Viewpoint: Why you should join an academic gang

academic gang

By InDecision Blog reporter and regular editorial contributor Troy Campbell

Question: How Do You Succeed in Academia?

To answer this all important question, let us start not with the truth, but with a myth. It is a myth that misguides so many students, and it is …

The Lonely Genius Myth


There is a myth in our field and that myth is “the lonely genius.”

The lonely genius is the researcher with the exact right research style, who reads narrowly but broadly, writes at least 90 minutes a day, balances work and exercise, is always strategic, knows exactly how to target journals, and above all else, does it alone. The myth goes: we should all strive to be just like the lonely genius and any deviation from this standard is wrong.

The Truth of the Lonely Genius

glass-case-of-emotionBeing lonely sucks and it is not productive.

The Hidden Real Answer


The real answer of how do you make it in academia, the source of the most variance in academic success, the holy grail of academic advice, is not a research style, and it is also not a certain work ethic, and it is certainly not that you should do it all alone.

The real answer is:  Academics succeed with the help and support of others.

People succeed in academia because they make friendships and connections with faculty, peers, and even research assistants. This is not “networking” but true “deep connections” where each partner cares about the success of the other and provides intellectual and emotional support.

In academia, you need to be tough, but you can’t be a lone wolf. Even the toughest of wolves usually can’t compete without a pack.

Recently, the importance of “others” has been greatly expressed at doctoral consortiums in the social sciences. Columbia University Professor Leonard Lee spoke about the role of senior faculty support for young faculty. University of Colorado at Boulder Professor Meg Campbell further argues this sentiment, stating that we too often neglect extended support networks. A recent study finds that even the most successful athletes are quick to mention the role of social support networks in their hall of fame induction speeches. And yes, even the great Anchorman Ron Burgundy admitted that he needed his news team.

On this website alone, we’ve documented many of the hidden ways colleaguesstudent peers, and mentors can benefit young academics.

The Method to the Madness

So if others are the answer, how can we starting succeeding with others?

#1 Never “Front”

front b

Professor Joey Hoegg of the University of British Columbia explains that in her first semester as a new professor she pretended that everything was going well with her research. Eventually, it became so obvious to a senior faculty member at the school that this was not the case. He kindly took it upon himself to mentor her and everything turned around.

No matter where we are in the process to tenure, many of those with tenure are here to help. Hoegg wasted months of her career because she was “fronting” with the very people who wanted to help her the most. Not everyone in academia wants to help you, but many do. So let those people help you.  

#2 Join a Gang

Screen Shot 2014-10-24 at 10.35.00 AM

Look at any successful professor. What do they have in common? As Northwestern University Profess Derek Rucker’s slyly expressed through a staged doctoral consortium: almost nothing. Some people are terrible at stats, writing, experimental design or public speaking but still make it.

The one similarity is they all join gangs, which is the best method to using the power of “others.”

These academics run with a crew that consistently publishes together or at least meets together. Sometimes a gang centers around a topic. Other times, it is just about a group of people who keep publishing together on many topics. Sometimes it’s a department, sometimes it’s a lab, sometimes it’s a cross-continental Skype-based collaboration, or sometimes it’s a larger field spanning movement (e.g. consider the recent movements and then sub movements in political psychology as different gangs).

To win this game (or war) of academia, you have to join a gang. This is the gang you see at every conference not just to catch up with but to push forward ideas with, who think like you and want to think about the same things. Professor Peter McGraw has noted that he never hung out with professors at conferences, he just made friends with peers who then become great colleagues. And Professor Dan Ariely notes that most of his collaborations started with friendship. Quality relationships make quality use of the power of others.

#3 Ask


So how does one join a gang or get help?

Ask. It may be the most cliché answer, but it is the right answer.

To get help and start research collaborations, you have to ask. Ask for your advisor to bring in other people on a project so you can start entering the larger world. Let the faculty know your struggles and let your friends or conference acquaintances know you’d love to talk about research. Go to all the sessions on a single topic and don’t just sit, but engage with people. Professor Fleura Bardhi also advises getting involved with your local community as another way to jumpstart your involvement.

