New article: Sport, physical activity and educational achievement

I’ve recently published an article in the academic journal Sport in Society on the question of the contribution sport and other forms of physical activities might make to school grades and examinations.

This is the abstract / summary:

Sport and other forms of physical activities have traditionally held an ambiguous place within schooling, often being pushed to the margins. At the same time, there is a consensus that such activities are necessary for the healthy development of young people. This was proven during the second half of the last century, representing a revolution in the understanding of health. Recent developments in neurology, psychology and related sciences hint at a second revolution in which a strict distinction between mind and body has physical activity can make distinctive contributions to educational achievement, and a host of wider benefits. Focusing on cognitive functioning, psychosocial development, school engagement and general educational attainment, the article reviews the available evidence and concludes that there is sufficient reason to believe that sports and physical activity can make useful contributions to educational achievement.

The article can be accessed here. Unfortunately, it is currently protected by a pay-wall. However, I will put a pre-publication version on ResearchGate and, which will be freely available.

Comments would be very welcome.

Ads would appear here

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The Philosophy of Science and Sport and Exercise Science


“Cheshire Puss,’ she began, rather timidly, as she did not at all know whether it would like the name: however, it only grinned a little wider. ‘Come, it’s pleased so far,’ thought Alice, and she went on. ‘Would you tell me, please, which way I ought to go from here?’“That depends a good deal on where you want to get to,’ said the Cat. “I don’t much care where—’ said Alice.“Then it doesn’t matter which way you go,’ said the Cat.“—so long as I get SOMEWHERE,’ Alice added as an explanation.“Oh, you’re sure to do that,’ said the Cat, ‘if you only walk long enough.”(Lewis Carroll, Alice’s Adventures in Wonderland & Through the Looking-Glass, 1902)

The Philosophy of Science is simply philosophy directed towards questions of science. These questions generally take two forms. First, there are those related to the nature of science in general, and about central concepts in science, such as the nature of theories, truth, objectivity, and so on. The most fundamental question of this sort is whether or not there really is a special scientific method, and if so, what is it? Second, other questions focus on specific sciences. The philosophy of biology, for example, examines evolution, genetics and development, whilst the philosophy of physics is concerned with possible interpretations of relativity, quantum mechanics and string theory. The Sport and Exercise Sciences could be described as second-order fields, since they rely and build on the concepts of more fundamental disciplines like physiology, mathematics and psychology, and seek to apply them in sporting contexts. It is difficult to imagine what a distinct and coherent “philosophy of the sports and exercise sciences” might look like, but philosophical issues are inseparable from serious study and practice in the sport and exercise sciences.

This essay aims to offer an introduction to the Philosophy of Science, and discusses some of the ways in which an understanding of its debates and disputes might be relevant for researchers and practitioners in the sport and exercise sciences. The language of this field is a matter of some debate itself. In some countries, it is conventional to talk of either sport science or sport and exercise science, while elsewhere people use Kinesiology, Bio-kinetics, Human Movement Studies, and other names. Different titles sometimes reflect local traditions, and sometimes they indicate am attempt to delineate the content of the field of study. Discussion of the most suitable terminology for these areas of study is a fascinating and worthwhile philosophical activity in its own right, but I will not be doing this here.

Does it matter if the sport and exercise sciences are scientific?

“When I use a word, it means just what I choose it to mean—neither more nor less.” (Humpty Dumpty, in Lewis Carroll, Alice’s Adventures in Wonderland & Through the Looking-Glass, 1902)

A great deal of the literature that makes up the Philosophy of Science addresses the meanings of central terms and concepts. The most fundamental of these is of course science, and this will be the focus of this short article. But it is possible to argue, as did Humpty Dumpty that we can choose our own meanings of the words we use, and we are sometimes free to do so. Poets regularly play with words and their meanings, as do small children, and this seems perfectly acceptable. When John Lennon of The Beatles wrote, ‘I am the Walrus’, it would be a peculiarly literal critic who condemned him as a liar: ‘I have seen pictures of Mr Lennon, and can confirm that is not, in fact, a walrus!’

Matters change when we make claims whilst trying to communicate with or claim to express truth to other people. In contexts like these, words and their meanings can matter a great deal. They can hide as well as show truth. This is not just an academic point. Adoption of the language of science is frequently used to present a set of ideas as possessing scientific value and credibility, and to adopt the intellectual authority that implies. Presumably this explains the emergence of Library Science, Leisure Science, Management Science, and so on. It might also explain why even the world of alternative medicine goes to great lengths to claim its scientific credentials.

The Australian comedian and poet Tim Minchin, in his ‘beat poem’ Storm, was unpersuaded by strategies

“By definition”, I begin

Alternative Medicine”,

I continue

Has either not been proved to work,

Or been proved not to work.

Do you know what they call “alternative medicine”

That’s been proved to work?


The demarcation problems

“If you set to work to believe everything, you will tire out the believing-muscles of your mind, and then you’ll be so weak you won’t be able to believe the simplest true things.” (Lewis Carroll, Letter to to Mary MacDonald, 1864)

The quickest way to get a sense of some of the most basic questions examined by philosophers of science is to consider the difference between science and non-science. This is called the problem of demarcation (or the problem of setting the boundaries or limits of science).

