The Wonderful World of Research

Over the summer a number of students visited on Nuffield Research Placements. These give sixth form students hands-on experience of a professional research environment through a placement in their summer holidays. Each of them worked with an academic on a mini research project. Here, three of them, working on a project looking at whether imagined contact in children would reduce prejudice towards  those with disabilities,  give a candid account of their experiences.

 

nuffield

From left: Forogh, Farzeen, Tashreefa

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One like me! Toying with the Doll Industry

Psychology @ Goldsmiths

JonesSianE

Dr. Sian Jones is a Teaching Fellow at Goldsmiths, Univdersity of London. Her research focuses on discrimination and prejudice among children and adults based on membership of a given group – and how friendships may be encouraged between children from different groups. Here, she looks at the Psychology behind the importance of representing disability in the toy industry. 

A lot of attention has focused on the toy industry of late, alongside changes in what is available and who it is targeted at. This ranges from the “let toys be toys” campaign pressuring for non-gendered marketing of products, to a plethora of companies like this one  marketing toys specifically designed to eradicate ethnic bias in dolls. This is coupled with changes to Barbie dolls both to make their shape more realistic, and to represent the careers that women may pursue.

Another avenue of change has been led by the #toylikeme campaign, with a recent petition garnering…

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Paper Review: Elementary School Children’s Reasoning About Social Class

Mistry, R. S., Brown, C. S., White, E. S., Chow, K. A. & Gillen-O’Neel, C. (2015), Elementary school children’s reasoning about social class: A mixed-methods study. Child Development. doi: 10.1111/cdev.12407

Against the backdrop, in the UK at least, of the imminent Labour Party leadership election, with supporters for the left-most candidate, Jeremy Corbyn, arguing for  “an economy which works for all, rejects austerity and places wealth and opportunity in the hands of the millions and not simply the millionaires”,  it seemed timely to look at this paper, examining as it does, children’s conceptions and understanding of social class.

The authors looked at 117 U.S. children’s (aged 10-12 years) placing of their family on a ten-rung ladder from people who have most money, to people who have least money, and were asked to tell researchers why they had placed themselves there. Additionally, children were asked what came to mind when talking about “rich, middle-class, and poor” people, and completed attitude scales of people in these categories. Further to this, their parents reported on the family income and subjective social class.

Children were asked to indicate what proportion of [rich] people would display each trait.

Children were asked to indicate what proportion of [rich] people would display each trait.

This was one of the first studies to test not simply the effects of social class (there are many of those studies out there) but to look at children’s understanding of social class. The authors expected that children would express the most negative beliefs about the poor as compared to the rich and middle class, and that childrens beliefs about the middle class (the modal class) would  be most positive.

The authors found that children’s understanding of their family’s income was informed by knowledge of material possessions, by lifestyle characteristics, and by comparison with others. Children rated “the poor” as having fewer positive attributes and more negative attributes than the “middle class”, and fewer positive attributes than “the rich”. Children who perceived that they were poor held less positive attitudes toward the poor than children who saw themselves as more middle class. But what does this mean for their understanding, exactly? 

Developmental Intergroup Theory

This study was framed within Developmental Intergroup Theory (DIT; Bigler & Liben, 2007) which, simply put,  proposes that children will categorize individuals according to salient perceptual dimensions and, seeing these dimensions used by adults in their classifications, develop hypotheses about why these dimensions are important for classification. What is it then that children pick up about social class categories?

Support was found here, for the tenets of DIT. Specifically, almost three quarters of the children in the current study rated their socioeconomic status as somewhere in the middle (i.e., ladder ratings between 5 and 7). Children seem to consider themselves part of the normative group. Furthermore, children were particularly focused on the concrete aspects of their social class, such as what they are (or are not) able to buy, what their house is like, and how their lifestyle differs from their friends’ (as opposed to noting more abstract features of having / not having money, such as security). 