Remember the first step to doing things not alone, is to show up to the party so very alone. You have to make the initiative, not just receive or rely on your advisors to “hook you in.” You will never make friends if you don’t show up to the party, ready to discuss.

The All-Important We

happy team

We succeed in academia when we can turn the question what should I do? into what should we do?

So find others, join a gang, and then you can start slaying it as a researcher. Whatever metaphor you like, a gang metaphor, a wolf pack metaphor, a Fellowship of the Ring metaphor, or an economy of scale metaphor; they are all true.

People spend so much time thinking about what to research and how to research it, but not enough time thinking about who to research with. Figuring out the latter almost always helps with the former.


How to advance science and look good in a talk

Many conference presentations have become more about impressing the audience than advancing science. While presenters should, of course, strive to be engaging, impressive, and proud of their work, they should also be more open about their limitations and not view their project as a lone watershed moment in science but as a piece in an ever-advancing timeline of inquiry. Here are some ways to have presentation that will not just look good but will also be good for the scientific enterprise.

#1 Have a true and guided discussion of the limitations.

Let’s be honest: there’s probably no chance that you’ve tested your theory in the absolute best way possible – funding and constraints almost always prevent this.

There’s also little chance that you’ve removed 100% of the potential confounds. If you have any doubts about this, just submit your manuscript to any journal club and the feedback you will receive will make it abundantly clear that there are at least six thousands potential confounds. Psychological research is imperfect—and as Anna Kirmani and Michelle Pham have recently argued, it is important we realize this.

So what does this mean for your conference presentations?

It means you need to take control over the discussion of your limitations. Maybe you are worried about a hidden ceiling effect in the Likert measure or an undetected mood effect; mention those things. Further, tell us how we as a field could better test your theory. Maybe it is with larger more diverse samples or maybe it is with different dependent variables.

#2 Have a true and guided discussion of the relevance of your findings.

When the first choice overload studies came out, the authors made it seem that lots of choice was almost always bad. Turns out that although choice overload does exist, the original idea as the author of The Paradox of Choice Barry Schwartz explains was overstated.

Instead of looking back at how awesome their choice overload work was, in their original presentations and papers the choice researchers should have looked forward and said to their audiences, here’s how we can test the breadth of this choice overload work. Rather than assume its ubiquity for a few studies, they should have been more humble.

Recently, my colleagues and I have tried to use a humble approach by starting many presentations with the statement: “Today our only goal is to have you leave here thinking: ‘Hey, this phenomenon happens sometimes, isn’t that interesting, and shouldn’t we explore it more?’”

#3 Don’t be a theoretical imperialist and always remember the motto: “Death to Dichotomy”

Many researchers seem to feel the need to explain why their theory explains everything. This can make one can look very good and lead to a type of prominence in one’s field and the popular press. Yet, rarely is one perspective as completely explanatory as it seems.

For instance in the field of motivated cognition, people often have dichotomous debates between the existence of a motivation explanation (e.g. self-deception) versus a completely non-motivational explanation (e.g. informational differences, self-presentation bias). Scientists often try to explain lab and complex real world phenomena within one psychological theory with nearly unqualified general claims.

This leads to a theory versus theory approach. It forms a “dichotomous” view of reality when as Michelle Pham argues, this is often far from the truth. The majority of the most interesting phenomena in real life are determined by multiple factors. For example, in the case of motivated cognition, there is a synthesis of factors in self-deception that can occur due to concerns over self-presentation.

Dichotomous type of thinking does not lead to our goal of optimally advancing science. Instead of pitting psychological mechanisms against each other in absolute terms, we should develop models that allow for a multiple psychological mechanisms. We should not ask does X mechanism explain this phenomenon better than Y mechanism? Instead we should ask, when do X and Y matter most when consider phenomenon Z?

A final consideration: Does all this humble limitation focus actually improve your presentation and make you look better?

