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Into the WikiWorld

We all know Wikipedia. It’s almost impossible not to. 

For me, from a quick look-up of some fact to prove your point in an argument with friends, to double-checking a chemical structure for schoolwork, or to translate an obscure plant name I can’t think of the English name for; I’ve used Wikipedia consistently for well over a decade.

I’ve always known that Wikipedia was an online encyclopedia than anyone could edit. But I’d never even considered making an edit myself. Until one day in April, I received an email from 500 Women Scientists with the opportunity to attend a 6-week wiki-editing course. I’d already been working from home for a few weeks, with a considerably lower workload than usual, and – to be honest – not quite sure what to do with myself. So, I jumped on the opportunity to learn how to use the skills I already have — hey, I’m a scientist, I’ve been researching and writing and fact-checking for years! — to make Wikipedia a more inclusive place.

500 Women Scientists Wikipedia

About 10 women scientists gathered twice a week to learn how to edit Wikipedia with one main goal: putting more women on Wikipedia. I was saddened, but not surprised, to learn that of all the biographies on Wikipedia, only ~18% are about women. That percentage is ~16% if we only look at academic biographies, and it drops down to ~6.5% for female engineers, my own field. 

One potential reason for this is that a lot of Wikipedia editors are men. And – likely due to implicit bias – they write and edit articles about… other men. Even if the academic world is becoming more inclusive, this isn’t necessarily reflected on the online encyclopedia that everyone uses. 

And that’s a problem. Middle or high schoolers looking to learn more about notable figures in a field of interest and don’t find anyone who looks like them or comes from a similar background, might be turned off from pursuing studies in that field. So that’s where 500 Women Scientists Wikipedia comes in. By increasing representation of women in the academic biography category of Wikipedia, either by improving existing articles or writing new ones (for example through the Women in Red Wikiproject, which aims to write articles for “redlinked” women), we could improve representation and therefore make Wikipedia a better and more inclusive resource.

That all sounds good, but how?

Okay, so I knew I wanted to make Wikipedia more inclusive and I knew why, but that didn’t really help me with the “why.” Again, the fact that anyone can edit, doesn’t make me feel comfortable doing so right away! Luckily, the WikiEducators (if that’s the term, the course was organized by WikiEducation, and everything related to Wikipedia seems to have “Wiki” in it!), walked us through the core policies of Wikipedia, the do’s and don’t, and helped us through our first article edits.

Here is a list of things that stuck (but you can find all that is relevant to editing Wikipedia, on – you guessed it! – Wikipedia):

  • Statements on Wikipedia must be verifiable, which does not mean they are necessarily true. It just means there’s a sourceable body of work to back up the statement. This feels counterintuitive (shouldn’t we be writing “the truth”?) but it ensures there are reliable sources for everything on Wikipedia.
  • Wikipedia is not a place for opinion; articles should reflect a neutral point of view. I did like that this meant according to consensus, as opposed to the journalistic rule of equal time. For example, if 90% of climate researchers are in agreement that climate change is real, that viewpoint should be reflected for 90% of the article.
  • To have a biography on Wikipedia, a person must be notable. They have to meet criteria with regards to their academic achievements, prizes won, and impact to merit a presence on the online encyclopedia. In an academic culture where men are typically still more valued than women, this can be another factor for why there are so few biographies about women on Wikipedia.
  • The definition of Wikipedia as an “online encyclopedia” is incredibly broad, and apparently it’s easier to define what Wikipedia is not.
  • You can contribute to Wikipedia in several different ways, whether it’s writing new content, taking care of layout, correcting spelling and grammar, or making Wikipedia more aesthetically pleasing (just to name a few). 

Making the first edit

The first edit was scary! 

What if I made a mistake? What if I undid someone else’s edit and step on their toes? What if I did something that was inherently anti-Wikipedian?

Wikipedia’s mantra is “Be Bold” – make the change! The beauty of a massively open, crowd-sourced, and peer-reviewed platform is that almost everyone there is willing to help. It’s not seen as a faux-pas to make mistakes, and if you do, someone else will come along and fix it. Accidentally left in a typo? Someone will fix it. Mistakenly got a fact not quite right? Someone will fix it. Change someone’s important edits without noticing? They can come back and undo your change. And Wikipedia keeps track of all the changes in the “history” tab, making the whole editing process transparent and traceable.

Shia telling us to JUST DO IT!
Don’t let your dreams be dreams.

Working on the second article was considerably easier. Sure, there are still some really tricky things, like adding images or editing boxes, but overall making edits on Wikipedia is really easy!

“So fix it”

Another Wikipedia Mantra is “So fix it”: if you see something wrong, make it better. 

If you see a lack of representation, write a new article. Make existing articles better (I was surprised to learn about how some articles in the outer corners of Wikipedia are not great). Increasing representation is not just about getting more women biographies on Wikipedia. Black, Indigenous and People of Color academics are more underrepresented on Wikipedia than they are in academia (thanks to the #editWikipedia4BlackLives effort on June 10th and ongoing efforts from the people involved, that will hopefully change), and Pride month brings LBGTQA+ themed “editathons” (sessions where groups of people edit pages together). Wikipedia is a group effort, and together we can all make Wikipedia better: more representative, more inclusive, and more equitable. I myself plan to edit or write one article a week! 💪

Statistics from the course dashboard showing 10 articles created, 96 artickes edited, 1.12K total edits, 20 editors, 38.4K words added, 484 references added, and 99.6K view of edited articles.
Our cohort created 10 articles and edited 96 for a total of 1.12K edits! (retrieved July 3, 2020)

Find out more:

Learn more about WikiEducation, or get started on editing yourself with these open-source resources: https://outreachdashboard.wmflabs.org/training/editing-wikipedia


They gave me a certificate, so it’s official!