The question of what is or is not scientific knowledge is as old as science itself, and remains the subject of on-going debate among philosophers and scientists. One difficulty confronting anyone reflecting on issues is that there are many different types of science (such as theoretical and applied), concerned with many different sorts of objects (including people, animals, plants and minerals), at different stages of disciplinary maturity (from emerging areas of research to well-established sciences). Consider, for example, some of the types of research reported in recent Sport and Exercise Sciences journals:

  • Randomised Control Trials of the effectiveness of physical activity interventions;
  • Surveillance reports of sports participation around the world;
  • Analysis of specific groups’ motivations to engage in exercise;
  • Systematic Literature Reviews and Meta-analyses of various, narrowly defined topics;
  • Observational studies of sports coaches’ behaviours;
  • Laboratory studies of oxygen uptake on a treadmill;
  • Brain scans of skilled practice.

    Research methods used in any multi-disciplinary field are likely to be diverse, since the methods of each of the parent disciplines can potentially be used, and this variety will only be multiplied when that field encompasses both theoretical and applied work, and populations ranging from shortly after birth to death. In fact, the range of methods used by sport and exercise scientists is even wider than that, since many methods regularly used have been imported from further afield. Systematic reviewing has origins in agricultural studies of seeds and fertilisers. Cluster analysis was first used by bacteriologists. And the detailed observational procedures used to track player behaviour during a game or session were imported from ethologists’ studies of animals in the wild (although that sometimes requires less of a leap of the imagination!).

    Although science has been defined in many ways, most people who have examined the subject agree it is ultimately not a body of knowledge, but a way of establishing and developing a body of knowledge (Shneider, 2009). There are many forms of inquiry that are not scientific, but are perfectly respectable. History, ethics and theology would not normally be considered branches of science, but they clearly have values and standards. Ways of differentiating science from these academic disciplines is sometimes a topic of the Philosophy of Science, but far more common is the distinction between science and what is usually called pseudoscience. Pseudoscientific theories claim to conform to the methodological norms of science, but, when judged by non-believers, the claims are deemed to violate science and often common sense (Koertge, 2013). In a recent article, I offered an alternative terminology theories and practices that look superficially like science, are presented as science, but do not follow the accepted standards of science: these theories are “ sciency” (Collins and Bailey, 2013).

    The philosopher most associated with the problem of demarcation is Karl Popper. Growing up in pre-World-War-1 Vienna, he was immersed in one of the most exciting intellectual environments there has ever been. As a young man, Popper attended public lectures and read books by many of the greatest thinkers of the day. He was impressed by the boldness of Albert Einstein’s new theory of relativity, and much less impressed by the psychoanalytical ideas of Sigmund Freud and Alfred Adler. The problem with Freud’s and Adler’s views, he thought, was that their power to explain psychological states and experiences was illusory, since it would be almost impossible to show them to be incorrect. Einstein, in contrast, explicitly stated the conditions that would kill his theory. Popper searched for some way of distinguishing between what he saw as the power of Einstein’s physics and the poverty of Freud and Adler, and concluded that the answer was falsification. A theory is scientific, he reasoned, if it can be shown to be false. This is in contrast to the idea that science operates through the generation of confirmations of theories, which had previously dominated discussions of the scientific method (and sometimes, in various forms, to this day).

    According to Popper, the relative power of positive (confirmations) and negative (falsifications) evidence is asymmetrical: no amount of confirmations can demonstrate a theory’s value because it is always easy to find them; but a single falsification, he claimed, can kill a theory dead.

    The most memorable metaphor Popper used to exemplify this point is ‘the black swan’. Europeans for thousands of years had observed millions of white swans. Relying on positive findings, we could come up with the theory that all swans are white. However exploration of Australasia introduced Europeans to black swans. Poppers’ point is this: no matter how many observations are made which support a theory, there is always the possibility that a single black swan can kill that theory.

    So, the scientist (or at least the good scientist) does not search for evidence that seems to support a theory, but looks for ways in which it might be found to be mistaken. In other words, genuinely scientific theories include statements that could be shown to be false by empirical evidence; pseudoscientific theories do not (Popper, 1934; Magee, 1973). And the spirit of falsification continues extends to the scientific community as a whole, where the “friendly- hostile co-operation” of scientists (Popper, 1994), is expressed through mechanisms like peer review of articles,

    Consider, as an example of the asymmetry between confirmation and falsification, the famous ‘four-minute mile’ that became an iconic goal for runners in the middle of the 20th century. For years, so many athletes had tried and failed to run a mile in less than four minutes that people suggested it was a physical and psychological impossibility. Scientists of the day even believed it was unachievable, as the human body was simply not able to maintain the necessary speed of 15 miles per hour (24.14 km/h, or 2:29.13 per kilometre, or 14.91 seconds per 100 metres). The theory gathered hundreds of confirmations until a 25- year-old medical student called Roger Bannister won a mile race in Oxford, UK, with a time of 3 minutes and 59.4 seconds.

