Referencing, plagiarism and building credibility

Plagiarism is a big deal in academia. As students we are told often what a terrible thing it is to plagiarise the work or ideas of others, and that if we do plagiarise we could face serious penalties. Academics have lost jobs, status and reputations over plagiarism – in South Africa there was a famous case in 2007 of ‘Chippy’ Shaik having his PhD degree rescinded as a result of allegedly plagiarising 2/3 of it, and in 2013, Dr Jane Goodall was accused of lifting several passages verbatim or near verbatim from other sources in a book that is scheduled to appear this year. Even outside of academia, cases of plagiarism are taken very seriously – US Senator Rand Paul and Transformers actor Shia Lebouf have both been accused of using the words and ideas of others and passing them off as their own without crediting the original sources.

Plagiarism is not just copying verbatim the words or ideas of others and passing them off as your own. Even when you summarise, paraphrase or incorporate the ideas of others in your own work without citing the original source, you are regarded as a plagiarist. Plagiarism is generally defined as the intentional or reckless use of the words and ideas of others, rather than unintentional or accidental actions, but the burden of proof about intentions is often on the student – how do you show that, if you did plagiarise, you did so accidentally rather than on purpose? One way you could do this is by showing your ‘paper trail’ – all your notes, and reference lists and planning that went into your writing. But this is a hassle, and it’s by far easier to do what you can to avoid plagiarism altogether by keeping track of all your source material, and by working hard on developing your own voice in your writing.

But, for a PhD student, this is not as simple as it may sound for a couple of reasons. The first, big reason, is that as PhD students we read a lot. We read and read and read, we make a lot of notes, and after a while these ideas become part of our own ideas, and the theory we are influenced by and that ‘gels’ with the way we see our research or the world around us really influences how we think. It starts to become difficult to tell our own ideas pre-reading apart from our ideas post-reading. We can, after a while, write 3 or 4 or 5 pages of a ‘literature review’ without even needing to consult a reference. This is how well you end up knowing your stuff. This is a good thing – as a PhD student you need to know your stuff that well. But, the downside is that you have to be really careful not to plagiarise. Which ideas are yours and which are the ideas of other authors and researchers whose work has influenced your own? Which ideas do you have to reference and which ones can you claim as your own?

The second, connected reason, is that avoiding plagiarism and being an honest and ethical writer and researcher is about more than just including references in the text and in a bibliography. If you copy your whole literature review piece by piece and reference it perfectly, you really are still committing a form of plagiarism, and you’re not doing your own research either. Being an honest and ethical writer and researcher requires an understanding of knowledge, and how it is built, debated, challenged and changed in academic communities of practice and research. We build when we research and write – we build on the ideas of others, on their research, on their data, on their methodologies and on their words. We join conversations, and we debate, challenge, dispute, agree and slowly establish our own voice and our own ideas, claims and positions which we hope (and fear) that others will challenge us on. So, even if the idea is also yours (and the writers’ you are citing), referencing well does more than just help you to avoid plagiarism; it helps you to establish the credibility of your voice, your ideas and your developing argument. This is essential for writing a credible and acceptable dissertation, and for ensuring that you do actually get full credit for your own ideas and arguments. If you reference poorly, lose sources and get sloppy, you risk being accused of plagiarism, you risk being discredited and you risk shortchanging yourself on your own intellectual development and growth.

I used two simple tools to help me: One was the P(oint), E(vidence), E(xplanation) paragraph writing structure, which helped me to ensure that I started and ended each paragraph with my own ‘voice’ and included accurately cited and referenced ‘Evidence’ to support my ‘Points’ and ‘Explanation’. As a tool it can be adapted and played with and it really works. The other was a bit techno-backwards, but I kept a manual list in separate file of all the sources I was using as I wrote. I cross-checked this regularly. I had it open whenever I was working on part of a chapter and I copied across the in-text references either at the end of a section or as I wrote, depending on how well or smoothly the writing was going. I regularly went into this list and filled in all the information I needed, and reorganised, cut and added as I went. I know I could have used Refworks, Endnote, Mendeley or other similar tools, but I actually found the effort of learning to use these tools effectively too much for my already-taxed brain. I trusted my system, and that gave me peace of mind. (I don’t think I left out any references, but frankly I am not going back to find out!)