As a young scholar, I am always so saddened when I attend talks by famous scholars or rising stars in academia only to see that they are biased toward the prominence of their theories. Their self-aggrandizing style can hurt them at least in some people’s eyes. Scientists appreciate when other scientists act like humble scientists, and yes – that is only a “usually,” not an “always,” but still, it’s worth playing the percentages.

We need to stop focusing on looking good and we to need to start focusing on doing what’s good for science. Arguably, doing the things that are good for science can also make you look good.

Outside The Matrix: Tiina Likki

Tiina LikkiDr Tiina Likki is a Senior Advisor at the Behavioural Insights Team in London where she focuses on labour market and welfare policy. Prior to joining the BIT, she completed a PhD in social psychology at the University of Lausanne where her research focused on public attitudes towards the welfare state in Europe. She also helped set up Tänk, a think tank that aims to introduce to an evidence-based, behavioural science approach to public policy in Finland.

Tell us about your work: how does decision making psychology fit in it? 

I’m a social psychologist by training and work for the Behavioural Insights Team (BIT). BIT is a former UK government unit, now a social purpose company that applies behavioural science to policy-making. My current focus is on employment and health and, therefore, I spend a lot of time looking at how the government could better support people getting back to work, or to stay in their current jobs. As a social purpose company, we cover a range of policy areas including education, financial and consumer behaviour, crime, international development, and energy and sustainability. Helping people and societies achieve good outcomes in these areas often boils down to supporting people in ways that allow them to make the right decisions.

Why you decided to go into industry instead of continuing in academia?

Towards the end of my PhD, I became increasingly passionate about the popularisation of science and evidence-based policy. I felt that findings from social psychology and behavioural science were incredibly important and that they should be more widely available for everyone to use. Some academics such as Richard Thaler and Carol Dweck do a great job of sharing their findings through accessible books, but many never make it from journal pages to policy-makers’ reading lists. In my current capacity, I am able to share and apply this vast scientific knowledge to deal with issues that affect large parts of the population. At BIT I have the benefit of being able to run randomized controlled trials and maintain close ties with academics, so I feel like I’m getting the best of both worlds.

What do you enjoy the most in your current role?

I enjoy how the role requires me to look at things from many different perspectives – those of the user, the client, the academic and the civil servant. This requires developing different skillsets in parallel, which can be challenging, but also very rewarding. I get incredibly excited when I get to apply the latest evidence to real issues. For example, I have been reading a lot on mental contrasting and implementation intentions which describe how to set effective goals, maintain the motivation to pursue them, and ensure you take the necessary steps to achieve your goal. I have been using this literature to develop coaching methods for people who are unemployed. I recently came across an article on the same methods in the Harvard Business Review. It is fascinating that the same theories can be applied to both jobseekers who have been out of work for a long time, and to high-level professionals looking to advance in their careers.

Do you see any challenges to the wider adoption of decision making psychology in your field?

I feel that there is an increasing openness among policy-makers globally to make behaviourally informed policy. The huge interest created by the recent BX2015 conference was a really positive sign. In the UK, having the support of past and present senior civil servants, such as Jeremy Heywood and Gus O’Donnell, has really helped a wider audience to see the value in behavioural insights. In my experience there is a real interest among civil servants to learn more, and the number of senior decision makers who have read books like Thinking Fast and Slow and Nudge has grown steadily.

How do you see the relationship between academic researchers and practitioners?

This is a relationship where everyone stands to win from engaging genuinely with each other. Practitioners can gain some truly useful tools and ideas, as well as support in evaluation, while academics can gain an understanding of where their research will have the biggest demand and impact. There is certainly room for more academic institutions to run workshops inviting representatives from policy and industry to share their challenges. Similarly, students could learn a great deal from hands on projects that allow them to apply the behavioural theories they have learned.

What advice would you give to young researchers who might be interested in a career in your field?

If you are about to start academic work in this area (as a student or researcher), see if there are ways to partner with another organisation for field work or results sharing. This will give you a taste of running more applied projects and will help determine whether you enjoy it or whether you prefer to stay in a more traditional academic setting. If you enjoy the experience and decide to move into industry or policy, your applied research experience will give you a strong head start.

