Writing the objectives: the right words to use

The methods section of the proposal is the place where we show we know what we are doing.  And most researchers are capable of demonstrating that they are masters of their methods as it is the work of their everyday lives and they know it inside out and tend also to know where the state-of-the-art is with it.  The objectives statements are different kinds of writing acts and deal with why the project is important rather than what it will do and although objectives and methods are very often mixed up it is critical that we keep them carefully apart.  Other aspects of writing objectives are covered in discussions of writing backwards, thinking SMARTly and FINER, and making sure that we are making promises about something new in a very strong sense.

A critical part of the objective statement is demonstrating to the evaluator that the objective has been reached i.e., how do we show that we know what we know in an ERC objective statement, how we will demonstrate that it has been reached.  This is a far more difficult thing and far more important thing to do than demonstrating that the researcher knows how to do research.  The methods are relatively less important in these proposals although people promote them very highly up the logical order of the presentation and it is necessary to draw attention very carefully to any aspects of them that are fresh or innovative and challenging.

So, here we have to think about the fairly complex question of how science shows proof and how scientists convince each other that they know what they know.  It is a question of epistemology that we are inevitably drawn into here but I hope to come out very quickly on the other side of these thoughts with some very simple recommendations about what words and ideas to use in objective statements and to have got a better justification of exactly why this is the best way to phrase them.

Episteme is “knowledge” and logos is “the study of” (very broadly) and so in English epistemology is the study of the nature, source and limitations of knowledge. So, when we are thinking about what ideas we need to use to best prove that we know some new stuff and can use it to new ends in the objectives statements we are dealing with questions of the epistemology of science.  Therefore, I think it is easiest if we take some simple ideas from those complex discussions for our practical objective of building powerful and convincing objectives.

The previous post in this blog dealt with similar questions about ‘how do we know this’ and tried to suggest that the best way of dealing with objectives in the ERC is to take a realist approach to answering that question.  I suggested that we need to answer it by showing that we know we have this new knowledge and that objectives have been reached because it is a new capacity to do new things, it is a new power to ‘interfere’ with the world in a way we couldn’t before the project.  I suggestd that rather than theoretical progress we are able to sell projects best by showing that they make practical differences in the world.

Here we are trying to find the right words and concepts to answer this ‘how do we know’ question in a bit more practical detail.  I’ll refer quickly to the work of Karl Popper in the philosophy of science although the same point could be made from any number of positions in this vast body of thought.  For Popper scientific thinking is demarcated from other types of thinking by the fact that it is falsifiable i.e., that a theory is scientific only if it is refutable by a conceivable event or observation and that one genuine counter-instance falsifies the whole theory (as always in this blog we are nearly murdering the ideas here for sake of brevity and ask indulgence from the reader for that as in fact the ideas are only a way to get as quickly as possible to a practical piece of advice that is well justified).  At the heart of this idea of science is the idea of ‘prediction’.  Science is characterised by its entailing and underwriting predictions that observations might reveal to be false but which take us one step forward in new knowledge and capacity if confirmed as successful.  It is through the creation of falsifiable predictions that science takes its steps forward.  Prediction is the best quality control test we have for the adequacy of our scientific theories and for confirming that we know what we claim to know.  Fundamental to a good prediction is specificity and detail.  And the more detail there is the more daring it becomes.  It is easy, for instance, to say that the a person will die – they can’t avoid it and the prediction carries with it no risk.  However, to say that a Fred will die in 892 days at 12 noon is far more detailed and consequently far more risky and a far greater achievement and a great deal of information can be derived from it if it is accurate.