Any tool you use, whether un-technological one like mine or more automated like Refworks etc, is only as good as the person using it. These tools can’t do your writing for you, or make sure you don’t plagiarise or leave references out of your reference list (or leave too many in after chapters get cut). They can’t do the work of developing your voice. But, learning to use particular tools, whichever ones work for you, can save you a lot of time and reduce your anxiety about keeping track of your sources as your PhD progresses. And using these tools to help you reference accurately can also help you show your reader your emerging voice that much more clearly as you write.

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Data: collecting, gathering or generating?

I’m thinking about data again – mostly because I am still in the process of collecting/gathering/generating it for my postdoctoral research. I had a conversation with a colleague at a conference I went to recently who talks about ‘generating’ his data – colleagues of mine in my PhD group use this term too – but the default term I use when I am not thinking about it is still ‘collecting’ data. I’m sure this is true for many PhD scholars and even established researchers. I don’t think this is a simple issue of synonyms. I think the term we use can also indicate a stance towards our research, and how we understand our ethical roles as researchers.

Collect (as other PhD bloggers and methods scholars have said) implies a kind of linear, value-free (or at least value-light) approach to data. The data is out there – you just need to go and find it and collect it up. Then you can analyse it and tell your readers what it all means. Collect doesn’t really capture adequately, for me, the ethical dilemmas that can arise, large and small, when you are working in the ‘field’. And one has to ask: is the data just there to be collected up? Does the data pre-exist the study we have framed, the questions we are asking, and the conceptual and analytical lenses we are peering through? I don’t think it does. Scientists in labs don’t just ‘collect’ pre-existing data – experiments often create data. In the social sciences I think the process looks quite different – we don’t have a lab and test tubes etc – but even if we are observing teaching or reading documents, we are not collecting – we are creating. Gathering seems like a less deterministic type of word than collecting, but it has, for me, the same implications. I used this word in my dissertation, and if I could go back I would change it now, having thought some more about all of this.

Generating seems like a better word to use. It implies ‘making’ and ‘creating’ the data – not out of nothing, though; it can carry within it the notions of agency of the researcher as well as the research participants,  and notions of the kinds of values, gazes, lenses, and interests that the parties to the research bring to bear on the process. When we generate data we do so with a particular sense in mind of what we might want to find or see. We have a question we are asking and need to try and answer as fully as possible, and we have already (most of the time) developed a theoretical or conceptual gaze or framework through we we are looking at the data and the study as a whole. We bring particular interests to bear, too. If, as in my study, you are doing research in your own university, with people who are also your colleagues in other parts of your and their working life, there are very particular interests and concerns involved that impact not just on what data you decide to generate, but also how you look at it and write about it later on. You don’t want to offend these colleagues, or uncover issues that might make them look bad or make them uncomfortable. BUT, you also have a responsibility, ethically, to protect not just yourself but also the research you are doing. Uncomfortable data can also be very important data to talk about – it can push and stretch us in our learning and growth even as it discomforts us. But this is not an easy issue, and it has to be thought about carefully when we decide what to look at, how and why.

These kinds of considerations, as one example, definitely influence a researcher’s approach to generating, reading and analysing their data, and it can help to have a term for this part of the research process that captures at least some of the complexity of doing empirical work. For now, I am going to go with others on this and use ‘generating’. Collecting and gathering are too ‘thin’ and capture very little if any of the values, interests, gazes and so forth that researchers and research participants can bring to bear on a study. Making and creating – well, these are synonyms for generating, but at the moment my thinking is that they make it sound too much like we are pulling the data out of nothing, and this is not the case either. The data is not there to be gathered up, nor is it completely absent prior to us doing the research. In generating data, we look at different sources – people, documents, situations – but we bring to bear our own vested interests, values, aims, questions, frameworks and gazes in order to make of what we see something different and hopefully a bit new. We exercise our agency as researchers, not just alone, but in relation to our data as well. Being aware of this, and making this a conscious rather than mechanical or instrumental ‘collection’ process can have a marked impact, for the better I think, on how ethically and responsibly we generate data, analyse it and write about down the line.