    In Popper’s terms, no amount of confirming evidence proved or even supported the theory that the four- minute mile was impossible. But just one negative piece of evidence destroyed that theory.

    Falsification as the criterion of demarcation continues to be influential among scientists, but philosophers have generally abandoned it as a simple way of setting science apart from pseudoscience. There have been various criticisms of Popper’s view, but the most damaging is probably what is sometimes called the ‘Quine-Duhem Problem’. It is based on the observation that when a scientist tests a theory, it is not in isolation from other assumptions and hypotheses. So what appear to be observations that falsify a theory might really be some other factors.

    Imagine a hypothetical experiment. A sport psychologist has a theory that sports players use reasoning skills during their game play which resemble norms of correct reasoning. The method is to recreate game situations, and asking players to solve problems whose correct solution is determined by logic, probability or decision-making theory. Suppose none of the participants manage to solve the problems according the prescribed. According to a simple account of Popper’s view, there is cause for concluding the theory has been falsified, and it should be abandoned. But this would be premature, as all that can be concluded is that the cluster of theory, accompanying assumptions and practical aspects of the experiment failed. Where the failure lies is, in itself, impossible to identify. It might be that the norms of reasoning cannot be provided by logic, probability or decision-making theory, or that, even if they can, they have been incorrectly applied in this experiment. Alternatively, the failure might be due to performance errors, or to misapplication of the experiment. Or perhaps there are other factors about which the sport psychologist is not currently aware.

    In response to these sorts of criticisms, Popper modified his theory, arguing that scientists should be very clear and explicit about both the theory and any associated assumptions and hypotheses that might affect it. In some ways, this is a stronger position, since it means that the scientist is prepared to dictate more fully the theoretical and experimental conditions necessary for proper testing. However, it does not adequately deal with the Quine-Duhem Problem, since it will never be possible to completely deal with complicating variables. In addition, Popper’s revised version of his theory lacked the beautiful simplicity of distinguishing between science and non-science that was so appealing about the original (Lakatos, 1978).

    While philosophers have tended to reject Popper’s formal theory of falsifications, most would endorse its central tenets, such as the central importance of a critical approach, well-designed tests and a suspicion of an over-reliance on confirming evidence. However, some philosophers have offered radically different theories of sciences. The best-known alternative is probably that of Thomas Kuhn.

    In contradiction to the Popperian account of science as revolutionary, and characterised by ambitious attempts to create and destroy theories, Kuhn portrayed science as an essentially conservative practice, ruled by powerful paradigms and in which the context of research is vitally important. Popper recognised that many scientists do spend their days solving Kuhnian puzzles that work within the confines of the concepts and methods learned from textbooks. However, this apparent fact neither offers support for Kuhn’s position nor does it undermine the value of experimental testing, as ultimately, Popper and Kuhn were addressing quite different questions. Kuhn portrayed science as it is sometimes carried out, whereas Popper’s primary interest was in how science ought to be. Kuhn sought to describe how science worked; Popper prescribed how it should work.

    At the centre of Kuhn’s analysis of science was his conception of the paradigm, by which he meant a recognised scientific achievement that provides model problems and solutions to scientists. Paradigms guide ordinary scientific practice, which Kuhn labelled ‘normal science’, which is research based upon previous scientific achievements that have been adopted by a scientific community. It is the everyday practice of scientists, as they exercise their skills against a restricted range of puzzles. Scientists within the same paradigm are engaged in an enterprise which is structured in the same way by the paradigm. Thus, their theories, methods, practices and the puzzles they attempt to solve are very similar. Basic rules and standards are unquestioned, with dogma an essential element in the process.

    As normal science proceeds and puzzle-solving activities are carried out, anomalies inevitably begin to develop, when the paradigm does not work as it is supposed to, or when circumstances arise that are not soluble within the current paradigm. Over time, these discrepancies mount up until some scientists begin to doubt the paradigm itself, and a crisis develops. Eventually, competing paradigms emerge, and a scientific revolution occurs when a new paradigm replaces the old. Kuhn called the period of crisis ‘revolutionary science’, when new paradigms are proposed and compete for the allegiance of the scientific community. The new paradigm is ‘incommensurable’ with the one it replaced, meaning that there are no neutral standards for judging or comparing different theories. The process of abandoning the old in favour of the new cannot be a gradual, logical or scientific process based upon evidence or reasoning. The differences between advocates of competing paradigms at the time of crisis will be so great that they are unlikely to agree on what would constitute good grounds for preferring one to the other, since the criteria for those preferences are internal to the different paradigms. Thus, according to Kuhn’s early work, at least, the scientist does not reason herself into the new paradigm; Kuhn compared it to a conversion experience into religious groups. In this respect, Kuhn’s account of science is radically different from those, like Popper, who viewed science as fundamentally concerned with bold problem-solving, innovation and exploration.

    The education of the scientist, according to this image of science, is one that aims to produce competent puzzle-solvers, fully familiar with standards and methods. In large part, this training is achieved through students attempting repetitively to solve puzzles that are learned from standard textbooks. Science is distinguished from other disciplines by its dependence upon textbooks, and until the last stages in the education of a scientist, textbooks are systematically substituted for the creative scientific literature that made them possible. The education of the normal scientist, according to Kuhn is an initiation into a largely unquestioned tradition. Kuhn implied that science is science because scientists say it is.