Attending a conference in your PJs

We can’t hold public gatherings anymore. So conferences and meetings are moving to virtual, which is… interesting?

Last month, I attended Science Talk 2020 (#SciTalk20), an annual conference about everything that’s science communication that’s usually held in Portland, OR. Not this year. This year is was on the internet.

I’ve never been – it’s passed on my radar the past few years, especially because Portland isn’t that far, but the combination of no longer being a student (so no student attendance fees) and the time/effort/cost of travelling (let’s face it, sometimes I’m just lazy), meant I never made the trip down.

This year however, there was no trip required, and I knew I’d probably have the time to attend (two afternoons), so why not? I love the scicomm community on Twitter and this could be a new way to connect.

Image
With no in-person attendees, the SciTalkOrg had to improvise to make a group picture. Where is Waldo challenge: can you find me?
(Image from SciTalkOrg’s twitter post)


You can read a blog post from one of the organizers on how the event went, but here are some of my thoughts as an attendee.

Conferencing at your own pace

I like attending conferences, but sometimes I’m just so tired at the end of the day from always being on. I enjoyed going to the #AAAS2020* meeting partially because I could just go home straight after. Sure, part of conferences – and I might argue perhaps one of the most important parts – is networking, those coffee breaks and meet-ups in bars and connecting over drinks, but attending a conference from your lazy desk chair has some perks:

  • You can get up and grab a coffee or go to the bathroom whenever you want without feeling like you’re bothering the speaker by getting up.
  • You can shamelessly doodle, knit, cross-stitch, … whatever type of “mindless” activity you like without feeling self-conscious. I particularly like this, because even during the most interesting of talks, I have the tendency to fall asleep, and doing something with my hands helps me stay awake.
  • You don’t have to dress up. Well, attend a conference in your PJs. Super comfy. You don’t even need to pack!
  • The catering is as amazing as you make it!

Running chat

One of my favorite things of the conference was the chat room, similar to the chat in a live-streamed YouTube video: constantly running in the background. It was pretty amazing to talk (mostly about the ongoing session but sure, there were also jokes) without bothering the speaker, at another conference, whispering in the back row would be frowned upon.

The chat room gave attendees the opportunity to network and provide resources directly. A lot of questions came up live, discussions got started, etc. It was like having a live tweet feed but a bit faster. In addition to the live-streamed speaker sessions, coffee breaks (with a chat open) gave people to opportunity to connect, discuss, and joke around.

Me during a flash talk, clearly in my leisure clothes. You can see the chat on the right.

So should all conferences go virtual?

Nah, of course not. There are aspects to in-person conferences that would be very difficult to implement virtually, such as networking events, (some) interactive workshops, and exhibition halls. But live-streaming can definitely make conferences more interactive, and accessible. Rethinking how conferences are organized can potentially increase their impact: can some conferences completely or partially be held online to reach more people? Do we really always have to travel halfway across the world for a meeting?

The organizers of #SciTalk20 showed that moving a meeting online in a matter of weeks is possible, with great speakers, wonderful attendees, and a disco party to end with.


* The annual meeting of the American Association for the Advancement of Science. You can read some of my session reports here, here, and here.

Friends of the Science Pod: Keys to successful (science) podcasting

Image of a microphone with the text "Science Podcasting"

Report on the session “Friends of the Science Pod: Broadcasting, outreach and professional networking” at the 2020 meeting of the Americal Association for the Advancement of Science (AAAS2020)

There’s no way around it: podcasting is the-new-thing. And for science communicators, podcasting sounds like a perfect way to participate in science communication, with the potential to reach audiences across borders and disciplines. During the annual meeting of the American Association for the Advancement of Science, Dr. Christopher Lynn (Department of Anthropology, University of Alabama), Dr. Sarah Myhre (Executive Director of the Rowan Institute Seattle; 500 Women Scientists), and Dr. Jo Weaver (Department of International Studies, University of Oregon) gathered together to talk about public scholarship, advancing your scientific career on the sound waves, and the ins and outs of podcasting. For science.

Public Scholarship: science is political

Dr. Sarah Myhre, cohost of “Warm Regards” – a podcast about the warming planet, started off the discussion by introducing the concept of being a public scholar. A researcher is embedded in society, and it is therefore impossible to be apolitical. Following the path paved by women of color, Sarah urged us to participate in public scholarship, rather than science communication.

While science communication is by no means unimportant – it brings science closer to communities by making researchers more personable, teaches academics to use clear language and stay clear of jargon, while conveying accurate information from a position of scientific authority – it has some limitations. For one, it lacks a thorough analysis of power. Science communication, in some forms, can be too much of a one-way street.

With public scholarship, however, being in conversation with the community is a central pillar. It takes into account that talking in public spaces makes the untrue assumption that anyone can engage, without taking into account that there is a higher barrier for people from marginalized communities. There are different ways to achieve public scholarship, such as organizing and hosting events, podcasting, writing Op-Eds, and moderating panels.

When creating media – such as a podcast or an OpEd – one should expect a deeply inequitable landscape and be actively countering the harm around you.

Sarah closed off her part of the session with an exercise for the audience: one person was to tell a story while the other actively listened but without showing any form of expression or acknowledgment. It was very uncanny not to receive any body language cues. Very useful though, for in a podcast, the audience is not there to provide direct feedback!

Why Podcast?

There are several reasons to start a podcast, even in the sea of the already so many existing ones! Dr. Christopher Lynn, who co-hosts a podcast on human biological variation in evolutionary, social, historical, and environmental context called “Sausage of Science,” started his talk by pointing out that “the world doesn’t need anything more than what it already has but they might like it anyway?”