As well as this, this paper goes beyond quantitative findings, and details careful qualitative exploration of why children understood their socio-economic status to be as they did. For example, one child said:

Well, I was thinking that at the top of the ladder, thats someone like J.K. Rowling, theyd just breally wealthy and the next one is like someone who is pretty wealthy and this one is [pointing to the next rung on the ladder], they probably live in a really big house and I think I might be here [points down] because I think my family has enough money to be comfortable and were happy and like we dont have a hard time, but its not likwe have a lot of money and its not like we live in a huge housewe live in a little house in [neighborhood] but its just nice and a nice size.  (p. 10). 

clearly indicating social comparison, and concreteness in describing their house size.

Who lives here?

Who lives here?

However, it may be that the tendency to identify as middle class is precisely because children imagined extreme examples of rich and poor (as above), and by default, somewhere between those extremes implies middle class. It would then be the nuances within “middle class” that would be interesting to look at – how do I compare with my friends? classmates? And how does that matter? 

And Beyond DIT

Further results showed that children did  associate the most negative attributes with the poor relative to the rich. They rated the poor as both higher in negative attributes and lower in positive attributes compared to the other social class group. When it came to their own group,, children who saw themselves as poorer rated the poor as having more negative attributes than the other more middle class children. This has echoes of the doll studies of the 1970s – where Black children preferred the White doll, rating the Black doll negatively. However, as the author’s note, in absolute terms, negative ratings weren’t that bad – only a “few” or “some” people had the negative traits.

Considering that children were asked to identify their socioeconomic status on the ladder rungs, it is also worth noting that no child rated themselves on the two lowest rungs of the ladder, and none self- identied as poor per sé. It is also worth mentioning that a measure of social identity with one’s social class was not taken. And, although the qualitative reports indicated some understanding of where money might come from, social mobility across social class was not measured either.

There is also the issue of this being a one-shot study, with a correlational design. That is, it is a snapshot of one school, at one point in time, with set diversity in terms of social class. Further research might usefully open up this diversity. For example, what happens in affluent areas, or private schools, where socioeconomic class is normativity high? Or between those who have or have not won scholarships for their study? How do perceptions of social class shape in-class interactions – or vice versa? And crucially, for a research program basing itself in the developmental intergroup framework – how do these perceptions develop? Only 10-12 year-olds were tested here: where did their ideas come from? And is the class system fair? Is it fixed?  Children were furnished with three class categories here: given the homogeneity in seeing themselves as middle class, what are the important  differences for them?

So, this was one of the first studies to look at children’s understanding of social class. It showed that children had awareness of their class, had differential attitudes towards other classes, and could explain how they came to perceive themselves as belonging to a given class. And, as with the best of research, there is now a multitude of questions remaining. What about “social identity”? How does age play a role here? How do children understand the notion of “social mobility” when it comes to SES? How does this interact with their moral reasoning about equality and justice? And then other, related questions spring to mind: how should we treat children from different classes? How do children’s perceptions relate to those of their parents? If you’ll excuse the pun, children’s reasoning about social class is indeed a rich area of research.

The Right Way To Do Statistics in Psychology

It’s that time of the year again. The time when undergraduate students in Psychology have collected their data, and are furiously trying to get it analyzed and written up, in time for their dissertation deadline.  It’s also the time of year when students tend to panic about the “right” way to analyze their data. But – as far as statistics go – there is no single right way to go about things. In fact, there is as much debate about doing statistics in Psychology as there is about psychological theories themselves – with whole journals dedicated to the topic. When it comes to dissertation stats, there is no single right way here, either…I explain.

I have one manipulated variable (call it Experimental Condition) and two continuous variables that I measured, Measure A, and Measure B. I want to know how Measure A and Experimental Condition interplay to influence Measure B. I have met all the assumptions for parametric data analysis. Although that research question is clearly defined, there are still several ways I could go about this.

Option 1

One way would be to perform a linear regression, entering Experimental Condition as a dummy variable and Measure A (centered about the mean) as predictors of my outcome, Measure B. If I found any interaction, I could analyse it using a simple slopes analysis. That would answer my research question.

Option 2

Equally viable, however, would be to run this analysis using ANOVA – because the maths underlying ANOVA and regression analyses are essentially the same. You can check this for yourself, by running the two analyses on the same variables: you will find that because both rely on what is called the General Linear Model the R squared value is the same for each. The distinction between the two in teaching terms is really just an historical artefact arising because ANOVA has been traditionally used for experimental designs and regression for correlational designs. It doesn’t have to be that way: whether the analysis you do make any sense depends on what you were trying to find out, more than anything.

