Katy Huff (one of our Software Carpentry instructors) has a great birds-of-a-feather talk on attracting diversity in the scientific python community up. She frames as an “intersectionality problem”, the notion of when you have two or more competing diversity problems (say, women in science, or women in science that code) to a double compounding of the problems.
Huff goes on to further explain: “The feature by which you’re both a rainbow and a unicorn, have all the features of social discrimination or social privilege because of your rainbow-ness. And also the same feature because of unicorn-ness but adding these two in a linear combination isn’t the same as having the experience of rainbow unicorn.”
Wikipedia describes intersectionality as “the study of intersections between forms or systems of oppression, domination or discrimination. An example is black feminism, which argues that the experience of being a black female cannot be understood in terms of being black, and of being female, considered independently, but must include the interactions, which frequently reinforce each other.
Take science for example, where there are roughly around 20% women (though certain disciplines are higher and lower). Computing in industry has something like 20% women. SciPy, Huff says, doesn’t have 20% women. These problems compound one another to ill-effect. And it’s not just women, but other minorities and groups in scientific computing.
I really like Huff’s take home recommendation to the audience. Lower the barrier to entry, but not the standards, because as Huff aptly puts it, “that’s offensive.” And as one of the panelist suggests, be careful about micro-aggressions. But that’s a separate post.
Have a watch.
This past week my colleague Greg Wilson kicked off another round of Software Carpentry’s online instructor training (the 10th cohort, I believe). Software Carpentry is the leading educational program of the Mozilla Science Lab (which I head up), and a core piece of the puzzle in changing the way researchers do science on the web.
In the past year, over 3,600 researchers, librarians and other members of the scientific community have participated in a bootcamp, learning how to use the shell, introductory git and version control, some data analysis and testing. The training is designed to help serve as a jumping off point for researchers to help them introduce efficiency into their work (and with any luck, lead them to doing more open and collaborative research). We also are fortunate to have over 130 volunteer instructors coming from a wide variety of backgrounds, and a series of online (and soon-to-be in person) trainings to help further increase that number. And we have big plans for the program moving forward, exploring ways to move from short two-three day trainings to longer term engagement and learning.
I’ve long been a supporter of the program – even before joining Mozilla to lead the Science Lab, and have even participated in a bootcamp as a learner myself.
This week, I took another leap and attended the first session of Greg’s online training (notes from that class can be found here), and started reading “How Learning Works” – the assigned course reading material. The training runs over the course of 12 weeks, with the class meeting every two weeks to discuss homework and the readings. Greg has crafted the course to focus heavily on teaching others how to teach rather than how to teach specific components of the bootcamp material (such as python or SQL). It’s rooted in educational psychology, looking at how students learn, and how to craft effective material to maximise learning and impact.
What am I hoping to achieve? Well, there are a few desired outcomes on my end, outside of practicing what we preach and learning more about the inner workings of part of the program. First off, I’m eager to get a better understanding of the process of graduating from a learner to an instructor (and outside of the instructor training, I have a lot of technical proficiency to build :) ), and experience Greg’s training for myself. Also, as someone who’s worked close to code but not often been the one programming myself, this exercise – with the end goal of being able to eventually help out with bootcamps – will give me a reason to embed these practices in my day to day. It also gives me a way to keep learning and engage with our outstanding instructor base in a new way (more on that later, and many thanks to those who’ve reached out to help so far). And beyond that, it gives me a better idea of where we need to focus out attention following a bootcamp to provide pathways for others to gain confidence and fluency in the skills taught, continue learning, and eventually one day, be able to give back and teach.
So, what’s next?
I posed to the instructor list a call for tips, tutorials and recommendations, so that in parallel to Greg’s training, I can also actively work to get up to speed with the bootcamp materials. I’ll post some of those recommendations in a subsequent post, and please keep those recommendations coming. Over the course of the next few months, I’ll be working to break away from some of my cheat sheets and gain more confidence in my technical skills, particularly around bash, git, python and SQL.
I’ll be blogging about the process, as well – as I’m sure I’m not the only dabbler interested in brushing up their skills so they can help with the program.