    Kuhn presents a rather unattractive image of science education; one more akin to certain forms of religious indoctrination (Bailey, 2006). Science has traditionally been seen as the apex of rationality and critical thinking. Predictably, Kuhn’s portrait of normal science education has received a frosty reception from a number of philosophers and scientists. Popper’s comment is typical: “‘Normal’ science, in Kuhn’s sense, exists. It is the activity of the … not-too-critical professional … The ‘normal’ scientist, in my view, has been taught badly (Popper, 1970, pp. 52-3). Others have described Kuhn’s account of young scientists’ training in unquestioned paradigms, dependent on uncritically absorbing the content and methods of textbooks to be more characteristic of indoctrination than Scientific education (Bailey, 2000).

    Another difficulty for Kuhn’s argument is that it is too inclusive, describing areas of academic work that are not usually associated with science. Consider, for example, the following sport-related contexts:

    • Strength and conditioning;
    • Mental skills training;
    • Research into the history of the sport of chess-boxing;
    • The 4-4-2 formation in football/soccer;
    • Cricket match-fixing.

      Each of these could be understood in terms of individuals working within variations of a general agreed set of basic concepts, theories and methods. A theory of science that might include physics, criminal behaviour and Bayern Munich’s team organisation is hardly adequate!

      The debate between Popper and Kuhn is, of course, only a fraction of the on-going the the debates within the Philosophy of Science. However, the central issues they discussed continue to occupy scholars, and are indicative of some of the central problems confronting anyone wishing to talk coherently about the nature of science.

      Bad science

      Alice laughed. “There’s no use trying,” she said: “one can’t believe impossible things.” “I daresay you haven’t had much practice,” said the Queen. “When I was your age, I always did it for half-an-hour a day. Why, sometimes I’ve believed as many as six impossible things before breakfast.” (Lewis Carroll, Alice’s Adventures in Wonderland & Through the Looking-Glass, 1902)

      So, should we abandon the goal of demarcating between science and non-science? Since it is so difficult to draw a clean line demarcation, some think so. Paul Feyerabend, a student and then critic of Popper, claimed that there was nothing particularly distinctive or even special about the scientific method. He also argued that there has never been a rule within science that has not been broken at some point. Specifically, he put forward the view that science is just a tradition or form of inquiry among many others and it is not characterised by any distinctive methodological rules. So, Feyerabend concluded, “the only principle that does not inhibit progress is: anything goes” (1993, p. 14).

      This attitude seems hardly satisfactory to scientists confronted with questionable ideas that do not just undermine their professional work. Untested, unregulated and un-supported medical practices can be seriously harmful to people; they can even be fatal (Singh & Ernst, 2008), and such practices continue to be used regularly with athletes today (Gerbing, & Thiel, 2015). There are other dangers, too, as outlined by the philosopher and biologist, Massimo Pigliucci:

      “The first is philosophical: Demarcation is crucial to our pursuit of knowledge; its issues go to the core of debates on epistemology and of the nature of truth and discovery. The second reason is civic: our society spends billions of tax dollars on scientific research, so it is important that we also have a good grasp of what constitutes money well spent in this regard … Third, as an ethical matter, pseudoscience is not — contrary to popular belief — merely a harmless pastime of the gullible; it often threatens people’s welfare, sometimes fatally so.” (2013, unpaged)

      The list of questionable ideas that have entered the Sport and Exercise Sciences is endless. In many cases, the popularity of their adoption stems from athletes’ never-ending pursuit of a competitive edge; that marginal gain in performance that lets them to excel in their sport. Sometimes, they take up such ideas because their coach, or even sports governing body, promote them. These are often ergogenic aids in the areas of drugs or nutrition, training routines or competition strategies and equipment or products (Pelham, Holt, & Stalker, 2001). One of the perennial concerns with any new practice or aid is the placebo effect and its relationship to expectancy. Expectancy directly relates to the athletes’ beliefs regarding the effectiveness of new idea, and a considerable amount of empirical research has demonstrated that expectancy effects alone can generate increases in performance (Lindheimer, O’Connor, & Dishman, 2015).

      A recent example of an ergonomic product, that promised extraordinary gains for those who used it, is the hologram or energy bracelet. This is a rubber wristband carrying a hologram (a photographic recording of a light field). According to one manufacturer, the wristband incorporates ‘hologram frequency-embedded technology’. It is not entirely clear what ‘hologram frequency means, other than it “mimics Eastern philosophies“. The makers the best- known hologram wristband claimed the “performance technology is a mylar hologram embedded with a range of frequencies that react positively with your body’s energy field”, resulting in “faster synaptic response, enhanced muscle response, increased stamina, more flexibility and vastly improved gravitational balance” (cited in Brice, Jarosz, Ames, et al, 2011). For a while, these products became hugely popular partly due, no doubt, by the fact that celebrity sports stars like Cristiano Ronaldo, David Beckham, Rubens Barrichello and Shaquille O’Neal wore and endorsed them. Unfortunately, the creators of these products seem to have undertaken no tests on the effectiveness before marketing them, and all rigorous tests so far have found the wristbands to have no effect on performance (Hansson, Beckman, & Persson, 2015; Teruya, Matareli, Soares, et al, 2013).