Anyway – if I ran this analysis using ANOVA, there are two ways I could go about it. I could continue to treat measure A as a continuous variable and, in SPSS at least, force the program, via the syntax editor, to treat measure A as continuous but nevertheless a bona fide fixed factor, by adding it after the WITH sub-command:

UNIANOVA
Measure_B  BY Experimental Condition with Measure A_centred

Option 2a

I could, however, legitimately perform a median split on Measure A, creating a new variable where people are coded as either high A-scorers or low A-scorers. I would then enter Measure A _ split into the ANOVA alongside Experimental Condition, as above.

In either case, if I found an interaction between Measure A and Experimental Condition, I would analyse it using a simple effects analysis (to look at the effect of Experimental Condition at differing scores on Measure A).

The Right Way?

So – either ANOVAs or regression could be used for the above research question. Neither way is “wrong” although statisticians will point out the advantages and disadvantages to each approach. The classic disadvantage to median splits, for example, is that I would lose some of the variance provided in the variable scores (because I have changed a continuous variable to a dichotomous one).

Of course, that said, there are some things that we need to do, for any of the above options to be “right” before we run those tests. Here is a checklist, courtesy of Tabachnik and Fiddell (2007) – with the health warning that, the debate around statistics rages on, and these are guidelines – one high-profile  journal in Psychology decided earlier this week that reporting p values is inappropriate full-stop….

(1) Before you do anything, check for missing values and cases where weird stuff seems to be happening. Work out what is weird, and consider deletion of these cases, or checking against the questionnaires for human error in data entry.

(2) Check you meet the assumptions for the tests you want to do. See Tabachnik and Fiddell (2007) for myriad guidelines on what to do with the data, if you fail to meet an assumption.

jf16(3) This is not a fishing expedition. Define your research question clearly, and the type of test(s) you need to do to answer it with your data. Report what you find.

(4) If you do perform extra post-hoc tests, because something interesting has come up, don’t be afraid to admit to that. There are ways of statistically adjusting for the probability of finding significant results in such cases, and the important thing is being transparent about what we are doing as scientists, to allow effective evaluation of findings.

So – to sum this up, before you do anything with your data, look at it. Is it weird? Is it normal(ly distributed)? Can you use parametric statistics or not? Then, work out what research question you would like to answer, and what types of variable you now have. Based on this, choose among the options for answering that research question. All the time, remember to be transparent about the analysis and post-hoc tests that you are using. Just as one rationalizes the inclusion of different variables in your study in the Introduction, the Results section should give a rationale for what you have done with each variable, why, and what was found. Statistics in Psychology is about having a rationale, rather than a “right” answer.

 

 

 

 

Memory Monday: How are you today?

In the spirit of blogging culture, this morning, as Time to Talk Day 2015 approaches, I’d like to look back on a post I wrote this time last year, and ask what, if anything, has changed.

The original post may be found here.

elephant-animal-comfort

Well, I still have an open-door policy, and I still see a lot of students in my office with mental health related concerns. And students are still very welcome to come and raise concerns with me; nothing has changed there. Indeed, from where I am sitting, mental health concerns at university are still normative.

But the plural of anecdote….

….is not evidence. So what’s changed, evidence-wise in the past year? Time to check the oracle (read: internet) .

First thing I realize is that since February last year, there has been a huge upsurge of student voices talking about mental health at university. There are many pieces on the taboo that surrounds it, noting, as I did last year that according to the latest NUS survey (2013) that one in five students say that they have a mental health problem, but most stay silent about it. I can’t find evidence (but am happy to stand corrected) of more recent large-scale surveys of UK student mental health. But this year, there are  more stories about mental health at university out there, with The Guardian having an overwhelming response to a request for them – gathering over 200 pieces. True, that the plural of anecdote is not evidence….but maybe the time is ripe for a qualitative study of student experiences…..

