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Head hits cause brain damage, but not always. Should we ban sport to protect athletes? Exposure to electromagnetic fields is strongly associated with cancer development. Should we ban mobile phones and encourage old-fashioned wired communication? The sciences are getting more and more specialized and it is difficult to judge whether, say, we should trust homeopathy, fund a mission to Mars, or install solar panels on our roofs. We are confronted with questions about causality on an everyday basis, as well as in science and in policy.

Causality has been a headache for scholars since ancient times. The oldest extensive writings may have been Aristotle, who made causality a central part of his worldview. Then we jump 2,000 years until causality again became a prominent topic with Hume, who was a skeptic, in the sense that he believed we cannot think of causal relationships as logically necessary, nor can we establish them with certainty.

The next major philosophical figure after Hume was probably David Lewis, who proposed quite a controversial account saying roughly that something was a cause of an effect in this world if, in other nearby possible worlds where that cause didn’t happen, the effect didn’t happen either. Currently, we come to work in computer science originated by Judea Pearl and by Spirtes, Glymour and Scheines and collaborators.

All of this is highly theoretical and formal. Can we reconstruct philosophical theorizing about causality in the sciences in simpler terms than this? Sure we can!

One way is to start from scientific practice. Even though scientists often don’t talk explicitly about causality, it is there. Causality is an integral part of the scientific enterprise. Scientists don’t worry too much about what causality is­ – a chiefly metaphysical question – but are instead concerned with a number of activities that, one way or another, bear on causal notions. These are what we call the five scientific problems of causality:

• Inference: Does C cause E? To what extent?
• Explanation: How does C cause or prevent E?
• Prediction: What can we expect if C does (or does not) occur?
• Control: What factors should we hold fixed to understand better the relation between C and E? More generally, how do we control the world or an experimental setting?
• Reasoning: What considerations enter into establishing whether/how/to what extent C causes E?

This does not mean that metaphysical questions cease to be interesting. Quite the contrary! But by engaging with scientific practice, we can work towards a timely and solid philosophy of causality.

The traditional philosophical treatment of causality is to give a single conceptualization, an account of the concept of causality, which may also tell us what causality in the world is, and may then help us understand causal methods and scientific questions.

Our aim, instead, is to focus on the scientific questions, bearing in mind that there are five of them, and build a more pluralist view of causality, enriched by attention to the diversity of scientific practices. We think that many existing approaches to causality, such as mechanism, manipulationism, inferentialism, capacities and processes can be used together, as tiles in a causal mosaic that can be created to help you assess, develop, and criticize a scientific endeavour.

In this spirit we are attempting to develop, in collaboration, complementary ideas of causality as information (Illari) and variation (Russo). The idea is that we can conceptualize in general terms the causal linking or production of effect by the cause as the transmission of information between cause and effect (following Salmon); while variation is the most general conceptualization of the patterns of difference-making we can detect in populations where a cause is acting (following Mill). The thought is that we can use these complementary ideas to address the scientific problems.

For example, we can think about how we use complementary evidence in causal inference, tracking information transmission, and combining that with studies of variation in populations. Alternatively, we can think about how measuring variation may help us formulate policy decisions, as might seeking to block possible avenues of information transmission. Having both concepts available assists in describing this, and reasoning well – and they will also be combined with other concepts that have been made more precise in the philosophical literature, such as capacities and mechanisms.

Ultimately, the hope is that sharpening up the reasoning will assist in the conceptual enterprise that lies at the intersection of philosophy and science. And help decide whether to encourage sport, mobile phones, homeopathy and solar panels aboard the mission to Mars!

The post Why causality now? appeared first on OUPblog.

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Game theory must be the epitome of Western faith in logic. We think that if we plug in some variables and press a button we can predict the future. Apparently, we apply it to all sorts of things: economics, war… It’s founded on our belief that if we know enough facts we’ll be in control. But do we really think that we can ever come close to factoring everything in? Isn’t it a bit like trying to predict exactly how the flap of a butterfly’s wings in Tokyo will affect the time that Mrs Morgan arrives at work in Sheffield?