Image of a microphone with a quote from Dr Christopher Lynn: " the world doesn't need anything more than what it already has, but they might like it anyway?"

A first valid reason to start a podcast is to propagate good science. But you might also want to promote yourself and gain recognition that can help enhance and advance your career. For grants, podcasting might count as a broader impact. Furthermore, through podcasting, you will build useful, transferable skills. Chris jokes: “Take the scientific approach: do everything once and then hire someone to do the things you don’t like.”

Dr. Jo Weaver, who hosts “Speaking of Race” – a podcast on racial science, chose the topic of her podcast after realizing that racial science was not really being taught anywhere. When they started their podcast, they brainstormed topics while asking the question: What do we think listeners want to hear? – and the rest followed. With 12 topics, the first mini-series was planned out. Because planning is crucial to maintain continuity throughout a podcast series. 

Jo went into some podcasting production details, including making the choice between doing an interview – or content-based podcast. Interviews require less preparation but are considerably harder to edit afterwards. Content-based podcasts are the opposite: there is more preparation required but once you follow a script, there is less editing work to do. And going for a hybrid basically requires a full production team. 

Advancing your career through podcasting

Jo continued by telling us her journey to getting her podcasting efforts more recognized at her institution. It is the general feeling that “If you’re on the tenure track, you need to be publishing.” From the university’s side, podcasting is not really considered a form of scholarship, so there’s no incentive to support it. It is one of those activities that institutions like to “brag” about when it’s successful, but not incentivize from the start.

However, there are several ways to get a podcast count towards an academic record. There are two main options:

  1. Turning content into a more traditional format, including an editing volume, theoretical (methodology) or research articles, “popular” academic writing.
  2. Convincing your institution that podcasting is a useful medium that counts as a teaching and research tool. 

Towards the second point, podcasts can be “peer-reviewed,” not only through their popularity rating but also by getting peers to review scripts or write letters of endorsement. To get your university to pay attention, it is helpful to find a supportive admin, lobby your institution as a group, and/or negotiate upfront in your contract.

The importance of having a brand

The session ended with Chris talking about networking and branding. He pointed out that he, as a tenured, white male, had an easy time doing things without fear and repercussion. Nevertheless, putting your research out in the public is a worthwhile endeavor. 

He paralleled his experience as a podcaster and a blogger. Through writing a lot (for a blog), you get a lot better at writing. Keep in mind that it is very likely that there will be more people reading your blog – or listening to your podcast – than reading your journal article! Blogs and podcasts allow you to build a platform. If you ever go to an editor to write a book, coming with a built-in audience will strengthen your case.

From a practical point of view, Chris advised us to think like a journalist: follow leads, use “strings” to create a narrative appeal, make sure you have an attention grabber (a “hook”) and know that both quality and quantity are important. High production quality, such as editing and sound for a podcast, will ensure that your audience sticks with you. And by putting out a high quantity of content, people will be more aware of you.

So – should you start a podcast?

That’s up to you! In any case, the session was informative, relaying tons of practical tips on how to be effective at podcasting – and thought-provoking – bringing up interesting discussions around public scholarship and non-traditional forms of publication. I would highly recommend to go listen to some podcasts, and see if you can find your niche!

Towards more inclusive scicomm

Report on the session “Building Community for Inclusive Public Engagement with Science” at the 2020 meeting of the Americal Association for the Advancement of Science (AAAS2020)

Many researchers and institutions participate in public engagement, including organizing public outreach activities and science communication events to help bridge the gap between science and the community. Unfortunately, too often parts of the community are not reached. Only people who are already interested in science come to a public talk, school outreach activities reach schools in more privileged areas, and the needs of communities are not taken into account when developing engagement projects.

Live sketch during the session by Alex Cagan

During the session on “Building Community for Inclusive Public Engagement with Science,” held on Thursday, February 13, 2020, during the American Association for the Advancement of Science’s (AAAS) annual meeting, this exact topic was addressed. The session was moderated by Sunshine Menezes (Metcalf Institute for Marine and Environmental Reporting, Kingston, RI), who introduced the speakers and outlined the scope of the panel: how we can be more intentional, reciprocal and reflexive in working towards more inclusive science communication. Those three words summarize the key traits of science communication:

  1. Intentionality: Are we actively thinking about who the target audience is and whether their identities and histories are being represented?
  2. Reciprocity: Are we learning from each other? Are the conversations based on what people bring rather than what they lack?
  3. Reflexivity: Are we evaluating our science communication strategies?

All three points came back in some form in three talks during the session.

Supporting Culture and Identity – Carrie Tzou

The first speaker, Carrie Tzou (University of Washington, Bothell, WA) spoke about supporting culture and identity in science education with equity-focused engagement. What educators should remember is that “when people enter into the practices of science and engineering, they do not leave their cultural worldviews at the door. Instruction that fails to recognize this reality can adversely affect engagement in science” [NRC, 2012, p. 284].

Learning is essentially cultural: what a person learns and how they learn depends on the community they are from. As a Western society, we often forget that for people of different cultures to learn our science, they also have to learn our culture!

Carrie Tzou outlined some strategies for learning that can be implemented to ensure that culture and identity are supported during learning. These include self-documentation, partnerships, and self-assessment. As an example of self-documentation, she told us about a project where students were given prompts, such as “how does your family use water?” to go take pictures in their daily life. This approach connects family and community to learning while broadening the definition of “what counts as science.”

By expanding what constitutes “science” – who does science, what counts as science, and in what contexts – personal identities and culture are supported in learning. Everyone can identify as a scientist and achieve scientific discoveries. As a final point, seeing science as part of justice movements offers new possibilities to understand the relationship between science, equity, and justice.