It was also interesting to note, on two counts for me, that the conversation has expanded. It’s not just about student mental health anymore, but also about mental health in academia. There is evidence that academics, from PhD students to professors are struggling in high-stressage environments. Alongside this, is the hypothesis that there is a culture of acceptance around mental health problems in the academy: in other words, social psychology is at work – stressage is part of the job.

And recently published research by Ken Mavor and his colleagues (2014) supports this contention. That is, a strong social identity as a medical student is associated with high levels of social support and improved well-being  (strong social identity = good) , but this comes with a set of unhealthy group norms (for overwork et al.) that may have a greater influence on students with a strong social identity, encouraging them to do things that put their well-being at risk (strong social identity = risk for poor mental health). Maybe the same is true of PhD students, top professors, early career researchers…If we cast the latter as peripheral group members  to use Jolanda Jetten’s term (that is, those who are on the edge, and want to be in the group of “established academics”) there would be even more reason to suppose that ECRs would be at risk….there are another two hypotheses to test.

So, what has changed? It seems that people are more vocal these days – and that there are a lot of stories out there about mental health in academia. But, beyond small-scale experimental work, there is not much hard-core evidence on the nature of the problem. Now it has been driven out from underground, and now that the hypotheses are being put forward, the time for up-to-date full-scale research seems to have arrived.

How are you today? The Department of Psychology, Social Work and Public Health will be marking Time to Talk Day at 11am, this Thursday, 5th February. If you would like to join us, drop me an email.

Remember my open door policy, if you have been affected by any of the issues mentioned in this piece – and the variety of support offered by Brookes Well-Being. And you can always contact Samaritans or Nightline for help and support, too.

 

 

 

Much Ado About Academic Essay Writing

By virtue of a course on lecturing that I had to attend over the past year, I got to research a lot on student writing. And there’s a lot out there. I might speculate on why this is – the numerous email messages I get from students – and the high proportion of these that are about essay writing might give me a clue. In my research paper, one student gave advice for future students thus:

Make sure the content of your draft is as good as possible (i.e. read everything you want to before the draft deadline) so that the draft comments are focused on how to make the essay read better

What I sense in this, and in a lot of the messages I receive, is a fear of writing – of defining one’s own carefully thought-out arguments in the wrong way. Drafts seemed to be students’ safety net – the fear, about striking out alone. As an academic I have to do a lot of writing. And outside work, I write for pleasure, too. I love writing. It’s one of the best things about being an academic – getting paid to write (albeit indirectly).

Given the messages I’ve had from students about writing, I’d like to use this post to share some of their thoughts with you, and to look at ways of becoming a more confident writer. In a nutshell, of course.

Shut up and Write Group - Oxford Brookes Psychology

Shut up and Write Group – Oxford Brookes Psychology

1. Practise, practise, practise. Here’s a secret. If you’ve got the information straight in your mind, there’s no wrong way of writing it down. There are different ways of expressing said information, and some will be clearer than others. Play around with different ways of writing the same sentence. Find which you like. Find a voice that suits you. Don’t just write for academia either – write in your spare time; write something you’d like to read – write for no one else’s eyes but yours. The more experience you have with writing, the easier words will flow.

2. Don’t forget your reader[s]. Think about where they’re coming from, what they know already, and the  gaps you need to fill for them. In any piece of academic writing, always set out what terms mean for you, at the start. “Parenting” can mean different things to different disciplines – so can “depression” and “effective”. Tell your readers what they can expect the content of the piece to be – and afterwards, sum up what that content was. If the two descriptions don’t match – something needs revising.

3. Write [and plan] in paragraphs. Most academic pieces have word counts. So work out how many paragraphs you’ll need to write, and bound your writing into those paragraphs. Do not write outside of a paragraph. Ever. If you have six paragraphs,  you can make six points – so what are the six key points  that need to be made – what are the key things that need to be included to present your argument? Give each point a topic sentence, an exploration, and a take home-message.

4. Join a “shut up and write” group at your school or university (or start one). Sit down with a few friends in a coffee shop. Tell each other what you’re going to write, and then spend the next half hour writing, in silence. If you start with a clear goal, you’ll get more done in that time, than you thought you could (trust me). Sharing a little of what you write with the group, also prevents the isolating nightmare that academia can otherwise become from setting in, and gives you the chance to get and give encouragement.

