2001). https://doi.org/10.1023/A:1017991017982

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Issue Date : October 2001

DOI : https://doi.org/10.1023/A:1017991017982

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