Seeing Yourself in the Data – Monica Ramirez

Monica Ramirez (University of Arizona, Tucson, AZ) showed us some participatory research projects she had worked on: co-created environmental health citizen science. She worked with “promatoras” – professionals with a similar cultural background as the person you’re trying to reach, helping to bridge the gap between “ivory tower researchers” and the community. In order to develop a successful citizen science project, she had the following tips:

  1. People want to participate if there is a community need, not just for the “advancement of knowledge.” Let the research question stem from the community, as solving a community-identified problem will contribute highly to the motivation of participants.
  2. Build meaningful relationships, by implementing personal support structures and peer education models (cfr. promatoras).
  3. Consider that participants might have limited time and/or access to technology, and incorporate this in the study design.

Equity Oriented Practice in Pre- and Early Career SciComm Professionals – Rabiah Mayas

Finally, Rabiah Mayas from the Museum of Science and Industry (MSI, Chicago, IL) gave a museum-perspective to creating inclusive scicomm. At the MSI, there is a training program for STEM graduate students who want to get into science communication. 

The program structure is inspired by traditional teaching education: initial academic preparation, supported practical experience in the classroom, and finally a lead educator position. In the scicomm space, this looks like training in best practices and K-12 teaching, as well as improvisation exercises. Participants are then allowed to try out their newly learned skills in the museum, allowing space to fail – because you only get good by failing! 

Conclusions:

While the world of STEM and scicomm is looking more and more diverse, we still have a long way to go. By building comfort around the language of inclusivity, creating spaces where it’s safe to have these “uncomfortable” discussions, stay aware of our personal identity while pursuing science, we can move towards more inclusivity and diversity. The three speakers of the session have definitely shown it can be done. 


Recommended reading:

Informal Science’s toolkit for science engagement professionals: https://www.informalscience.org/broadening-perspectives

Perspective article on a critical approach to science communication: https://www.frontiersin.org/articles/10.3389/fcomm.2020.00002/full

Engaging diverse citizen scientists: https://ui.adsabs.harvard.edu/abs/2018AGUFMNH43B1036B/abstract

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Make ’em Laugh

Report on the session “Make ’em Laugh: Science Comedy to Ignite Curiosity and Increase Self-confidence” organized by the Marie Curie Alumni Association at the 2020 meeting of the Americal Association for the Advancement of Science (AAAS2020)

Science is the pursuit of knowledge. But what is the point of research if this knowledge is not communicated to others? Comedy is one way to connect people, and it could be the key to bridge the science community with a society that is often susceptible to fake news and clickbait. 

At the annual meeting of AAAS, which took place from February 13–16, 2020 in Seattle, we organized a workshop to learn how to make people laugh with, and sometimes at, science. The session was organized by Valentina Ferro (Vice-Chair of the MCAA) and Valerie Bentivegna (Chair of the MCAA Communication Workgroup) and was facilitated by Adam Ruben (American Association for the Advancement of Science, Washington, DC) and Matthew Murtha (MCAA). 

Here are some of the take-home messages.

Comedy — the “rules”

Comedy, like many forms of entertainment, has some formulas that are guaranteed to work. Okay, I’m lying here. But there are some general rules that seem to help when working on a joke.

One format is “the list of three.” Lists of three are quite common in storytelling, and in comedy, this can be by surprising the audience on the third item with a twist. Let’s take the example from The Dick Van Dyke Show

“Can I get you anything? Cup of coffee? Doughnut? Toupee?” 

A cup of coffee is an ordinary thing to offer someone, and so is a donut. But it’s the third element that takes the audience by surprise and makes them laugh. The element of surprise is the other big part of comedy: keep the audience on their feet.

On the other hand, being too formulaic or too predictive can work against you. It might be better to just be silly, remember to have fun, and break the rules if they don’t work for you!

Bring comedy into your “boring” science presentations

I’m not saying science presentations are always boring, but let’s be honest, often they are. Bringing in some comedy into your science can be a way to lighten things up, but you might want to be careful when you’re early in your career. A close-to-pension, established, tenured scientist with nothing to prove can easily add humor into their talks without sounding unprofessional, but, as an early career scientist, you don’t want the humor to undermine your scientific message.

However, there are some tools from stand-up comedy that can help with your science talk:

  1. A microphone is not a wand. Don’t wave it around like you expect a Patronus to come out of it. Microphones work best when they are held an inch from your mouth, and you can help anchor it by placing your thumb on your chin or directly putting the mic on your chin. On a microphone note: use it! Don’t think the back of the room can hear you if you “project your voice,” not to mention that there might be some hard of hearing people that rely on you speaking through the microphone.
  2. Practice. Practice. Practice. You can be nervous to speak in front of a room full of people, but you should not be nervous about forgetting what you’re going to say.
  3. Communicate and connect with your audience. A good way to do this is by going into a talk with the motivation that you have something fascinating to tell, not because you have to.
  4. Use your slides wisely. Mostly images, bullet points for the rest. There are plenty of online resources to help you create amazingly effective (or effectively amazing) slides, find one that works for you!
  5. Constantly be thinking about what the room is thinking. Don’t be the last person to know something odd happening in the room. If something falls, or your projection is cutting out, or anything else is happening that the audience can’t help but miss, don’t ignore it.

So how can you put some humor in your science talk without overdoing it? Use the element of surprise: an unexpected funny photo or meme could get you some laughs without distracting from your data.

One final point

The best advice anyone can ever give is to be likable. Be authentic and relatable. And if you do want to go into comedy, just do it. Often. Go to open mics and try out your stuff. You will bomb sometimes, but it’s by failing that you’ll get better!