BIT profile | LinkedIn

Viewpoint: Three steps forward – a research agenda for behavioural change

three steps forward 2Alongside the blog reboot, we also have a new contributor, Tom Wein, who is the founding partner of Aware International, a social enterprise offering behavioural science for international development. Tom will be writing about the practice of applying behavioural science. 

Behavioural change has come a long way fast. In recent years, we have developed a far more fine-grained understanding of different behaviours in different contexts, and of the psychological processes behind them. We have a huge list of revealed heuristics and biases. We have too a healthy range of well-evidenced models for grouping and prioritising factors in behaviour, in relatively parsimonious fashion. We have begun (though there is much work to do) to think about how to consistently and transparently link our understanding of a behaviour to recommended interventions to change that behaviour. Neuroscientists and evolutionary psychologists are enthusiastically attacking the problem of where these psychological processes might come from, and work has begun on the effort to validate and investigate findings across cultures.

Of course there is vastly more to do in all these areas. For instance, there are new contexts to examine (the field remains dominated by health and financial behaviours) and our models need further refinement. Doubtless there are new heuristics and biases to uncover too. Yet these are areas that are receiving plenty of researchers attention; there are a number of crucial topics beyond this that remain under-examined.

This piece outlines three interwoven lines of work that seem particularly pressing. These are:

  1. linking linear behaviour change with our understanding of complex systems;
  2. developing a good basis for selecting behaviours to change; and
  3. understanding what we mean by behaviour in the first place.

Underlying all of this, a constant presence, is the need to check our work and replicate our findings.

Behaviour in complex systems

Those interested in behaviour change often contrast their work with that of traditional communications professionals. One of the key differences, they claim, is that behavioural change offers a much tighter focus on achieving a particular, observable change. Focus is surely a good thing, and many ordinary communications campaigns have hopelessly, unmeasurably broad aims – so broad that even if they could possibly succeed, one could never accurately judge their success. Yet the behaviouralist reaction to this can often lead to an overly linear approach. Too often, behavioural change posits a simple causal relationship between a specific campaign and an isolated behaviour. This is not how the world works.

Take, for example, preventing corruption: even the most well-researched, well-designed, tailored campaign to stop civil servants taking bribes will fail, if it fails to address the political and social pressures those civil servants are under from patronage networks below, corrupt benefactors above and co-conspirator peers. These groups have a strong interest in maintaining the corrupt behaviour, and will surely respond to our campaign. Or take obesity: our tightly-focused campaign to improve eating by these people now must be complemented by an understanding of the likely responses by peers and food companies, and by a consciousness of secondary and tertiary consequences.

Economists know quite a lot about the effect of incentives in complex systems; behavioural change advocates will need to match that expertise. A more focused approach to behaviour change brings benefits – but we need a much clearer and better evidenced picture of the downsides, of how and when targeted approaches succeed or fail, and of what the best response might be. Integrating the behavioural change approach with what we know of complex systems and how they come to change is an enormously important, daunting challenge. As a practical means of summarising how change happens in complex political contexts, international development’s Theory of Change approach (which allows actors to make their assumptions about social change explicit) might supply a starting point.

Choosing a behaviour

Most behaviour change approaches assume an objective has already been selected. The behaviours that will achieve that objective are then picked based on some combination of informal ethnography and political acceptability. (Good qualitative work happens sometimes, but it is certainly not the norm). Pragmatic flexibility must be preserved for behaviour change to thrive, but it is surely odd to devote so much detailed effort to determining how to change a behaviour, but so much less effort to figuring out if that is the most sensible thing to do. At the very least, some rules of thumb must be developed. What behaviours are to be candidates, and how are we to prioritise among them?

Just as we use search strategies for identifying the relevant papers, we need to establish search strategies for listing the behaviours we could seek to change in order to deliver a given policy objective. Then, we need to choose between the various options. How to do so? We need some criteria on which to judge behaviours, which at the very least makes assumptions explicit. As an initial set of considerations, those criteria should probably include the relevance of the behaviour to the eventual policy objective, the measurability of the outcome, an estimate of the likelihood of achieving the outcome and the ethics of altering this behaviour.