      A second example of a questionable practice is learning styles. The relevance here is that assessments of learning styles is extremely common in certain areas of sport and exercise science, especially sports coaching. A survey of questionable practices in coaching in the UK revealed that every major national governing body for sport used some form of learning styles assessment at some point in their coach education, and anecdotal evidence suggests a similar pattern exists in other countries. Learning styles refers to the belief that different people learn information in different ways (Pashler, McDaniel, Rohrer, & Bjork, 2008). The assumption of the learning styles hypothesis is that different people learn information in different ways, and that formal experiences can be tailored to the individual learning style of the student, player or coach. It this idea is true, it would revolutionise coaching, as it would allow coaches to identify each player’s learning strengths, and to develop a bespoke programme of development, much as they might devise a physical fitness training schedule. As before, and despite its great popularity, there is no compelling evidence that matching formal instruction to individual perceptual strengths and weaknesses is any more effective than instruction which is not multi-sensory specific (Kirschner & van Merriënboer, 2013; Rohrer, & Pashler, 2012). Teaching according to an assumed preference may even cause harm, as learning is best promoted by taking students out of their comfort zones, not keeping them in it (Coffield, Moseley, Hall, et al, 2004).

      So, at the issues discussed by philosophers of science are not just of academic interest. They often have very practical implications. For example, distinguishing between pseudoscience and genuine science has a practical importance. But in the absence of neat criteria of demarcation (such as falsification), is it really possible to identified science?

      A useful tool used by philosophers when clarifying ideas is to consider the ‘necessary’ and/or ‘sufficient’ conditions for its use (Brennan, 2012). A sufficient condition occurs when it is enough to make something happen, whereas a necessary condition means that something will not happen unless the condition happens. For example, for a sports team to win a competition it is necessary to practice (but that is not enough on its own). Breaking a major rule during a game is sufficient for them to be disqualified. Popper believed that falsification was both a necessary and sufficient condition for an activity to count as science. There are reasons to suppose that this characterisation of science has serious problems. Kuhn’s account is less clear, but it would be fair to say that there are certain characteristics that are necessary for fields of inquiry to possess for them to be scientific, such as established paradigms, with shared concepts and methods. So, although Kuhn did not identify sufficient criteria for science, he did believe there are necessary ones. Some philosophers, however, have abandoned the pursuit of necessary and sufficient conditions for something to be science completely. In its place, they have tended to provide lists of criteria that make a field more or less scientific. According to this view, a field that shows a number of specified characteristics is considered more likely to be scientific or pseudoscientific. Tavris (2003), for example, wrote that, in contrast with pseudoscience, scientific research tends to be characterised by a willingness to question received wisdom, to gather empirical evidence to determine the validity of the prediction, and falsification. Another list tried to highlight the characteristics of pseudoscience (Lilienfeld, Lynn, & Lohr, 2015):

      • unfalsifiability
      • absence of self-correction
      • overuse of ad hoc immunizing tactics designed to protect theories from refutation’ of;
      • absence of connectivity with other domains of knowledge (i.e., failure to build on extant scientific constructs;
      • the placing of the burden of proof on critics rather than on the proponents of claims;
      • the use of obscurantist language (i.e., language that seems to have as its primary function to confuse rather than clarify;
      • overreliance on anecdotes and testimonials at the expense of systematic evidence;
      • evasion of peer review;
      • emphasis on confirmation rather than refutation;
      • absence of boundary conditions (well-articulated limits under which predicted phenomena do and do not apply); and,
      • the mantra of holism (the idea that scientific claims cannot be judged in isolation).

        Considered individually, many of these criteria are insufficient to indicate that field is pseudoscientific or has problems. Conclusive falsification, as has been seen, is extremely difficult (if not impossible), and obscure language is hardly absent from scientific journals. In fact, many of these characteristics could be identified in reputable scientists. The point, however, it is not to compile a list of necessary criteria for science, but merely a list of clues that will help to separate good scientific work from nonsense.

        This is a much more modest aim than Popper and Kuhn sought. But perhaps it is also more realistic? Science is complex and takes many forms, and this especially true for sport and exercise science, so it seems unlikely to be reducible to simple criteria of demarcation. There is much scepticism among philosophers about the possibility of clearly distinguishing science from non-science, in part by unsuccessful attempts to provide such criteria in the past, and by the acknowledgement of the ever-increasing diversity of methodologies and methods of those disciplines considered scientific. Early, ambitious attempts by the likes of Popper to provide a satisfactory criterion of demarcation have been replaced by more contested approaches. However, there are good reasons to continue this enterprise. And there are good reasons why is sport and exercise scientists should become familiar with these debates.