Want the learn more about #ScienceComedy? Depending on where you live, there are plenty of opportunities to work on your stand-up skills or just learn how to implement comedy into your science! Some examples are:


This post was originally published on the Marie Curie Alumni Association Medium Page.

Geek vs Nerd

No, this is not an epic battle. It’s a question that has been bugging me for the past week or two:

What is the difference between a geek and a nerd?

According to Big Think: ‘the words “nerd” and “geek” are often used interchangeably, as if they mean the same thing. They actually don’t: geek – An enthusiast of a particular topic or field. … nerd – A studious intellectual, although again of a particular topic or field.’

But then, “Harry Potter Nerd” sounds a lot better than “Harry Potter Geek,” and I’d like to know which one I am!

And then there was a website claiming that geeks are “socially adapted” nerds. Which I don’t really like as an explanation so I’m ignoring it.

So I asked my friends, and I asked twitter, and I was none the wiser. It seemed that about 50% of the people I know adhere to the description from Big Think above: nerds are the more “academic” of the two. The other half of my friends claim it’s exactly the opposite! Tech geeks, all of them!

A fellow nerd comedian (self-described) said that he uses them interchangeably, “Mainly because that’s how I was described in grade school. Nerd. Geek didn’t show up for me until college.”

Another interpretation was given by David Ashlin on Twitter: “Going by the, admittedly apocryphal, etymology that GEEK=General Electrical Engineering Knowledge, I always differentiated it by theoretical vs practical, as in nerds know things while geeks know how to do things.” What a nerd.

Another source used twitter data to differentiate the two, and created a graph with words commonly associated with “geeky” and “nerdy.” Apparently technology and comic books follow under the geek name while science pursuits, books, and education are more for nerds.

Geek vs Nerd

He summarizes: In broad strokes, it seems to me that geeky words are more about stuff (e.g., “#stuff”), while nerdy words are more about ideas (e.g., “hypothesis”). Geeks are fans, and fans collect stuff; nerds are practitioners, and practitioners play with ideas. Of course, geeks can collect ideas and nerds play with stuff, too. Plus, they aren’t two distinct personalities as much as different aspects of personality. Generally, the data seem to affirm my thinking.

I still don’t really know the answer. I consider myself both, depending on the situation but don’t ask me what exactly the differentiating situations are…


What do you think? What is the difference between a geek and a nerd? Share your view in the comments or on the original post on twitter.

Building confidence through comedy

A few months ago, I invited the wonderful Kyle Marian to Seattle to give a comedy workshop at GeekGirlCon.

Within 90 minutes, I saw a group of people going from being complete strangers to co-writers, participants going from hesitant to join the activities to laughing, and teenagers going from shy and reserved to stepping up on a stage to talk for 3 minutes; it was amazing to see community and confidence grow in such a short time.

What Kyle did extremely well during this workshop, in my opinion, was create a safe space for people to mess up – which essentially is crucial for building confidence.

Creating a safe space to fail

When you watch a comedy special, it looks so easy. The stand-up comedian moves smoothly between storytelling and jokes, seamlessly adding in crowd work, impeccably times their silences and their words to create space for laughs.

What you don’t see is all the work that went behind it, from jotting down random ideas in a notebook to having jokes fall flat at open mics. Comedy is hard work, and part of that hard work is being okay with things going wrong once in a while.

What I’ve found very useful, from my own experience as well as witnessing the GeekGirlCon workshop, is having a safe space to fail. A space where you don’t have to feel scared to voice out that random idea that you think won’t work, a space with such a supportive audience that by just forgetting what you were going to say, you’ll get an encouraging clap or laugh.

In the workshop, this is what Kyle had created: if an idea didn’t quite work, it wasn’t the end of the world but other participants would help to find a way to make the joke work, add an extra quip, add repetition (three is the charm), all while being super-supportive.

Comedy for Confidence

The first time I stood on a stage for stand-up, I did so through BrightClub Dundee. Two weeks earlier, I had gone through their training – a professional comedian taught us the ins and outs of comedy: how to write jokes but also how to hold the mic like a “real comedian.” I thought I’d just attend the training and maybe be a better presenter.

But after the training, I had an idea for a set and voila, there I was, on a stage, strumming Bruno the Blue Ukelele, adrenaline rushing through my veins.

It’s terrifying and exhilarating. Ask any comedian, they probably still get nervous before getting on a stage, no matter how long they’ve been doing this. But in another way, it really builds confidence. Standing there in front of 10, 30, 50 or 100 people, and getting that first laugh, you feel like you can take on anything.

And it’s even more of a confidence-boost to feel like you’re empowering others.

Geeky Comedy Seattle

So, I started this thing. I wanted to create a space for alternative, geeky, comedy (because that’s what I do) in a city that is, inherently alternative and geeky (Take that, Portland!)

Enter Geeky Comedy Seattle. It’s still early days, but if you want to come to a fail-safe place (as in, it’s a safe place to fail!), you can join us on February 1st month for a workshop and/or open mic, or come see the next show.


Enough with the shameless self-promotion.

Science of SciFi

Science of Scifi in computer-tech letters

Could we bring dinosaurs back to life? Will we ever make contact with aliens? Will robots take over the world?

With these questions in mind, 6 scientists and I-didn’t-really-count-how-many audience members gathered together for the panel The Science of SciFi, at this year’s GeekGirlCon – a celebration of geekiness in all its glory!

