The science of science communication, summarized

No, do not do a Google image search for "scientist" if you do not want to be depressed and outraged.
Is this what scientists think of “the public”? Stock Photo from Getty via jacks of science.
I’ve identified as a scientist for most of my life, despite leaving at the end of my master’s to pursue a career in science communication. The biggest challenge for me in that career shift – next to learning to meet a zillion little deadlines every day in lieu of huge ones once every few years – was learning to be present and relatable.

By default I am the classic cerebral, shy, white-coat nerd type. I’m still constantly fighting my own tendencies to live inside my own head and spew evidence faster than others can process it – tendencies that the culture of academic science enhanced in me, even socialized into me and my former science colleagues. I think I’ve finally managed to internalize the notion that I’m not just trying to reach “the public” with science; in fact I am part of “the public.”

The point is, sometimes scientists need to be reminded of their own humanity. And who better to do that than humanities scholars?

There’s a whole issue of PNAS out dedicated to the science of science communication, based on a meeting of the same name that I at one point was dying to attend. It turns out many of the sessions were recorded and you can still view them online at the meeting website. Or you can go to the 2013 meeting!

I doubt I will make it to the 2013 meeting. But I have the videos and the special issue of PNAS to relish. One piece from the special issue, Communicating science in social settings, includes a summary and discussion of assumptions scientists often make about “the public” and “the media” that, based on lots of social science studies and extensive survey data, deserve further scrutiny. Here are my takeaways from that section:

  • 1. More information is not better.
    Resist the urge to summarize your entire body of scientific knowledge in one conversation. Make one point. Make it quickly and make it well.
  • 2. The public still trusts scientific institutions.
    There goes that excuse.
  • 3. Stories are much more powerful than lectures.
    How well do you remember the last three movies you saw? How well do you remember the last three two-hour lectures you saw?
  • 4. No one totally ignores his own worldview when interpreting scientific information.
    That includes scientists.
  • Discouraging data: women in CS and IT

    In making my mark in the realm of data and information visualization, it will probably do me good to become a better and more knowledgeable coder. I am now looking into pursuing a little more CS education, and am excited about diving into edX MOOCs in computer science (remember when edX was OCW?).

    I’ve never shied away from things technical. I enjoy every opportunity I get to learn new software and programming languages, and nothing sucks me into an-all absorbing work cave as effectively as a new Javascript, HTML or CSS coding challenge. I’m even considering diving much deeper into CS than just the basics. After all, the entry level pay for a computer scientist or software engineer is at least 1/3 higher than the entry level pay for people in my current line of work.

    However, these data give me pause:

    Looking at the BLS numbers, it is interesting that these professions attract more women (as a percentage) than software engineers (20.2%):

    • Bailiffs, correctional officers, jailers (26.9%)
    • Chief executives (25.0%)
    • Database administrators (35.3%)
    • Biological scientists (45.1%)
    • Chemists and materials scientists (30.0%)
    • Technical writers (50.4%)

    Even the professions that are said to have a glass ceiling (such as CEO) have more women in them than software development. Based on the number of science positions listed in the BLS data with substantial numbers of women in them, it is clear that the myth that women are afraid of math or science is just plain wrong (even if less than 1% of mathematicians are women). And given the bizarre outlier of DBAs at 35.3%, and technical writers at 50.4%, we can see that women certainly do not dislike computing fields in general.

    IT gender gap: Where are the female programmers? by Justin James

    Now I remember why I wasn’t attracted to CS at university. I would try to strike up conversations with computer geeks, and then get shut out of the weirdly intense technobabble tournament that every computer geek conversation eventually turned into. My work is now and was then a huge part of my life; but I learned very early that the people I surround myself with are at least as important as the work that I do. At the time, a choice of major seemed like a choice to surround myself with people like the people in that major for the better part of my adult life.

    I can’t be the only woman who looked at the majority culture of computer programmers and thought, is this it?


    #ESA2013 Ignite: Open Science

    I had sooooo much fun organizing my first Ignite talk session. I would do it again in a heartbeat. I met several excellent people and learned a lot about data, R and collaboration tools. I am also super proud of how awesome my speakers and moderator are, and how thoughtful and stimulating the discussion was.