        “Begin at the beginning,” the King said, very gravely, “and go on till you come to the end: then stop.” (Lewis Carroll,  Alice’s Adventures in Wonderland & Through the Looking-Glass, 1902)

        So, sport and exercise scientists need an account of what science is, what scientists do, and what aims and methods characterise scientific research. Consumers of sport, exercise and health are bombarded with remarkable claims. With such responsibility handed to scientists and the scientific community, it is important that there is some strong understanding of what counts as a proper science and, as opposed to pseudoscience and non-science. Otherwise, it would be impossible to distinguish between contemporary exercise physiology and ancient theories of energy, or between sport psychology and psychobabble. The sciences of sport and exercise can bring many benefits, both for individuals and societies, from improved sports performance to the reduction of noncommunicable diseases. If there is a value in Sport and Exercise Sciences within the perennial context of limited resources, it seems important to be able to identify what counts as science and which research projects are worth supporting and learning from.

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        Exploring the world of data-driven innovation

        Mike Masnick is founder of the Copia Institute.

        In the last few years, there’s obviously been a tremendous explosion in the amount of data floating around. But we’ve also seen an explosion in the efforts to understand and make use of that data in valuable and important ways. The advances, both in terms of the type and amount of data available, combined with advances in computing power to analyze the data, are opening up entirely new fields of innovation that simply weren’t possible before.

        We recently launched a new think tank, the Copia Institute, focused on looking at the big challenges and opportunities facing the innovation world today. An area we’re deeply interested in is data-driven innovation. To explore this space more thoroughly, the Copia Institute is putting together an ongoing series of case studies on data-driven innovation, with the first few now available in the Copia library.

        Our first set of case studies includes a look at how the Polymerase Chain Reaction (PCR) helped jumpstart the biotechnology field today. PCR is, in short, a machine for copying DNA, something that was extremely difficult to do (outside of living things copying their own DNA). The discovery was something of an accident: A scientist discovered that certain microbes survived in the high temperatures of the hot springs of Yellowstone National Park, previously thought impossible. This resulted in further study that eventually led to the creation of PCR.

        PCR was patented but licensed widely and generously. It basically became the key to biotech and genetic research in a variety of different areas. The Human Genome Project, for example, was possible only thanks to the widespread availability of PCR. Those involved in the early efforts around PCR were actively looking to share the information and concept rather than lock it up entirely, although there were debates about doing just that. By making sure that the process was widely available, it helped to accelerate innovation in the biotech and genetics fields. And with the recent expiration of the original PCR patents, the technology is even more widespread today, expanding its contribution to the field.

        Another case study explores the value of the HeLa cells in medical research—cancer research in particular. While the initial discovery of HeLa cells may have come under dubious circumstances, their contribution to medical advancement cannot be overstated. The name of the HeLa cells comes from the patient they were originally taken from, a woman named Henrietta Lacks. Unlike previous human cell samples, HeLa cells continued to grow and thrive after being removed from Henrietta. The cells were made widely available and have contributed to a huge number of medical advancements, including work that has resulted in five Nobel prizes to date.

        With both PCR and HeLa cells, we saw an important pattern: an early discovery that was shared widely, enabling much greater innovation to flow from proliferation of data. It was the widespread sharing of information and ideas that contributed to many of these key breakthroughs involving biotechnology and health.

        At the same time, both cases raise certain questions about how to best handle similar developments in the future. There are questions about intellectual property, privacy, information sharing, trade secrecy and much more. At the Copia Institute, we plan to more dive into many of these issues with our continuing series of case studies, as well as through research and events.

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        Irish students win the 2014 Google Science Fair

        Ciara Judge, Émer Hickey and Sophie Healy-Thow became interested in addressing the global food crisis after learning about the Horn of Africa famine in 2011. When a gardening project went awry, they discovered a naturally occurring bacteria in soil called Diazotroph. The girls determined that the bacteria could be used to speed up the the germination process of certain crops, like barley and oats, by 50 percent, potentially helping fulfill the rising demand for food worldwide. Oh—and they’re 16 years old.

        Today, Ciara, Émer and Sophie were named the Grand Prize Winner and the 15-16 age category winners of our fourth annual Google Science Fair. They are some of thousands of students ages 13-18 who dared to ask tough questions like: How can we stop cyberbullying? How can I help my grandfather who has Alzheimer’s from wandering out of bed at night? How can we protect the environment? And then they actually went out and answered them.

        From thousands of submissions from 90+ countries, our panel of esteemed judges selected 18 finalists representing nine countries—Australia, Canada, France, India, Russia, U.K., Ukraine and the U.S.—who spent today impressing Googlers and local school students at our Mountain View, Calif. headquarters. In addition to our Grand Prize Winners, the winners of the 2014 Google Science Fair are:

        • 13-14 age category: Mihir Garimella (Pennsylvania, USA) for his project FlyBot: Mimicking Fruit Fly Response Patterns for Threat Evasion. Like many boys his age, Mihir is fascinated with robots. But he took it to the next level and actually built a flying robot, much like the ones used in search and rescue missions, that was inspired by the way fruit flies detect and respond to threats. Mihir is also the winner of the very first Computer Science award, sponsored by Google.
        • 17-18 age category: Hayley Todesco (Alberta, Canada) for her project Waste to Water: Biodegrading Naphthenic Acids using Novel Sand Bioreactors. Hayley became deeply interested in the environment after watching Al Gore’s documentary “An Inconvenient Truth.” Her project uses a sustainable and efficient method to break down pollutant substances and toxins found in tailing ponds water in her hometown, a hub of the oil sands industry.
        • The Scientific American Science in Action award: Kenneth Shinozuka (Brooklyn, New York) for his wearable sensors project. Kenneth was inspired by his grandfather and hopes to help others around the world dealing with Alzheimer’s. The Scientific American award is given to a project that addresses a health, resource or environmental challenge.
        • Voter’s Choice award: Arsh Dilbagi (India) for his project Talk, which enables people with speech difficulties to communicate by simply exhaling.