And with that, I have some homework to see to.
Early on as we were setting up the Mozilla Science Lab, I had a chat with a former neuroscientist about the challenges facing modern day research – soundboarding our initial ideas, hearing about his experiences in academia, discussing gaps in training and awareness. What struck me from that conversation in particular was a comment made about where “most of the good science” came from (90%+ in his estimation), challenging the idea that such a program as ours was needed as in his opinion, if you needed to know something or access research and if you were at a top notch university, then it was a non-issue.
And that’s where 90% of the “good science” was done, he soon after conveyed – at top-level universities in the US (with a few exceptions).
Now, it’s no secret that the research we see gain the most citations, rank highest in indices such as the ISI, or share is not fully representative of all the world’s researchers, and that what’s available is skewed largely to western cultures. That’s slowly changing, but in reply to the neuroscientist’s point above, what’s reflected in the literature is not the whole picture, nor is it indicative of the broader research community – the folks we aim to help through our work at the Science Lab.
Which brings me to my conversations over lunch today. I’m currently in Nairobi, here for a workshop that kicks off tomorrow focusing on discoverability and openness of African scholarship, with many of the participants East African agricultural scientists. The two day workshop is sponsored by the Carnegie Foundation and organised by OpenUCT in Cape Town, the first of what I hope are many knowledge sharing discussions with those here on the ground trying to stay on top of their research, build out their university and personal footprint in their fields, and well, communicate that out to the world without their voices being lost.
Here Open Access is a touchy issue – most of the researchers and librarians I’ve spoken to in support of the premise and of what that unlocks for them in terms of the world’s literature. But in the push to turn that spigot all the way to OA, there’s also a tangible fear of losing what competitive advantage they may have built up over their careers, a worry that their work will not reach the same audience as others in the West.
And then there are the technical and cultural issues here on the ground, of which I’m just scratching the surface. From a UNESCO / eIFL workshop I participated in back in 2009 around sharing content and data on the web to the perspective heard today at lunch from a librarian in Ghana, we’re still working across varying levels of awareness and just sheer resource. Many students, even up to the postgrad level, at these universities still rely on their central library on campus for Internet access (smartphone adoption is helping, but personal laptop ownership is still not yet the norm). Some universities only recently celebrated their 20th anniversary, as opposed to their 150th (or 918th, if you’re Oxford), formed after African independence. (Have a read of Eve Gray’s fantastic post about these issues for more.)
So why am I here, and not at say, SXSW? Because science is global. Perspective is important. The means to understand the world, the ability to process, share, and generate new knowledge is not just for the elite, but for all (and luckily, my colleagues at Mozilla firmly believe that too). And given a chance to hear from other researchers on the ground, curious about “science on the web” from discoverability and dissemination, to capacity-building/skills training was an opportunity I couldn’t pass up.
This is one of our first steps in building bridges with researchers in other parts of the world, so that we can truly work together to make research more efficient. As stated in our plan for 2014, we’ll also be looking at running events and hearing from others in South America, Australia and in Asia about their challenges in doing open research on the web. Our goal is to continue to see how we can help the broader research community and join up the various efforts and threads of conversation to move forward together. Have an idea? Get in touch. We’re here to help.
And many thanks to the Carnegie Foundation and the Open UCT team for inviting me to join them this week in Nairobi. You’ve already given me much to think about, and I look forward to learning more over the next few days.
Today marks the start of the Mozilla Summit (#mozsummit), a three-day meetup (split between three cities) of Mozilla staff and key contributors. It’s a celebration of and a chance to discuss the amazing work that’s being done across the organisation, from Firefox OS to Open Badges and the Science Lab. This is our chance to come together as a community, learn from one another, and more specifically for our work at the Science Lab – our chance to not only tell our story, but invite our colleagues in to help test and shape it.
Earlier this week, in the lead up to the event, two of my Foundation colleagues posted two stellar pieces that got me thinking about where we’ve come in the last four+ months with shaping the Science Lab. If you have the time, do check out Matt’s post on working in the open – core to how we operate at Mozilla, and Brett’s reflections on the summer of Maker Parties on the Webmaker blog. They’re a great lens into not only the activity going on at the Foundation, but a look into our process as a whole.
