How to avoid being a mansplainer.

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You may be someone who means well, but is sometimes accused of mansplaining. Or maybe you suspect you might be mansplaining, because the people you have been talking to have been nodding without saying anything for the last few minutes and they start to look bored/distracted or there is a weird silence when you stop talking… sound familiar?

These are a few suggestions I’ve discussed with other colleagues when we think about what makes some conversations and collaborations more productive than others. Research, like so many other things, is an inherently creative process. Whenever the environment feels overly dominated by one voice or unproductively combative, ideas are lost or never make it into the discussion because contributors decide “it’s not worth trying to add” more ideas. I always notice which of my colleagues engages with me in a conversation rather than talking at me — and I am much more likely to collaborate with someone who engages with me like a teammate rather than their audience member.

First, a golden rule: ask questions. Before you assume anything, ask more questions with an open mind.

What does this look like in practice?

You can ask me what I study/do, then let me give you a full answer before you tell me about something semi-related you’ve read before. Ask me about the projects I have completed and maybe even my methodology, if you are curious. The best approach for this is to enter with an open mind, rather than an immediately critical one. This is a good time to learn about a different approach, rather than try to force my work into something you’ve already done or seen before.

Second guideline: Give me space to ask questions when I need to ask them. Do not assume I need an answer from you.

I am very likely aware of the challenges in my long term research work and methods. Researchers often need to work collaboratively — I run many of my ideas, methods, data, and results by my peers, my advisor, and other people in my field before I present them. Unless you are an expert or have experimented in similar ways yourself, it is not very likely that you’ll add to the conversation by simply listing my methods’ various pitfalls. I am also deeply aware of the context of my data and research areas. These do not need to be explained to me, but if I have questions because you know something about them too, I will ask them. Trust me to ask questions when I need to ask questions. There will be things I do not know well and I will do my best to admit them. Ideally, you will also admit your own gaps in your knowledge and skill sets. This is how we can grow together.

Third guideline: Approach this as a learning opportunity, a brainstorm, a conversation — NOT a presentation that you are making or a debate to be won.

This is an exciting opportunity to brainstorm together. Make it productive! Focus on what comes next! Now talk to me about other questions you are curious about that might be related and new methods opportunities that could be cool. I am excited to think about the future of my projects and now I am open to ideas and discussion of different opportunities/pitfalls of future projects. This feels really different from a debate or a presentation because you are building something with me — that means we should be talking and listening for similar amounts, and when you are listening, you should be really listening (not just thinking about the next thing you want to say).

All of these guidelines take practice implementing them if they are new to you. It might be worth asking some of your colleagues to give you a little signal if you’ve started to go on a monologue or ask them to interrupt you when you start explaining something they already know. Make a mental note of how often this happens and how to recognizing when it’s happening. It’s also really helpful practice to try doing some interviews where you are 100% a non-critical observer just trying to learn more about a person. It is possible to get better at this over time. I’ve seen it happen with my own research partners before. Good luck!

Ph.D. Candidate at Princeton (Labor, Technology, Law, and Informal Economies) | previously research + content at TED

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