        As the Grand Prize winners, Ciara, Émer and Sophie receive a 10-day trip to the Galapagos Islands provided by National Geographic, a $50,000 scholarship from Google, a personalized LEGO prize provided by LEGO Education and the chance to participate in astronaut training at the Virgin Galactic Spaceport in the Mojave desert.

        Thanks to all of our young finalists and to everyone who participated in this year’s Google Science Fair. We started the Science Fair to inspire scientific exploration among young people and celebrate the next generation of scientist and engineers. And every year we end up amazed by how much you inspire us. So, keep dreaming, creating and asking questions. We look forward to hearing the answers.

        Posted by Clare Conway, on behalf of the Google Science Fair team
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        Change the world: the 2014 Google Science Fair Global Finalists

        Samuel Burrow, 16,from the U.K., wants to improve the environment by reducing pollution. Taking inspiration from the chemical used in sunscreen, Samuel created a special coating that reduces waste chemicals in the air when subjected to ambient light. Guillaume Rolland,17, from France, aims to revolutionize mornings by creating a scent which will wake you up with maximum energy at a prescribed time.

        These are just a few of the European examples of the 15 incredible projects we’ve named as the global finalists for 2014 Google Science Fair. This is our fourth time hosting the competition as a way to encourage the next generation of scientists and engineers. From Russia to Australia, India to Canada, this year’s finalists (ages 13-18) are already well on their way to greatness. Europe accounts for a full third of the finalists. Read about them – and about all 15 finalist projects – on the Google Science Fair website.

        What’s next for our young scientists? Well, next month, they’ll be California-bound to compete at Google HQ for the three Age Category Awards (ages 13-14, 15-16, 17-18) and of course, the overall Google Science Fair Grand Prize Award. The competition will end in style with an awards ceremony, which will be live streamed on the Science Fair YouTube channel and on our website. Tune in to be one of the first to find out this year’s winners!

        But first, you get to have your say! We need you to pick your favorite project for the 2014 Voter’s Choice Award. Show your support for the finalists and cast a vote on the Google Science Fair website beginning September 1. Every year, we are blown away by the projects and ideas these young people come up with, and you will be too.

        Posted by Clare Conway, Google Science Fair Team
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        Hollywood has a poor reputation when it comes to scientific accuracy.  Perhaps the classic example is the Rachel Welch’s One Million Years B.C., which was premised on the claim that humans and dinosaurs co-existed and battled each other for survival.  In fact, the last dinosaurs became extinct around 65 million years ago, and the species of whom which Ms Welch is a particular fine example did not appear until round 200,000 years ago.

        This film is not unusual: most films that touch on science seem to get it wrong in some major respects.  James Cameron is a notorious stickler for details, yet he felt compelled to change the starlight backdrop to Titanic for that film’s re-release when Neil Degrasse Tyson pointed out that the stars were in the wrong place in the original!  And almost every space film ever made, from Star Wars to the new Star Wars has failed to deal with the annoying fact that – what with space being a vacuum – there would be no noise.

        The recent movie Lucy, starring Scarlett Johansson, joins this list of offenders by rekindling the myth that we use only 10 percent of our brains.  Johansson’s eponymous character undergoes a transformation when a bag of drugs she was forced to transport inside of her stomach leaks, and rather than causing an agonising, inevitable death, this event somehow gives her access to all of her brain’s potential.  With this gift Lucy is ability to learn languages in an instant, beat up gangsters, and throw around cars with the power of her mind.

        The premise of the film is summarised by Morgan Freeman, who plays the world’s leading neuroscientist: “It is estimated most human beings use only 10 percent of the brain’s capacity.  Imagine if we could access 100 percent.”

        The idea that we use only a fraction of our cognitive capacity has become something of a Hollywood cliche.  From Flight of the Navigator (1986), via John Travolta’s Scientology advertisement Phenomenon (1996), Inception (2010), and Limitless (2011), movies have asked ‘what if we really are using just a fraction of our true potential?’  Even The Simpsons succumbed, when Bart is prescribed a fictional hyperactivity drug that allows him to use the “full” potential of his brain:

        “Most people use 10 percent of their brains. I am now one of them!”

        Wouldn’t it be nice?
        Many speculative ideas about the brain and learning seem to be motivated by a powerful drive, that I call the ‘wouldn’t it be nice drive?’, inspired by the Beach Boys paean to wishful thinking:

        Wishful thinking has become one of the dominant themes in modern educational practice, and lies behind the waves of bullshit and pseudoscience that currently bombard schools. 