The panel consisted of local researchers from Seattle 500 women scientists:

  • Dr. Daniela Huppenkothen, who studies black holes and asteroids using modern statistical tools and machine learning methods;
  • Dr. Kim Bott, who studies alien life scientifically (yes, that’s a real thing and it’s called astrobiology);
  • Dr. Meredith Rawls, who writes software to handle terabytes of nightly data from the Large Synoptic Survey Telescope, which will ultimately become the highest-resolution movie of the night sky ever made;
  • Dr. Jeanna Wheeler, who works with mice and nematode models to understand diseases like Alzheimer’s and ALS; and
  • Dr. Jenn Huff, who as an archaeologist focuses on questions like “what can technology we invented and adopted in the past tell us about how we relate to technology now and in the future?”

Guided by questions from the audience, we explored the links between scientific research and science fiction, looking at what advances are being made in fields portrayed in SciFi media, discussing fictional and real research, and what lessons each can learn from the successes and failures in the other.

Here are some of the take-home messages I’d like to share.*

Science fiction makes scientists

One thing that was immediately clear was how science fiction had influenced the panelists in their life. By seeing positive female role models in their favorite science fiction shows and movies – just think Samantha Carter from SG-1, Ellie Sattler in Jurassic Park, Ellie Alloway in Contact, and numerous female characters in the Star Trek franchise, – they had someone to look up to and aspire to be like.

Seeing female characters who were both physically and intellectually adventurous, who were tough and smart, who were well-rounded and passionate, showed the women on the panel, and many female scientists, that they too could be a scientist.

There are several studies showing that having representation matters. If all you ever see is people who are not like you doing a thing, you’ll be less inclined to do that thing. If we can create positive role models, show that STEM professionals come in all stripes, we’ll create a more diverse and exciting research environment.

Response to a Discovery’s very non-diverse promo video showing that – even if it’s not a full representation of everyone in science – #scienceisforeveryone.

… but we can still do better!

Despite there being quite a few inspirational science fiction scientists, the overall depiction of scientists and the science they do in movies, series, and books is often – well – inaccurate.

Scientists are not (always) super smart, geeky people who sit around in a lab coat for no apparent reason and solve the science thing within an hour. Oh, not to mention being a very attractive, mid-twenty-year-old with 4 PhDs. Or a software developer spending 30 seconds to find the bug in their software. Because that sounds totally possible, and I know some software engineers.

Little known fact: when you get a Ph.D., you get a bonus second Ph.D. on calling people on their shit. From: Rampage (2018)

Let’s also not forget the idea that for scientists in fiction, science is often their whole life. Showing that being super passionate about science, and science only, is the only way to be a good scientist is not a message we want to share. Could we have more well-rounded, realistic, scientists in fiction, please? With hobbies and all?

And while we’re at it, let’s get some science straight: mutated does not equal evil; mutation is the substrate of all the beautiful diversity we have everywhere!

Special acknowledgment to shows that do show good representations of scientists. The Martian depicted a scientist pretty well. And not to pull favorites, but The Expanse has a pretty good portrayal of gravity systems affecting how a body develops. Not to mention that long-haired people in space definitely tie up their hair and that there is space in space – and it takes time, fuel, and pulling Gs to travel through it.

Accuracy versus story

This brings up another question: does science fiction need to be scientifically accurate?

Sometimes science fiction is fun because of the story or the characters. Who doesn’t love some good space magic?

The consensus seemed to be that, as long as things are consistent with the story, and that the movie/series/book isn’t claiming to be super scientifically accurate while totally not actually being so, accuracy is not the most important thing.

Two characters in space speaking by touching helmets
“In space, no one can hear you scream.” In The Expanse, the solution is to hold helmets together so the vibrations can pass to the other person. Sometimes scientific accuracy is cool.
From: Paradigm Shift. Season 2, Episode 6 of The Expanse.

Human vs. Tech?

Another point was brought up during the panel: how will future technology shape our future?

It started with a discussion on making designer babies – whether this would be feasible, and what the ethical implications might be. With CRISPR/Cas9 technology making small edits to a genome a lot easier, it does not sound like something too far in the future!

While we are likely to be able to treat serious diseases with a clear genetic cause sometime soon, making genetic super-humans is a whole other deal. We don’t really really know enough about the genetics of intelligence (to name one trait) to make those changes! And if we believe science fiction, making superhumans usually does not end well.

That’s the way it usually seems in SciFi – tech will either be the end of us all or the solution to all our problems!

But if we’re being honest, technology is just heated up rock (quote from Jen). Most of our problems are of social nature, and technology will not be able to solve those.

For example, there are numerous examples of computers in general, and algorithms in particular, increasing inequality. We give computers datasets that are biased, so the automation will also be biased!

Technology is not the solution. It is an agent. We would better ask what humans are going to do with new technology. How will we shape our future?


Honorable quotes (slightly paraphrased):

“Can we ever train humans to be unbiased?” – Jeanna, as a response to the question of whether we can ever make AI/algorithms unbiased.

“I’ve never watched Interstellar, but I’ve read the scientific paper that came out with it.” – Daniela, commenting on how Interstellar felt a little close to her real work.

“If we can’t fix/control our own climate – we’re unlikely to be able to change that of another planet. Also, should we? Do we need another planet?” – Kim and Jeanna commenting on when we’ll be able to terraform another planet. Also, remember that time we *accidentally* left tardigrades to the moon?

“We do have spooky action at a distance” – Kim bot on how quantum entanglement explains how we can transfer information faster than the speed of light. Which is probably as close as we can get to having transporters.


* We talked about a lot more than what I’ve briefly described here. Feel free to reach out to any of the scientists on twitter to find out more or to ask your favorite science-versus-science-fiction questions!