On to some reflections of our own …
We launched with an idea of how Mozilla could best help the research community this past June. We had a project up and running to build on (Software Carpentry) and a sketch of some of the areas making the most progress in advancing science on the web, as well as an even longer list of areas needing attention.
So where have we come since June 14? Here’s a look at our progress to date, what we’re excited about and what we’re still exploring (and could use your help with).
We spoke with over 3,000 people.
In the last four months, we’ve engaged with (not just talked at) over 3,000 people, astonishingly, largely face to face, to ask them where they see the research system breaking down, where is attention needed, and start to discuss how an organization like Mozilla can help. I’ve spoken with researchers, educators, developers (or “research software engineers”, bridging both worlds), scientific startups, publishers across the spectrum, and institutions around the world. We’ve spoken with researchers of all shapes and sizes working on problems in the US, Australia / New Zealand, South America, and Africa – to see how we can best work together to achieve this vision of more web-enabled research that helps us connect, helps us learn and innovate, and helps us interoperate.
We honed a model for the Mozilla Science Lab.
A few common threads emerged from those conversations.
There’s a tremendous amount of work being done to move science to the web, but not in a coordinated fashion. And for all of that development, it’s still difficult to discover what work’s already been done. So we’re duplicating efforts, or, even worse, continuing on with business as usual.
You can read more about the model for the Science Lab in our post here (feedback always welcome). We strongly believe that what Mozilla can best contribute to this space is the expertise, values and leadership needed to fill in the missing gaps (digital skills education, examples of what’s technically possible if systems interoperate), to be the support beams needed to truly change the way science is done.
We started to map activity to those pillars
What have we learned (and what do we need to work on)?
… and we need a tighter way of articulating our project aim to a wider audience.
One of the interesting points that’s bubbled up in the last few weeks is a bit of dissonance between the phrasing “Open Science” and “science on the web” – two characterisations that I believe are dependent upon one another, often used interchangeably in these circles. But there are other situations where “open” is used as a catchall, and we need to do a better job at unpicking why what terminology matters, what it means in this context, and explore the relationship between those two.
In the open science circles, working on the web is the condition to moving work forward – crafting our systems to interoperate, designing our communities to operate in a networked fashion, making sure the components of our research (data, code, content, materials) are as reusable and maximally interoperable as possible. Working on the web without having those components or that process be open doesn’t scale. But we need to better articulate what we mean by those two phrasings, and show by doing to researchers what science on the web means.
We need a better, more explicit call to action.
In the short term (for those of you who have been asking ;) ), we are working towards launching our Science Lab website. But that’s not really the type of engagement I’m shooting for, though it will help us create a core focal point for developments and resources not only with the Science Lab, but also in the community. Watch this space.
We’re currently exploring an action-based community building effort that we’d love your feedback on – the aim being to do more science on the web, and build communities of practice around that action. Much of this is a hattip to the brilliant work the Webmaker team has done. For those of you who’ve seen me talk recently, I also take inspiration from the International Geophysical/Polar Years – international efforts spanning 60+ nations, involving 50,000 participants across the social / life / natural / theoretical sciences to push towards one common goal.
I think we have a real opportunity to do the same for science on the web, showing that working with open-access content, open data, open-source / interoperable tools and code, or running a training is the future of 21st century science, and invite you all to join us.
This is where we could use your help. As we work to craft resources to help others learn more about how to work on the web – about implications for data, content, code, new tools, training programs, how can we best structure that for maximum engagement?
I’d love to hear your thoughts.
But we’ll save further discussion on that for another blog post … I’ve got to get ready for the Summit. :)
The event also features Pete Binfield (PeerJ), Elizabeth Iorns (Science Exchange), Barry Bunin (Collaborative Drug Discovery), Mark Hahnel (figshare), Brian Nosek (Center for Open Science / Open Science Framework) and more. Check out the agenda here.