Without some more rigorous basis, we will design the interventions that suit us, or that suit the powerful. What is more, we will never have a justificatory basis for selecting a non-obvious route to change. This work will of course have to be linked to the understandings of systems called for above.

What is a behaviour?

If we are to list and choose between behaviours,  then we must know what a behaviour is; it is not clear that we currently do. Some suggested objectives are clearly broad and non-behavioural in nature. Similarly there is clearly a lower-bound – no one advocates three separate behaviour change campaigns to address reaching for the seatbelt, pulling the seatbelt down and securing it – but many cases are more marginal. Yet there is surely an ideal level of human action – not too vague, not too specific – at which change campaigns should aim. We just don’t know what that level is.

Without a good definition of the behaviour that we claim is at the centre of our approach, what response are we to give to those who suggest that we use a national communication campaign to ‘promote healthy lifestyles’, other than our general intuition that this is too vague to do much good? How are we to review the effectiveness of interventions, if we are less than certain what level of human action it is supposed to alter? This is more than a philosophical loose end; it is a gap at the heart of the enterprise. Much has already been written on the question of individuating actions in the philosophy and psychology of action literatures, but the behavioural change field has not examined or incorporated it.


We press always ahead into new areas, as we should. But our excitement at breaking new ground must be tempered by a realisation that much of our current knowledge is in doubt. Psychology is no science at all until it can replicate its findings, and sort the true from the merely promising. Too many of the most exciting discoveries of recent decades remain for now in epistemological limbo, neither false nor true, and we can only move forward with a solid base, and with healthy institutions that ensure that future results will receive the same scrutiny. This is not the place to propose how that should work, but any articulation of the discipline’s future that omits this duty is inadequate.

Practical, usable, explainable solutions in these three areas of research, plus the task of replication, would put us well on the road to an ‘end-to-end’ behavioural change approach, and begin to provide a transparent and explicit basis for decision-making at every level below that of high level policy and priority selection (which will properly remain the domain of consensus politics, not technocracy). Get to work!

You can learn more about Tom on our ‘Who we are’ page.

Tom is grateful to Dr. Chris Mills and the UCL Centre for Ethics and Law, who organised the November 2015 workshop on ‘Behavioural Public Policy: Theory and Practice’, at which many of these thoughts were crystallised. He is further grateful to both Chris and Dr. Jeroen Nieboer of LSE for their valuable comments on an initial draft.


Research Heroes: Dilip Soman

DS-Imag1Our first Research Hero of 2016 is Dilip Soman who is a professor at the Rotman School of Management and the Munk School at the University of Toronto, and the co-director of the university’s Behavioural Economics in Action research cluster. His research interests are in the area of decision-making, financial wellbeing, health behaviours and inclusive innovation. He is the author of several books, including the recently published The Last Mileworks with several governments, businesses and NGO’s in the area of behavioural insights and teaches an open online class (MOOC) on Behavioural Insights. In his past life, with degrees in engineering (B.E., Bombay), management (MBA, IIM) and the Behavioural Sciences (Ph.D., Chicago), he has worked in sales and advertising, consulted for several organizations, as well as taught at the University of Colorado and the Hong Kong University of Science and Technology. He currently serves as a senior policy advisor at the Privy Council Office of the Government of Canada.

I wish someone had told me at the beginning of my career…

….to spend a lot more time studying, understanding and developing (one’s own) philosophy of science. Many graduate students get thrown into a massive drift of domain specific knowledge right from the get go. And today, with all the pressures of publishing and getting started with your research early, there is even less of an emphasis on understanding the philosophy behind everything we do.

I most admire academically…

Richard Thaler. He hasn’t written as many papers as he could have over his career, but he taught us to try and make each paper important and meaningful. I could cheat and give you more names, but I’ll stop at the “most” admired.