    So I’m sharing it all like a proud session mama. Here are the session details from the program and, when available, the talks themselves:

    Sharing Makes Science Better

    Organizer: @sandramchung | Moderator: @jacquelyngill

    Scientists too often labor alone. The need to closely guard ideas during the race to immortalize them in professional publications can make the practice of science crushingly lonely and ill-informed by tools and knowledge that could make science easier and better. Occasional scientific meetings are often the only opportunities to share ongoing work and connect with colleagues outside of one’s immediate working environment. But there’s a fertile online science ecosystem of innovation, collaboration and mutual support that carries on all year round, and its lifeblood is a network of scientists and science lovers who openly share tools, data, knowledge and ideas that help all researchers to do stronger, better, faster science. The rapidly growing open source and online science communities suggest a new model of doing science in which we build our work on tools, data, knowledge and ideas that are freely offered and contribute our own in return. This session features several free and open-source tools that ecologists have created specifically to help fellow researchers do the work of ecological science, as well some other tools we didn’t create but have tried and found enormously useful. We encourage our colleagues to try them, improve upon them, and perhaps most importantly, share what they’ve learned so that others can benefit as they have.

    IGN 2-1

    Big Data in Ecology

    | @ethanwhite, Biology, Utah State University, Logan, UT

  • Slides and text
  • Increasingly large amounts of ecological and environmental data are available for analysis. Using existing data can save time and money, allow us to address otherwise intractable problems, and provide general answers to ecological questions. I will discuss why we should be actively using this data in ecology, how to get started, and give examples of what can be accomplished if we embrace an era of big data in ecology.

    IGN 2-2

    EcoData Retriever – automates the tasks of fetching, cleaning up, and storing available data sets

    | @bendmorris, University of North Carolina, Chapel Hill, NC

    Ecology often relies on data that has already been collected, and an ever-increasing amount of biological and environmental data is now available online. However, it can be difficult and time consuming to compile synthetic datasets from data files stored in various online repositories or research web sites. The EcoData Retriever is a community-centered tool that automates discovering, cleaning up, and organizing ecological data into the format of your choice. I’ll speak about problems solved by the Retriever and touch on future directions aimed at further utilizing community effort and the web to automate ecological data access.

    IGN 2-6

    R-based tools for open and collaborative science

    | @recology_ (Scott A. Chamberlain), Department of Ecology and Evolutionary Biology MS 170, Rice University, Houston, TX

    Open science is the practice of making the elements of scientific research – methods, data, code, software, results, and publications – readily accessible to anyone. While this has great potential for advancing research, the absence of an open science toolkit prevents open science from being more widespread. We are building bridges between data (e.g, Dryad) and literature (e.g., PLoS journals) repositories and the open source R software, a programming environment already familiar to many ecologists. These bridges facilitate open science by bringing together data acquisition, manipulation, analysis, visualization, and communication into one open source, open science toolkit.

    IGN 2-7

    Social media for scientific collaboration

    | @sandramchung, NEON Inc.

    Sharing Makes Science Better: Social Media for Ecologists from Sandra M Chung on Vimeo.

    Scientific research is about the nurturing of knowledge and ideas. And to knowledge- and idea-lovers, the Internet is a door to an infinite candy store. Social media provide a means to quickly access exactly the online knowledge you want – by filtering the grand store of information through interaction with the people, topics and communities that matter to you. I wouldn’t stop at just knowledge consumption, however. Sharing your science online can connect you with mentors and collaborators, sharpen and deepen your science, hone your communication and teaching skills, and even earn you funding.

    IGN 2-9

    The power of preprints: the open publication project for ecologists

    | @cjlortie, Biology, York University, Toronto, Canada

    Ideas are free but not cheap. Peer-reviewed publications are still the major form of accepted dissemination of ecological ideas. Even with open access however, this communication modality is outdated. Discussion, feedback, transparent review, versioning, ranking, and articulation of both idea development and peer-review are needed to accelerate scientific discovery. A new communication venue is proposed herein: archival of open access pre-prints similar to arXiv but with annotation, review, and discussion. Think stackoverflow + arXiv for ecologists; not a final step in the evolution of scientific communication but an affordable idea we need to explore.

    Add your Twitter username to your conference badge

    R674372838_proof

    A Twitter sticker in action
    A Twitter sticker in action

    I designed these Twitter stickers in July 2012 to hand out at the ESA meeting in Portland during and after the social media workshop I ran with Jacquelyn Gill. They’re getting more and more popular (as of ESA 2013, I’ve handed out nearly all of the original 300 I printed) so I thought I’d share the artwork and information on how to order them.

    I used Sticker Mule to order custom 3.5″x.75″ rounded corner stickers that fit nicely below your name on your scientific conference badge (right).

    ADDENDUM 2013.08.12
    Feel free to re-use, modify and share the design. But please do not sell the stickers. They are for only personal and academic use.