5. Start now. Grab a note pad or start a blog and get going. You don’t have to start with writing your opening paragraph, or your take-home sentence. Start with what you like, what you know, work out what you don’t know, and write from there.

Happy Writing 🙂

Thanks to Tim Kourdi for this “shut up and write” location, and for chocolate cake to keep us going.

Video-gaming: A Pedant’s Response

My attention was caught a little while ago by a story on the BBC news website about the effects of video-gaming in children. The paper it refers to (Przybylski, 2014is published in Pediatrics. The paper reports secondary data analysis of a large ESRC survey, which divided children into four groups, according to their engagement with video games. One group played no games at all, one group played video games for less than an hour a day, one played for between one and three hours a day, and a fourth group played video games for over three hours a day.

vg

Findings showed that the second group reported better adjustment. That is, playing video games for less than an hour a day was linked to better life satisfaction scores, more pro-social behaviour, and fewer internalizing and externalizing problem behaviours, when compared to (a) playing no games and (b) playing for more than three hours a day. There were no significant differences between playing a moderate (1-3 hours) amount and the other groups.

Then I saw this tweet.

And it got me thinking about what we mean by the word “agree” when we’re referring to scientific findings. We could look at agreement in terms of scientific merit – the problems of relying entirely on self-report measures, and the correlational nature of the findings, might lead me to be hesitant in my agreement.

I could be pedantic at this point and disagree with the tweet, because there was no claim made about “producing” well-adjusted children. But the evidence, clearly and transparently reported in the paper, suggests that playing video games for under an hour a day was associated with better adjustment.

More interesting is considering invitation to agreement as based in the readers’ experiences. The tweet might be inviting  anecdote. So I want to use this tweet as an opportunity to talk about the difference between anecdote and evidence.

You might well hear a scientist say at some point:

 The plural of anecdote is not data

This is because anecdotes and experience are prone to bias. So is science – but it is arguably less biased than reliance on personal experience. This is why we do science, in fact – to try as far as possible to uncover truths about the world around us that are free of such bias. Research evidence, of which the above study is a good case in point, takes a representative sample (so here, 5 000 children) to answer its question.

Furthermore, these  5 000 children are each an anonymous row of data on a spreadsheet, not children with whom the researchers had any emotional connection or investment in their psychological adjustment. The argument of science is that taking such a sample gives a “truer” answer than asking one or two people about their experience.

And yes, it is true that some theories we have today in Psychology are rooted in the observations of one or two children. A famous example of this is of course Piaget (1959) and his careful records of his children growing up, showing us how children (might) develop. This, is a good example of empiricism – of observation. Piaget’s early records do not lay claim to cause and effect relationships. To determine the answer to why development happens, cue the scientific method (as argues Piaget himself, e.g., Piaget, 1932).

OK. Good so far. But what about qualitative research? Here, couldn’t each data set be summarized as a collection of anecdotes? Researchers are often explicitly interested in interviewees’ stories. And that counts as data. Well, yes – eventually. The data set is a set of organized “stories” that are then submitted to rigorous analysis by researchers, to build up a picture that is grounded in all the available data.

In sum, I heartily encourage students to question empirical papers: do the claims match up to the data that are being presented? What alternative explanations might there be for the findings? But questioning agreement from the point of view of your own experience, I do not encourage. This paper showed that spending less than an hour a day video-gaming was associated with good psychological adjustment among  5000 children. This result was statistically significant. Among those children, there will be several for whom this association is not true. Scientific methods allow us to draw conclusions based on a representative picture: more than an anecdote is needed, if you disagree with them.

Guest Post: The Write Stuff

Emily is a student in Year 13 at a local secondary school. This week, she spent time on a work experience placement, in the Department of Psychology, with me. Here, she reflects on her experiences. 

This week I have been helping out Siân with all of the general time consuming paperwork involved with being a researcher. I’ve met several other people who work at Oxford Brookes and have been able to get a real feel for what life as a researcher is like. I’ve transcribed, summarised and organised lots of data from feedback forms to interviews.