Thank you to 500 women scientists (especially the Seattle pod) & the Marie Curie Alumni Association (MCAA) for their support in setting up this panel. Thank you to GeekGirlCon for hosting us!

I’m giving a public presentation – please send help

Giving a talk is hard. Giving a talk to the “general public,”* is possibly even harder. What if people don’t care about what you’re talking about? What if you’re not able to explain it in a clear way, without “dumbing it down”? There are many pitfalls to giving a public talk, and from giving and going to quite a few myself, I have a few ideas on how to make sure you nail your next talk!

A mistake I’ve seen quite a lot is diving straight into the data. But that will immediately lose anyone in the audience who is not an expert in [insert topic of talk here]. Here’s an example outline for a [fictional] talk about research on a sciency thing:

1. Set the stage

Tell the audience why they should care. Maybe your research is on ice shelf stability and there was something recently in the news about a city-sized chunk of ice breaking off an Antarctic ice shelf. Lucky you! (not so lucky for the ice shelf though). Use that powerful image as your first slide!

Chunk of ice breaking off an ice shelf (gif).
Elsa! Elsa! Please come help! [Stef Lhermitte / Sentinel 1 ESA]

Or maybe what you’re talking to contributes to the rising sea level? Great for you! (not so great for the Netherlands though). Use that striking image of cities that will disappear as your other introduction slide.

Part of Manhattan, and Jersey City but who really cares**, will flood with a 15 ft/4.7 m water rise (equivalent to the 2ºC temperature increase we should be more scared about). From: Before the Flood

Or, if you’re like me, your research is (was) about the Physics of Cancer. I like to start talks pointing out that “physics” and “cancer” are not necessarily two concepts that we think about in the same context.

A wordcloud about cancer, including words such as mutation, DNA, cell, screening, treatment, etc.
Can’t see “physics” anywhere! (Wordcloud from the Wikipedia page on cancer)

Whatever you’re research is about, there is a reason to care and a very illustrative image to accompany your impassioned exposé of why we should all be caring. You’re learning more about how cells work which can lead to better disease treatment. You’re satisfying our human need to keep on exploring by making better rockets to send into space. You’re leading to a better understanding of how humans interact with each other which will help us all be better to each other.

I don’t know, I’m just spitballing, but your research is important and we should care. And there is most definitely a meme, powerful image, or powerful gif available that shows us why.*** Because, let’s face it, we all like pictures more than words, no?

2. What do we know?

Time to show some numbers. Maybe there are some prediction models and the observations made in the last decades are increasingly matching those (scary) predictions. If you’re giving that talk about sea-level rise, show the climate temperature rise graph. If your talk is on a new and tinier microchip, Moore’s Law is your thing to show. If your talk is on cancer, you can give some numbers on incident rates, or how earlier detection can lead to earlier and better treatment.

In my case, my second slide is an overview of what cancer actually is, followed by an outline of what my talk is about: how understanding the changing mechanical properties of cells and tissue can help us better understand how cancer works, improve diagnostics, and come up with better ways to detect cancer.

What is cancer? Abnormal cell growth, abnormal cell survival, the ability to spread to other parts of the body, an accumulation of genetic mutations.
[Not a real representation of cells… contrary to popular belief (not really), they do not have faces.]

In short, set your research into a more general perspective. What is the current view on this subject, and where are the giant gaps in the knowledge. Because that’s where you come in!

Tip: if you ever start a slide with “there’s probably too much data on this slide…”, just don’t. Break it up into multiple slides. Only show the data that matters for what you’re saying. Anything but saying there’s too much data.

3. Time to shine!

This is where you can plug in your stuff. What is new about it? What problem is it solving? What does this new shiny data show?

Picture of me improvising a presentation
Look at my data, my data is amazing.

Some tips to help:

Show the process of your research and tell a story. People really like hearing stories about science is done. Maybe there’s an anecdote about how you were messing around with scotch tape and suddenly discovered graphene. Or about how you were able to hitch a ride to the field study and made an unusual friend. Or how the first time you set up the Atomic Force Microscope, which uses a tiny micro-probe, you broke the tip right when the professor walked into the lab.

Scanning Electron Image of atomic force microscopy tips
That triangle-shaped thing on the left labeled D is tiny and breaks really easily, especially when the scientist using it is being watched. From Bruker.

Also, don’t “half” introduce a complicated concept. If you need to explain a complicated technique to explain your results, go ahead. But don’t half-mention them and leave the audience wondering what that word (or abbreviation) was all about. Did you know that AFM can refer to Atomic Force Microscopy, Acute Flaccid Myelitis, or the American Film Market?

4. Conclusions

End your talk by looping it back to the first point. You told us why we should care about the subject, now tell us what your new findings mean for that subject. Add some future perspectives. Add another meme. Add an inspirational quote. Leave time for questions. Or if you’re me, you might take out a ukulele and sing a song.

Final conclusion, on the left a Nature Magazine cover showing scientists as superheros and a D'Arcy Thompson Quote.
I truly believe scientists are superheroes. Also, I find D’Arcy Thompson inspirational.

A final tip, make sure you plan your talk in advance! There is nothing more frustrating than seeing someone rush through their slides because they didn’t do a run through.

If you are in research and early in your career, such as a PhD student or a Post-Doc, you might have the chance to take some science communication training through your institution. I would highly recommend it! There are plenty of resources online as well!

Final thought, I secretly believe that scientists at all levels should take get training and practice about giving engaging presentations, to whichever audience, and learn how to make sure your audience doesn’t get put to sleep.

Good luck! You got this!


* “General public” is the worst blanket description of an audience. Let’s just say that the people who might come to a public lecture are not experts in whatever you are talking about but do have an interest in it (or they wouldn’t be there).

