Research philosophy

I may not have gone where I intended to go, but I think I have ended up where I needed to be. (Douglas Adams)

In this research group we study the ethology of wild primates to gain a better understanding of their and our behaviour and cognition. To do so we draw on biology, socio-ecology, anthropology, psychology, philosophy, and more. We are holistic researchers.

Ethology is the process of ‘interviewing’ an animal in their own language (Tinbergen). Modern primate species are of interest to us in their own right. While they also provide a scaffold to understanding our own evolution, all species behavioural repertoires represent unique adaptations to their own particular niche. When we employ a uniquely anthropocentric perspective, we risk missing extraordinary species-specific capacities.

We are committed to applying what we learn to make the world a better place by supporting open inclusive scientific practice, sustainability, and diversity of thought and action.

General Guidelines

We are here to challenge ourselves to learn new ideas. We are curious.

Science is hard. But we create our culture and our culture is inclusive.

We are ambitious, but the definition of success is different for each of us.

If we don’t understand, we ask questions.

We take intellectual risks, but these leaps are taken from a solid research foundation. We do no harm. We do the reading, we do the groundwork, we double check, and we don’t take risks with our wellbeing, or the wellbeing of the environments and communities in which we work. We have a plan B.

We are lucky enough to work in an area where flexible working hours are the norm. These can be both a plus and difficult to manage. This sentence is stolen from Dr. Bastian Greshake’s email footer and forms the basis of our approach to flexible working: “While I may be sending this email outside my normal office hours, I have no expectation to receive a reply outside yours.”

We recognise and celebrate the work we do (that means data collection and crunching, paper and grant submissions, not just the work that works out).

Collegiality and Ethics

Everyone in this group is treated with respect and dignity and is able to work towards their individual aspirations.

We do not tolerate bigotry, abuse, or harassment. We value and support diversity in the workplace. Our ‘workplace’ includes the countries, communities, and field-sites we work in around the world. We make the work we do accessible to the broader community, and by drawing in diverse viewpoints to enhance mutual understanding of science, scientists, and the needs of our wider communities.

We do no harm. We acknowledge that all data collection has an impact on the species we work with, we seek to minimise this at all times. The well-being of the non-human individuals we work with always has priority over any data we collect. There will be times where this means accepting that some data, and some types of data, should not be collected.

Honesty is essential for correct science. We prefer to avoid mistakes, but mistakes happen for all of us. We take a deep breath, acknowledge them, and fix them. We are members of a wider scientific community; we both contribute to it, and draw upon it when needed. We communicate openly with our colleagues. We seek out frank but constructive and kind criticism. We return the favour.

We attend lab groups, journal clubs, and School seminars. Even where these are not directly in our area of interest they are an opportunity to learn new approaches and to participate in wider scientific discussion.

We support open science. We make our research data freely available whenever possible, to support future use in meta-analyses, reviews, and re-visitations of our work. We produce and share reproducible, re-usable data manipulation and analysis code, so people can understand our assumptions and workflows, and so future scientists can learn from our efforts without duplicating them. We seek out expertise from conventional and unconventional stakeholders in our work. We welcome feedback. We acknowledge contributions to our work, and cite the ideas of others – we don’t work in a vacuum.

We are members of a global society. Making our findings and data available to those outside of our scientific community, and in particular sharing knowledge with the communities in which we work is a key part of our job. We help people see what we do but respect the constraints others work under. There are many ways we can do this (stand-up comedy, skills sharing, science communication, art, or helping to maintain the group website…) we each find something we are comfortable with contributing.

Where ever possible, and including where it might cost us a little more money or time, we will make the most of any public transport or shared ride options available.

We recognise the responsibilities we have to the communities and wider eco-systems in which we work. Respect, conserve, share knowledge, reduce, reuse, recycle. Each action makes a difference, even the small ones.

Health, wellbeing, and work-life balance.

Health and personal difficulties, including mental illness, are common challenges people in academia face, as in many walks of life. Fieldwork can be remote and isolating, but we know this; sometimes it’s the challenges in non-fieldwork times that catch us out. It’s OK not to be OK. Engaging with the problem by discussing it with your peers, supervisors, or whoever you are comfortable talking to can go a long way towards getting help and accommodations. I don’t tend to initiate questions about personal topics, because I don’t want to intrude. But, if there are issues at home, or especially with health (mental or otherwise) that you would like to talk about, you are always free to talk to me. You can also ask me for advice on who to talk to about an issue that you don’t want to discuss in detail with me.

Find a work-life balance that lets you do your job to the level you aspire to and lets you be happy. Sometimes I work long & late; I do not expect you to. Sometimes I will work on a ‘weekend’ because it’s convenient, or because I’m on ‘a roll’ with a particular bit of writing or analysis, or because I’ve buggered up and I have a deadline on Monday I can’t otherwise make. I also sometimes take a sunny weekday off-work and go climb a bit of rock.