Monday:

I’d already met Siân when I’d visited Oxford Brookes for a Sixth Form Psychology conference earlier this year, it was there that Siân kindly offered to me some work experience (a really amazing opportunity for anyone who wants to study psychology). So I arrived at Oxford Brookes and made my way up to the Psychology Department. There Siân greeted me before presenting me with a large pile of A5 sheets of paper. In the tutorial room that was to be my office, Siân explained that she needed me to write up the results of the feedback sheets she’d handed out at her Friendship Workshops. Only slightly daunted by the masses of paper I sat down and got to work.

Several hours later and I finished the stack at number 400 and something (although I did start at 152). My next job was to work out the averages and summarise the data for Siân. However this would have to wait till tomorrow!

Tuesday

Sat down in front of the computer and set to work summarising and present the data I had collected yesterday for Siân. I impressed her with my highlighting skills (at least I think so). Siân’s next job for me was to write a leaflet for teachers who were going to have the friendship workshop done in their school. My first design was amazing. It had colour. It had style. It had some pictures.

It didn’t fit the university’s theme though.

So back to square seven whereby I copied and pasted all the information over to a university approved PowerPoint and made everything a kind of swampy green (there’s just no accounting for taste is there).

Lastly I wrote up some signs and certificates for Siân to use at her next workshop, as well as some short acting out scenarios for the kids to do (Siân had me conduct thorough research for these in the form of Charlie and Lola…).

Wednesday:

Woohoo! Lie In!

Well a short one anyways. Joined Siân and some of her colleagues for a Writing Retreat at a Hotel on Banbury Road. Spent the afternoon writing out three short stories about intra-friendship bullying (being very careful to stay ethnic friendly). It was a rather nice way to spend the day since it was for once actually pleasant weather (although possibly too sunny).

reteat2 retreat1

Thursday:

Transcriptions today. Namely eleven transcriptions of five year-olds playing with Playmobil. The research was all about how children feel about other children with disabilities (e.g. being in a wheelchair, and to see how they would use the Playmobil child in a wheelchair). Lots of long silences and pauses as I typed up the cute but inane musings of children. Secretly I felt that Lego pieces should have been used, I mean Playmobil doesn’t have a movie does it!

Siân showed me the mirror tracing device and I became suitably annoyed with the thing after ten minutes of failing to write a legible version of ‘Twinkle Twinkle little star’.

photo (22)

Finished writing out some more scenarios for Siân and added pictures.

Friday:

More transcriptions!

This time I was doing some work for Sarah who needed transcriptions of interviews conducted with Mini E test drivers. I now know all about how absolutely lovely T’s Mini E was. Sarah also talked to me about how Interpretative Phenomenological Analysis works so I shall be able to go back to school come September and wow my teacher with my inexhaustible knowledge (and large ego ;D).

I end the day by writing up this blog post for Siân and wincing at the photos she has sneakily taken of me!

Overall I have had an excellent week and am glad to finally have something decent to put in my personal statement!!! (Aside from reading about it there is almost nothing psychology-related to put in a personal statement thanks to all sorts of ethical guidelines).

And, as last year, I have no regrets about having taken on a work experience student. Emily did impress me with her initiative, the speed at which she picked up what I was after, and with her story-writing and design skills (which we did dovetail with the university’s requirements in the end) – and with her enthusiasm for Psychology as a discipline. She’s even coming back next week as a research participant. So I haven’t put her off 🙂 

Privileged Participation: EASP 2014 In Review

I have been abroad a fair bit for research this year. From 9-12th July this year, I attended the European Association of Social Psychology’s triennial conference in Amsterdam. This conference is always impressive. This year, it was bigger than ever before with over 1 400 delegates, from within and outwith Europe, and four full days of  twelve parallel sessions to choose from. Added to that were twice-daily poster sessions with over 100 posters apiece. I was privileged before I had started, to be going as not all submissions are accepted.

And I was glad that I went. The sheer range of sessions meant that there was always something of interest, if not of direct relevance to my research, on offer (and often it was the case that I had to choose between two or more directly relevant presentations). Social identity was writ large here, its applications spanning ever further –  from physical to mental health, sexual orientation to gender identity, emotion regulation to morality. That, as well as cutting edge looks at the usual suspects: collective action and intergroup contact to name but a few.