** I’m kidding. I’m technically from New Jersey.

*** Yes, I know I used a wordcloud as an example.

I’m a model and you know what I mean

Wait, what do I mean?

It’s perhaps a bit of a stereotype, but scientists don’t always know how to talk to non-scientists. To be completely honest, scientists don’t always know how to talk to other scientists! This can partially be attributed to the use of jargon – lingo that is used by a specific group of people that is difficult for people outside that group to understand.

Let me give an example.

If you look up the word “model”, Mirriam-Webster gives 14 different definitions; that’s already cause for misunderstandings without any science coming in!

Meaning number one: “I’m too sexy for my shirt!”

model noun [ mod·​el \ ˈmä-dᵊl ]
9 : one who is employed to display clothes or other merchandise //has appeared as a model in ads for swimsuits

In every-day, fashion lingo, a model is someone who shows off clothes or other merchandise on billboards, in magazines, on the catwalk, in tv ads, etc.

This version of the word model is probably not what any scientist means when they are talking about their model. Except maybe if they’re bragging about that “model they dated back in college,” but we were all dating models then, weren’t we?

dating a model meme: Leonardo DiCaprio saying: I'm dating a model now, she's a simplified representation of reality
I don’t believe you, Leo

Meaning number two: To see what cannot be seen

model noun [ mod·​el \ ˈmä-dᵊl ]
11: a description or analogy used to help visualize something (such as an atom) that cannot be directly observed

Some things we can’t really take a picture of. Or even if we can, it’s difficult to gather any meaningful information from the picture. A model of that thing can help; such as a model of an atom, or our solar system, or the universe. Such a model is usually simplified to allow a clearer understanding, and as a result, it is never 100% accurate.

For example, the model of the atom has gone through many iterations and has become more representative of the physical reality (in so far as we understand it). That doesn’t mean that older models are wrong, they’re often just insufficient. For many purposes, the Bohr model is enough to explain the formation of bonds and many aspects of physics and chemistry even though the quantum model is more details, and is needed to describe more advanced principles (like the types of bonds).

Models of the atom over time, a comic by xkcd
Hovertext: J.J. Thompson won a Nobel Prize for his work in electricity in gases, but was unfairly passed over for his “An atom is plum pudding, and plum pudding is MADE of atoms! Duuuuude.” theory.
From xkcd

Meaning number three: To the computer!

model noun [ mod·​el \ ˈmä-dᵊl ]
12: a system of postulates, data, and inferences presented as a mathematical description of an entity or state of affairs
alsoa computer simulation based on such a system (e.g. climate models
)

But not the type (i.e. model) of your computer. Wait. This is confusing.

The model of your computer might be 80NW. But a computer model – or a computer simulation – is a mathematical representation of a system and nowadays those mathematical representations are often running within a computer (because they can do math faster). Basically, a computer model/simulation is a program that is used to predict (hopefully) useful information based on a number of equations (or from learning data in the case of machine learning) that have been predefined.

In my PhD, I created a computer model for how ultrasound interacts with tissue. I told the program the properties of the ultrasound wave (its frequency, its shape, etc.); the properties of the tissue (size and shape, but also how stiff the tissue is); and the boundary conditions (how big the experiment was). After letting it run for some time, it would give me information back that I could use to understand this interaction better and compare it with results from physical experiments.

Graphical output of modelling ultrasound interacting with a penguin
Here is the incredibly useful test model I ran of an ultrasound wave (coming in from the left) interacting with a penguin. Image from PZFlex.

Computer models are very useful. Sometimes we would have to run experiments that are not possible to do physically, due to lack of resources or time or any other reason. Running a computer model is relatively cheap. In other cases, we are trying to make predictions on what will happen in the future, trying to do experiments on the unknown. An example of that is climate models.

Meaning number four:

model noun [ mod·​el \ ˈmä-dᵊl ]
14: ANIMAL MODEL an animal sufficiently like humans in its anatomy, physiology, or response to a pathogen to be used in medical research in order to obtain results that can be extrapolated to human medicine

also a pathological or physiological condition that occurs in such an animal and is similar to one occurring in humans

We are complex organisms, with a bunch of different types of organs and different types of cells that have a bunch of different processes going on at a bunch of different times. Sometimes, researchers can use cell lines – these are cells that have been isolated (often decades ago) and immortalized (they can be grown in petridishes and cultured for quite some time in said petridishes) to study biological processes and the effects of potential new drugs. But these isolated cells never give the whole picture (because they are so isolated), and sometimes animal models are needed for the next phase of genetic studies, cancer research, or drug development.

So unlike what I picture in my mind when I hear “animal model”, this does not mean mice in the bikini special. Rather, certain animals have traits that mimic a human condition or disease in such a way that research is meaningful. Whether it is ethical or not – that is a whole other discussing but just let me say that there are a lot of regulations and the principles of the 3Rs (Replacement, Reduction, and Refinement) are enforced in any proper lab conducting experiments using animal models.

The other note to make is that animal models don’t always give us the full information either. Again, it’s a model, An approximation. But since human experimentation is – well – inhumane, that’s often the only way to study genes and test drugs in a working-body-context.

A note on scientific theories

I don’t remember where I read this but: science theories are models for how the world works. In other words, like any model, they are not perfect! But they are a great way to try and understand the world better with our fairly limited brain capacity*. The fact that they are not perfect is actually really exciting: there is always more to discover, more to learn, more to understand!

In any case, if anyone tells you that they’re a model, if you know what they mean, you might want to ask them to specify… Just to avoid confusion.


*If you find this offensive, remember I’m mostly offending myself.

Definitions are taken directly from Mirriam-Webster dictionary.