This line of thinking will take us off into another post about the level of detail with which objectives need to be phrased where we’ll (it’ll come as no surprise) be saying that the level of detail in general is far too low and that the better the statements are they greater their granularity.  And it will also take us off towards a far better understanding of the idea of risk which pervades the ERC literature and confuses researchers as they try to write.  Risk, as we’ll see, inheres in good objectives statements as they aim to step over the state-of-the-art frontier which is always highly risky and the greater the level of detail in the promise so the higher the level of risk that sits inside them and which we can easily draw attention to with very little extra effort.  Too many researchers treat the idea of risk in the simpler but slightly stranger sense, given that we are doing science, of the risk of not finding the right people, of the data not being clean enough, of a machine not being able to detect this that or the other which are largely extraneous risks which are interesting to some extent but not really the issue at hand.  When the ERC say risk they probably mean something like the possibility that the predictions set out in the strong objective statements will be falsified by observation, that they will turn out not to be true rather than that certain contingencies will get in the way of the research making the observations in the first place.

But to return to the task of finding the right words to use when writing objective statements I’d like to focus again on the idea that at the heart of Popper’s very influential ideas about the epistemology of science i.e., the notion that science is continually trying to achieve (and continually failing to achieve completely) new levels of control of natural systems and to be able to make detailed predictions about them which can be tested by future observations.

So, I would argue – and I make this clear during the training presentation that I give often across the EU – that the very best words to use in the objectives statements are ‘control’ and ‘predict’.  These are the ideas that are closest to the core of what science is commonly understood as being and which seem to be underpinning the epistemology of the ERC’s own vision of science practice and purpose.  I think we can think of these two ideas as very closely linked indeed and at about the same level of importance as each other and can be combined successfully in powerful objectives statements.  I think they are very useful tools to use in objectives when making bold claims in a proposal designed to dazzle the evaluator and get the researcher’s hands on the cash.

In an earlier post discussing ideas in the objectives statements I recommended using ‘evaluate’, ‘judge’, ‘recommend’ etc. (the list of words is easily found) along with ‘predict’ and ‘control’ because they are higher order thinking skills in Bloom’s Taxonomy of learning effects.  Such words are excellent ways of showing high levels of new knowledge and mastery and, most importantly, for setting the ideas that underpin the objectives in contrast to the lower level ideas about describing and identifying and collecting up which dominate so many of the statements that I get to read.  The justification for using the ideas of controlling and predicting that I draw out of Popper I think is at least, probably more, powerful and persuasive. Together with the reference to the work of Bloom I think we have a clear case for arguing that objectives based around the ideas of control and predict as being among the very strongest possible approaches to writing them and certainly the first one I would recommend.

So, in summary, I think the ERC supports a vision of science that is broadly Popperian and this is reflected in the vocabulary and concepts they use to structure the programmes i.e., the idea of risky, clearly stated objectives-driven research located in the great detail in the current state-of-the-art and aimed at opening new horizons of knowledge.  The particular philosophical underpinnings of the programme, I think would be a very interesting topic for research in and of itself as the ERC is a highly influential body in world science – at least such a study should give those bidding into the programmes a real edge arising from a firm understanding of what is in the mind of the funder!  But I think even without that detailed investigation we know enough about the ERC now to know that it is based on mainstream science theory in which the idea of ‘control’ and of ‘prediction’ are the key measures that scientists can use to show that they know what they know.  And, so, I would suggest that these are the ideas we use to base the writing of the objectives on as by doing so we are tapping into some of the deepest and most commonly held ideas about what science is like and what new ideas should be doing and how they assessed as being real and valuable.

An earlier post on writing the objectives dealt with the idea that must logically kick off each statement i.e., that it is ‘for the first time’.  And, in keeping with the individual-researcher focus of the programmes, this must be followed up with an ‘I’ and not a ‘we’ as the researcher takes up the mantel of the originating protagonist in this mini-drama.  And then we can move towards completing these statements with something like ‘control’ or ‘predict’ or some other words from Blooms Taxonomy at the higher levels.   And to make the statement come to life we need,  as we saw in the earlier post on the work of Hacking, plenty of detail about what this new promised power will actually allow us to do and to what degree i.e., we need to make the promise as detailed as possible if we are to complete the  job of objective making.  It is not to say that we need to use exactly these words in a formulaic way – although I have worked with people who successfully did use this objectives formula three times more or less unvaried – but that these are some of the main elements that we need to get down on the page in some way or other to give us the best chance of being clearly understood and fairly evaluated: this is all we can control – if they like what we are promising is an entirely different matter.