The meta-contact was, as ever invaluable. Great conversations were had over coffee, and at the conference dinner, there was ample opportunity to catch up with old colleagues, and to spark new connections.   

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Maybe the important thing here is that social psychology makes social identities visible. The privileges of being European, of being educated, of being from that social class, that ethnicity, along with the differences between being male or female, or transgender, heterosexual or LGBT+, are studied. Privilege is scientifically demonstrated. You cannot attend this conference and not leave with a sense of just how much social groups matter. And I was proud of the way in which social psychology is moving forwards to uncover identities that are often otherwise erased by society.

I was also pleased with the way in which the “green” agenda ran through the conference. Although, maybe this is where I need to make the conference team aware of their own privilege. A privilege of not having a physical disability. It was a green decision, no doubt, not to have conference bags. But, when you can only use one hand, some fore-warning of this would have been helpful.  We still had things to carry, after all. It would also have been useful to have coffee breaks every morning and afternoon – if only to give time for swapping between conference sites between sessions. The buildings of Amsterdam are gorgeous, but cobbled streets and bicycle jungles don’t make for the easiest of passages. I had to forget plans to change destination in the midst of sessions at the outset.

But this is a small point, for next time. Because I will be back next time. This is the social psychology conference not to miss.

Something Different: British Academy Social Exclusion Event Review

When delivering a children’s sermon recently, at the church I attend, I asked the question, ‘what does it mean to be friendly’? I had some idea (of course, as any teacher would) of the kind of answers I wanted. But the one I got was much better. One child told me being friendly is about understanding each other. ‘Yes,’ I said, ‘it is’. That key word there: understanding. It was in this spirit that Ayse Uskul and Lindsey Cameron organised this event at Kent University, on 6th June, to help us, as academics, speak to and understand policy makers and practitioners working on social exclusion.

I have never been to a meeting quite like this one. Each academic talk was followed by a commentary from a practitioner, offering more “grass roots” insights on the topic under consideration. The subjects spanned homophobia, ageism, mental health stigma, ethnicity and religion, engaging charities, and human rights organisations along the way. The accessibility of each presentation was impressive, as was the range of ideas noted at the panel discussion for ways in which we can move forwards in collaboration with each other. My only criticism is that I wish this latter discussion was given more “air-time”.

The aim of the event was undoubtedly met: we got to a better place of understanding one another. This got me thinking about research on social exclusion. It seems to me, at the moment, that the zeitgeist is for the contact hypothesis (e.g., Everett, 2013): that increased contact of various forms emphasises similarities between in group-out group members, making the other less scary, less different. A classic example of this is the so-called ‘Good Samaritan’ set-up studies, showing you’re more likely to come to the aid of in group than out group members: the more similar they are to you, the more likely you are to help. And it’s all about framing. If you support Manchester United, you’ll help a fellow ‘football supporter’ but not necessarily the same person, framed as an ‘Arsenal supporter’.

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Arsenal, Manchester United, or football supporter?

The interactions at this event got me thinking. What would happen if we went beyond emphasising intergroup similarity in research?  Everyone, everyone on Earth is different. There are songs that only you can sing, and conversations that only we can have, thanks to our myriad different experiences. Arguably, emphasising similarity reduces anxiety – it’s a necessary first step towards good relations –  but it also reduces the other’s humanity, their uniqueness. True understanding – that might only come through exploring – not by ignoring – differences. I wonder if oftentimes it is frustrating to be categorised in a certain way, and understood on that basis, however positively, especially if one belongs to a stigmatised group.

As a case in point, one speaker argued that the key difference between researcher and practitioner was the wearing of a tie: yet, a quick glance around the room revealed that this was not true of those present. And, while I wasn’t wearing a tie – there are other reasons, besides being a researcher,  for that. Indeed, one way forward that was discussed was a blurring of the lines between research and practice: true understanding of the ways forward at this event was borne out of exploring different aims and ways of working on a case-by-case basis, for researchers and practitioners.

Children see that being friendly is about understanding each other as individuals. Understanding and working with our differences was key to the success of this event. Maybe it is time to start applying this to the subject of our research, too.