Fieldwork: custom, character and questions of ethics

I have been thinking about fieldwork a lot lately, and how to improve on what I did with it during my PhD because I am doing it all again, post-doctorally. I have started a new, connected research project which I will probably write about later on, and I am wondering if the way I am doing my fieldwork is the best way. I am not really doing anything too different yet, and I’m working in the same two departments although with different lecturers. This will probably be one of three posts thinking through different aspects of doing fieldwork, so I’d like to start with considering the question of ethics, and the ethical behaviour of researchers in ‘the field’.

Fieldwork is generally defined as ‘an investigation or search for material, data, etc, made in the field as opposed to the classroom, laboratory, or official headquarters’ (http://www.thefreedictionary.com/field+work).  I gather data in classrooms, and in conversations with lecturers, and from documents. This year I am also adding student voices to the mix. This may not fit this definition but for the sake of using one word instead of two, and because it tends to be a ‘catch-all’ term for this phase of a research project, I am going to use the term fieldwork to talk about the phase of gathering different kinds of data from different sources, even is a classroom or lecture hall.

The lecturers I worked with last year and the ones I am working with this year are colleagues. I know them and they know me, and we respect and like one another professionally and personally as well. So it is very important that we can work together well, and that I am ethical in the way I behave as a researcher because that will affect the way I am received as a colleague. There are several benefits to working like this: access to data is much less complicated – I have been welcomed with open minds and arms, and they are interested in what I am doing; I can ask questions after class and even in class if I want to, so I feel like part of the environment rather than a detached outsider (more about this in another post perhaps); I am really enjoying this work a great deal because these departments are so interested and welcoming.

However, there are also drawbacks. The biggest, for me, stemmed quite specifically from the kind of data gathering I was (and am still) doing – what Paul Trowler calls doing research in your own ‘backyard’ and learning what Kevin Williams has called ‘guilty knowledge’. I work at the same university I gather my data in, and I do other kinds of work from time to time with the lecturers who are talking to me and letting me into their classrooms. So, I am not a detached outsider. I am part of this environment, and it is thus a challenge to try to be more objective about what I am seeing and thinking, and not get too emotionally involved with the courses or the lecturers and students and therefore end up skewing the representations of my data, or omitting important observations because they may not paint the lecturers or students in a good light.  Williams especially talks about this in his paper – he argues that doing research with colleagues in your own university, in a place in which you have invested part of yourself, is difficult because sometimes you learn things you are not sure you should disclose, or dig into deeper. This can leave you and your research in a tricky place, as your professional identity as a staff member can conflict with your identity as a researcher. Choices may have to be made, and this is where custom can clash with character.

Essentially, the literature on research ethics talks about ‘custom’ as being chiefly about the forms you fill in and the ethical protocols you agree to abide by. These are the standard ethical rules to live by in your field. ‘Character’, on the other hand, is to do with how you behave as a researcher when confronted with guilty or difficult knowledge or situations that present you with ethical dilemmas. This is an important distinction. I filled in forms, and got ethical clearance and promised, quite truthfully, to abide by the ethical rules laid down by my university. But when I got into the field, I was confronted by a couple of dilemmas that those forms and rules did not necessarily help me to solve. I had to call more in my character as a researcher, reflect very carefully on the dilemma, and speak to my participants openly about the problem yet without compromising myself or my research in that process. I had to rely on character, rather than on custom, to get me through and to keep the integrity of my research project intact.

This was not easy, but through this part of my fieldwork phase, I realised that while the rules and protocols are there for a reason and need to be observed diligently, there are also things they cannot account for. It is when these unexpected twists and turns arise that you need to call on your own character as a person and as a researcher. You need to cultivate relationships, as far as you can, with your participants that are open, so that when difficulties arise that include or affect them you can share these and reach an understanding, solution or compromise as needed. Share with them, if it’s helpful, pieces of what you are writing and get their feedback. Show them your classroom or interview transcripts, and ask for their input and whether they would like anything omitted. Discuss their requests for omissions or changes with them openly, especially if they may compromise your research. Talk about this in your methodology, so your reader knows what happened too.

It’s important to actually be ethical, and not just to say you will be, and it’s important to realise that things don’t always go according to plan in the field, so having an ethical and upfront character and approach to your research will stand you in good stead in case the unexpected is part of your journey too.