Fieldwork can be particularly tough for work-life balance. The species we work with don’t follow particular schedules, and doing the work we do can require very long days. Remember that, as well as data collection, the following things are also ‘work’: travel to and from your site, data downloading and processing, data and equipment maintenance, organising meetings and training sessions with field staff. That means that you should be taking time for yourself within your fieldwork that is not about these things – reading a non-work book, going for a run, napping, catching up with friends and family, whatever you need to do to get the balance right. It can feel sometimes like ‘missing’ a field-day means that we ‘lose’ data – it’s always the day you don’t go in that the amazing thing happens. My motto is this – ‘if it’s real it’s replicable’. If it only ever happens once then it might be an amazing experience, but it’s not the data that your scientific career is based on.

As tough as fieldwork can be, I find non-field time harder. Fieldwork often comes with a clear schedule, and that schedule doesn’t typically respect things like weekends, sensible-length work days. Coming home after several months of this can mean that adjusting to a different schedule is tough, particularly where there are so many things you can now choose to do with your time. Find a strategy that works for you, as well as the ‘big jobs’ make lists of small manageable tasks from week to week.

My obligations to everyone in the group:

  • I am deeply invested in helping you develop as a colleague, a scientist, and a part of our global community. My job is to help you achieve your career and life goals, to the best of my ability.
  • I also believe that the mentor-mentee relationship is reciprocal: you have experiences, skills and ideas that I do not, please share them! You have been hired not just because of your passions and eagerness for learning, but also because I believe you can bring your unique perspective to problems. I look forward to learning from you.
  • I will give you rapid feedback on ideas, manuscripts, etc. I strive provide direction, support, and resources wherever I can, and connect you to people that can help, when I can’t.
  • I write your recommendation letters for jobs and grants. You can take this for granted, but please give me enough advanced warning.
  • Conflict resolution is my job. If people aren’t getting along, or something is wrong, please talk to me.

Your obligations to me and our group.

  • I mainly ask that you bring a willingness to work and to think hard, to be open to changing and developing yourself, and a commitment to science, truth, and kindness. I will endeavour to bring the same things to our relationship. My ‘door’ is open (even if it’s through email, whatsapp, etc..).
  • Tell me when there is a problem, in the group, with your data, or with other people.
  • We’re often going to be working in different places around the world, we will agree a sensible check-in schedule. Stick to it, even if it’s just to say all is OK.
  • Be independent to the extent you can, teaching yourself skills, solving problems. If you come up against a problem you can always talk to me about it, but think it through first – what are our options, what might the next step be? Talk to me before you are in a rut.
  • Back up your data! (then back it up again somewhere else).
  • Write up Standard Operating Protocols (SOPs) for any commonly-used method so people who follow after you can replicate your methods exactly.
  • Be creative and productive. That often involves working efficiently, rather than super-long hours.
  • I encourage external collaboration and projects outside of your MSc, PhD, or postdoc. Talk to me about it first, though.

Authorship

  • You earn first authorship if you do most of the data collection, analysis, and writing.
  • You earn co-first-authorship if you and someone else either did equal amounts of work or each contributed most of different stages (collection, analysis, writing)
  • You earn co-authorship if you contribute essential effort to getting a substantial portion of the data, analysis on, or writing of the paper.
  • You earn co-authorship if you develop a methods contribution (e.g. a coding scheme or analysis) that you are happy to share, and have not yet published with yourself.
  • You must have read, understood, and approved any paper you are co-author on. We will make sure that everyone who has collected a substantial portion of the data has the opportunity to do so.

Your obligations to yourself

  • Be kind to yourself and others.
  • Attend seminars to learn what others are doing.
  • Practice asking questions. Write down > 1 question per seminar talk you see. If you don’t get a chance to ask the speaker, ask someone else in the group.
  • Read more than you think you can and outside of your immediate field, you are a scholar training to be a world expert on a specific topic, but that is best founded on holistic understanding.
  • Know the history of the ideas you are studying. This includes reading the old classic papers, and reading theory.
  • Keep a notebook with ideas, observations, and data.
  • Go to a conference & practice public speaking (even if it’s just to our group at first).
  • Make a twitter account, it’s the best way to extend your scientific network in our field. You can use this to find new papers, funding, and jobs. You can also use this to share and participate actively in the online community. Treat this as an extension of your working self, engage our community honestly and respectfully.
  • Read about scientific ethics, philosophy of science, and history of science.
  • Learn to keep a budget of research expenses.
  • Be kind to yourself and others (yes this is on the list twice. It’s the most important thing on there.)

The material in this guide is based heavily on the work of other PIs who were kind enough to share theirs publically – these include: Prof. Dan Bolnick; Dr. Kirstie Whitaker; Dr. Christie Bahlai @cbahlai; and Dr. Timothée Poisot.