The best research project I have worked on during my career…

The early work with John Gourville on transaction decoupling and payment depreciation. We were able to out some structure on the mental accounting model, and we had a lot of fun working on those papers. In one of the papers, we received data from a theater company on ticket sales and attendance. The data came in several shoeboxes stuffed with ticket stubs and paper order forms, and it too eons to get it into usable form. We did a number of other field studies (many which never made it to the paper) on ski slopes and at cricket games.

The worst research project I have worked on during my career…

Honestly, none! There were some I fleetingly felt I should never have done, but on deeper reflection I learnt even from the ones that didn’t work out for whatever reason!

The most amazing or memorable experience when I was doing research…

I won’t zero in on one, but doing fieldwork is always throws up the best moments. I did a bit of work in India a few years back on savings and healthcare behaviours. Many of the field studies didn’t work out given the sheer difficulty of achieving experimental control, but in a very small way we were able to change people’s lives and the happiness and gratitude they expressed more than made up for the unsuccessful studies!

The one story I always wanted to tell but never had a chance…

Sometime in 1999, I received a paper on Dual Processes in Cognition to review. I was suitably confused as to why I had received it and politely wrote to the editor saying that I didn’t feel I had the expertise to review it. Several years later, I found out that Steve Sloman had received a paper on mental accounting to review and was similarly suitably confused! Unlike me, he told me that he labored through and completed the review. These were the days of manual paper processing, and clearly someone had confused Sloman and Soman!

A research project I wish I had done…

In many situations in life – in decisions relating to health, family, careers – we spend a lot of time agonizing over choices; and we do so with the implicit belief that there is some “truth” underlying each option and our job as decision-makers is to find the correct option. I’m beginning to think that we tend to overweight the importance of “the choice.” There are also a series of post-choice decisions that we need to make that will help shape the outcome of the choice. You could, for instance, end up at an seemingly inferior job but do well and actually succeed in your career; you could seek and find happiness in a city that wasn’t your top choice for places to live in. So I guess the study I would like to run is one which tests whether choices we believe are important in life actually determine success and happiness. As you can see, a good study like this one would need more than money!

If I wasn’t doing this, I would be…

A physicist (I turned down admission to a Physics program to study Business) or a not-very-good cricket player.

The biggest challenge for our field in the next 10 years…

Both rigour and relevance. As a field I think we need to do a lot more to formalize our models – not necessarily through math – and test them more rigorously. A lot of researchers today answer conceptual questions about their model with empirical data. And we need to be relevant to someone – policy, welfare, business, consumers… anyone (this doesn’t simply mean being applied applied).

My advice for young researchers at the start of their career is…

Two – first, leave the comfort of the lab. There is a whole world outside that is overflowing with data. Even if you choose to primarily do lab experiments, go out and observe behaviour or identify phenomena that you can test. Second, you could do research that explains a lot of phenomena parsimoniously (but none perfectly), or you could do research that explains a phenomenon thoroughly (but doesn’t explain much else). While the world might push you towards the latter, I think the former lives longer and has much more of an impact!

Departmental profile | LinkedIn | Twitter


InDecision: rebooted

reboot indecision imageAfter a very long break, InDecision is finally coming back. 

For a number of reasons, the blog has been on a break for 18 months – partly because some of the team went on the job market and have focused on settling into their new jobs, and partly because I have focused on other parts of my life.

Now, once everyone’s lives have started to settle, the time has come to reboot InDecision.

While we will continue to bring you interviews with Research Heroes, those who have stepped Outside The (academic) Matrix and who are applying behavioural science In The Wild, we will also include new content for young researchers as well as new types of interviews later on in the year.

We are also curious about who our readers are: originally we thought that this blog would only be read by a small group of academics but over time the readership has expanded considerably so we would like to know just who is reading and what type of content you like the most, so in the near future we’ll be doing a short survey – when you see it, please take it.

This month we have the pleasure of featuring Professor Dilip Soman in our Research Hero series, Dr Tiina Likki from the UK’s Behavioural Insights Team and several posts tailored for young researchers by our regular contributor Dr Troy Campbell.