And yet, perhaps those game theorists have a point. If, as quantum physicists now seem to believe, "we are one", the flap of a butterfly’s wings will affect the time that Mrs Morgan gets to work. Nothing acts in isolation. Every event, every movement, every action, every thought is affected by everything that has come before it and in turn affects everything that comes afterwards. So there is, in fact, a formula connecting Tokyo and Sheffield – and if we could plug in every variable we could calculate the outcome.

In order to predict such complex causality with any certainty, however, our equation would have to take everything into account. The result would be that it wouldn’t just predict one outcome, it would predict every outcome. It would be huge. It would be a mathematical equation that would incorporate the entire world. No - the universe! Wait a minute – this equation would be the universe. Our primitive little left brains, which like to quantify and categorize, simply aren’t sophisticated enough for this sort of maths.

Our right brains, however, would seem to be designed to compute exactly this sort of all-encompassing complexity. Not logically – but intuitively. In the creative and scientific disciplines, tiny portions of the Great Equation tend to reveal themselves in brief, bright flashes of insight, during which we shout ‘eureka!’ In fact, David Bohm, quantum physicist and author of On Creativity, believes that the intrinsic appeal of all artistic or creative endeavour is this moment of satisfaction, in which we perceive what he describes as ‘a certain oneness and totality or wholeness, constituting a kind of harmony that is felt to be beautiful’.

The truth, in other words.



Writing fiction involves exactly these sorts of flashes of insight. They’re like lightning strikes, illuminating the way. Flash by flash we find our way through the forest, and step by step the narrative unfolds. Every step must link logically – truthfully – to the one before it and the one that comes after it. One false note and the chain is broken and the mathematics goes awry.

If we try and predict a plot logically, using a pre-arranged formula – the way that game theory seems to – it tends to feel ‘wrong’. It never quite rings true in a way that makes you want to shout ‘eureka!’ What a novelist wants is for the causality of events to be so sophisticated and yet so flawlessly logical that afterwards the reader thinks, “I didn’t see that coming – but in retrospect, of-course it was inevitable.” This sort of integrity is rarely achieved by the logical mind; it has to be intuited.

So, step by step we intuit the way. We draw on all the powers of our unconscious to intuit exactly what a certain character will do and what will happen as a consequence. Intuition is about widening our perspective, holding the whole world of our novel in the periphery of our vision in order to feel the pattern.

The end result is a plot: a linked sequence of cause and effect that has an almost scientific integrity to it. The plot reveals the underlying pattern, the mathematical formula that underpins our novel’s ‘reality’. How do we know if we’ve got it right? Because it feels right. It clicks.


Sometimes people assume that writing fiction must be easier than non-fiction. They assume that because you can make it up as you go along, you can write whatever you want. But nothing could be further from the truth. You can’t just write whatever you want. You have to write exactly what would happen. No wonder writing fiction is so difficult. We are trying to predict the future.

www.heatherdyer.co.uk

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Many thanks to everyone who participated in this month's blog series! I had a lot of fun gathering candid and heartfelt responses from authors. Lorie Ann asked me to post my own list, so here goes nothing:

7 Things You Don't Know About Me
1) I've been writing stories and songs since birth, practically.
2) I am capable of charming squirrels out of trees.
3) There is no television show I have loved more completely from start to finish than Leverage.
4) I love word play.
5) Synchronicity and causality are recurring themes in my life.
6) Chances are, I'm shorter than you.
7) I project. In more ways than one. 

So there you have it! I hope March has been lovely for all of you. Don't forget to mark your calendars for Operation Teen Book Drop 2014, which will be happening in just a few weeks on April 17th. Stay tuned to the readergirlz blog, Facebook, and Twitter to learn how you can participate and #rockthedrop!

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by Caroline Relton

Epidemiology, a well established cornerstone of medical research, is a group level discipline that aims to decipher the distribution and causes of diseases in populations. Epigenetics, perceived by many as the most fashionable research arena in which to be involved, is a mechanism of gene regulation. What brings these perhaps unlikely partners together?