        Wouldn’t it be nice if my son was not academically weak?  Oh look, it turns out that he isn’t!  He is a kinaesthetic learner, and the school system simply ignores his gifts!

        Wouldn’t it be nice if there was some magical way to accelerate my daughter’s performance in mathematics?  Quick, get the chequebook: neuro-psycho-physio-gym can join up disconnected parts of her brain without her breaking a sweat!

        Wouldn’t it be nice if I could become happier, healthier and wealthier, without investing any time or energy into making it happen?  Woo-wee!  There are lots of ways of doing this, and the only reason they aren’t better known is because scientists and governments are keeping them from us!

        I suspect that ideas like those promoted in films like Lucy give fuel to this sort of wishful thinking by combining an allusion to ‘sciency’ brain talk with the intuitive power of a simple idea that is frequently repeated.  And people do believe it.  A 2012 survey of British and Dutch teachers found that 48% and 46%, respectively, accept the claim.  According to a 2013 study of Americans by the Michael J Fox Foundation for Parkinson’s Research, 65% of Americans believe it too.

        The claim has now spread around the world, including into schools and workplaces.  I have heard doctors, teachers and academics cite it as if it were proven fact.  You probably have too.

        The bad news
        Unfortunately, it is not true.  We do not use 10% of our brains: most of us have access to 100%, and without the boost from a life-threatening injection of drugs.

        The human brain has evolved over hundreds and thousands of years, at great cost.  The average brain weighs just 3% of the body’s weight but uses 20% of the body’s energy.  The idea that this process of development would result in an expensive organ that left 90% of its capacity unused is absurd.  And unused cells in the brain that are unused would turn to atrophy, anyway.  Not surprisingly, brain scans show the entire brain is active all of the time, even whilst resting or sleeping.  In fact, even the most basic functions of the brain – like those controlling breathing and balance – take up more than 10%, and these are needed just to keep us alive.

        But don’t take my word for it …

        So what?
        The 10% Myth is unusual among contemporary brain myths as it does not seem to have originated from a misunderstanding of real science.  It seems that it was simply made up.  No one really knows where it began, although a popular culprit is American psychologist and philosopher William James, who once mentioned in passing that we “are making use of only a small part of our possible mental and physical resources”.  This comment was repeated in the preface to Dale Carnegie’s 15-million-selling How to Win Friends and Influence People.

        Does it matter that it is not true?

        Many people find the idea inspiring in some way.  Perhaps we should continue to use the idea, but as a metaphor rather than a factual claim.  We do know that performance in almost every domain can be significantly improved through lots and lots of high quality practice, so maybe the 10% Myth can become a memorable ‘meme’ for emphasising the difference between our potential and our current performance.  Perhaps.

        But the simple fact is that most people who repeat the 10% Myth are not using it in this way.  They are making a claim about the brain that is not true, and is not even plausible.  And since gullibility and scientific illiteracy tend to like company, this myth is often accompanied by a host of other nonsense.  So, Lucy does not just become brighter and stronger.  She develops telekinesis!  Advocates in the wonderful world of social media use the 10% Myth as the jumping-off point for an endless stream of equally unsubstantiated claims, from NLP and learning styles to spoon-bending and spiritual healing!

        We do not use 10% of our brains.  Not even people who believe the claim do.  Perhaps it is about time we put this particular myth to rest?  Believing bullshit is a dangerous habit to acquire.

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        Thirty ideas to change the world: EMEA Science Fair finalists

        Many great scientists developed their curiosity for science at an early age and in January we called on the brightest young minds from around the world to send us their ideas to change the world. Our 2013 Google Science Fair attracted an exciting and diverse range of entries, with thousands of submissions from more than 120 countries.

        After a busy few months for the judges, we’re ready to reveal our 90 regional finalists for the 2013 Google Science Fair. It was no easy task selecting these projects, but in the end their creativity, scientific merit and global relevance shined through.

        Thirty of the finalists come from 15 countries in Europe, Middle East and Africa, from Belarus to the United Kingdom. They range from Aya Hazem, age 15, from Egypt who is working on a SOS Phone to prevent domestic violence to three Kenyan 14 year olds who are pursuing a project titled Can heat and tomatoes produce electricity?. In the UK, 13 year old Isabel McNulty is one of the youngest finalists; her project is called: Natural Electricity Production Using The Dynamo Effect.

        The 90 Regional Finalists come from all over the world.

        For the second year, we’ll also be recognizing the Scientific American Science in Action Award. This award honors a project that makes a practical difference by addressing an environmental, health or resources challenge. From the 90 finalists’ projects, 15 were nominated for this year’s award.

        On June 27 we’ll announce the 15 global finalists and the winner of the Science in Action Award. These young scientists will then be flown to Google’s California headquarters for the last round of judging and a celebratory event on September 23.

        Thank you to everyone who submitted a project—we really appreciate all your hard work. Congratulations to our 90 regional finalists!

        Posted by Sam Peter, Google Science Fair team
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