Epigenetic processes are key features in gene regulation. Epigenetic patterns are laid down in early development and are moulded through in utero and early postnatal life and continue to show some degree of plasticity across the lifecourse. Many environmental, behavioural, nutritional and lifestyle factors are believed to influence epigenetic patterns and in some case the evidence base is substantial. What is less clear is the role of this environmentally modifiable ‘epigenome’ on disease risk in populations. This is where epidemiology can help. A good starting point for an epidemiological engagement with epigenetics is clearly identified by Nessa Carey, in her recent popular science book The Epigenetics Revolution:

“The majority of non-infectious diseases that afflict most people take a long time to develop, and then remain as a prob­lem for many years if there is no cure available. The stimuli from the environment could theoretically be acting on the genes all the time in the cells that are acting abnormally, leading to disease. But this seems unlikely, especially because most of the chronic diseases probably involve the interaction of multiple stimuli with multiple genes. It’s hard to imagine that all these stimuli would be present for decades at a time. The alternative is that there is a mechanism that keeps the disease-associated cells in an abnormal state, i.e. expressing genes inappropriately. In the absence of any substantial evidence for a role for somatic mutation, epigenetics seems like a strong candidate for this mech­anism”.

Recent literature points to a role for epigenetic variation in a range of diseases including neurological disease, cardiovascular disease, osteoarthritis and obesity but in most instances these are correlations without robust evidence of causality. Indeed, epigenetics is often proffered as the answer to many unresolved causes of disease. The enthusiasm for establishing whether epigenetic mechanisms link the environment with disease development must be tempered by the knowledge that the epigenome is dynamic and has as much  potential to  respond to disease as respond to the environment. Therefore it is very difficult to disentangle cause from consequence when studying epigenetic variation and disease.

This is just one of the many challenges that face researchers interested in understanding the role of epigenetics in common complex disease. Other challenges include the differences in interpretation of the term ‘epigenetics’ itself – in a field that attracts cell, developmental and evolutionary biologists, epidemiologists and bioinformaticians, amongst others, it is unsurprising that epigenetics means different things to different people and discussions of its relevance to disease can sometimes suffer misinterpretation.

The methods at our disposal to accurately measure epigenetic variation and in turn assess the impact this has upon disease risk are still being developed and there is much to do in this arena with respect to when, where and how to look at the epigenome. The complexity and interplay of multiple factors in determining d

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Be sure to read the first two parts of this essay:

• Part 1: Terminology and the Difference Between Narrative and Story
• Part 2: Taking a Closer Look at Story

Got  Plot?

Okay, so I’ve got a story, but do I have a plot? Let’s take a look at how plot is different. Once a writer has established his or her story (what happens) one will need to decide which events to present to the reader. This is the construction of a plot. A plot is “someone’s telling of the story” (Liz), “how the story is presented” (English Basics), or “the arrangement of what happens” (Chea). The author isn’t going to share every event of the story, (well you could, but that would probably be a lot like reading a boring history book), instead an author will select specific events that best engage the reader in the story (see figure 3).

To create a plot, however, one won’t select events at random. There’s another important ingredient.

In Forester’s original example of story he said: “The King died and then the Queen died.” Here we have two events which create a story but it does not have a plot. In order for this to become a plot there must be a connection of causality. Forester thus offers: “The King died and then the Queen died of grief” (Cowgill). Stephenson Chea says that “in examining plot, we are concerned with causality, with how one action leads into or ties in with another” (2). Forester’s addition of the words “died of grief” shows the action of the Queen’s death is a result of the previous event.  Plotting means selecting events with an internal logic, events “that lead the characters from their situations and attitudes at the beginning of the problem to their situations and attitudes when the effort to solve the problem is finally over” (Dramatica). In The Art of Fiction, John Gardner describes this logic as profluence.  He says “a story contains profluence, and the conventional kind of profluence – though other kinds are possible – is a causally related sequence of events. This is the root interest of all conventional narrative”(55).  He goes on to state that the reason profluence is necessary is because “we cannot read a whole novel in an instant, so to be coherent, to work as a unified experience…narrative must show some profluence of development” (55).

If a story is what happens, and plot is the selection of events with a cause and effect relationship, one can begin to see how the two overlap. Ultimately an author in early stages of novel development may be simultaneously figuring out the story (what happens) as well as plotting it (how and why it happens). Humanities Professor Ron Layne states that “the plot is a series of conflicts or obstacl

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