I believe the question you're trying to ask is whether Outreachy interns
will end up bringing more people from diverse groups into the free software
communities they participate in. Will they go on to be mentors in their
community? Will they tell other people to join the community?

I think the question of whether people from marginalized groups will go
onto mentor or train others is not a useful question to ask. We can't
expect that people from marginalized groups do all the emotional labor of
making free software better. The burden of emotional labor of fixing a
community that skews towards a particular demographic should be on people
from the majority demographic. Otherwise the culture will never change, and
people from marginalized groups will spend all their time on
diversity/community efforts, rather than on free software development.

It should be the duty of the ASF community leaders to provide mentorship,
not on the people who are joining ASF projects hoping to be mentored or
find an inclusive free software community to contribute to.

Premise aside, to answer your question, I can provide some statistics about
the conversion rates of Outreachy interns to mentors and coordinators. I
don't have hard numbers on how many total interns have been converted to
mentors since we haven't done our longitudinal study. The rest of these
statistics are for the last Outreachy internship round.

Out of 42 community coordinators who participated in the last round, there
were 4 coordinators who were former Outreachy interns. Three of those
coordinators interned with the Linux kernel and one with OpenStack. Most
coordinators stick around for 3-5 years, so there's not a lot of
coordinator churn.

Out of 90 mentors for last round, there were 5 mentors who were former
Outreachy interns. Communities they originally interned with include
Fedora, LibreHealth, QEMU, Public Lab, and the Humanitarian OpenStreetMap
Team.

Onto your second question, which was how much impact word of mouth has on
the number of people from marginalized groups participating in free
software.

Word of mouth has a very big impact on whether people apply to Outreachy.
We accepted initial applications from 1,018 people last round. 14% of them
heard about Outreachy directly from a former Outreachy intern. 24% of
applicants heard about Outreachy from a friend. 9% heard about it from
Twitter. About 3% heard about it from another student.

If you combine these statistics, word of mouth brought in 52% of
Outreachy's applicants last round. The point being that word of mouth is an
important way to reach people from marginalized groups in tech.

Anecdotally, word of mouth is important because people from marginalized
groups tend to hang out in private, safer communities. They're likely to
face harassment when participating on public forums like StackOverflow,
social media, or even GitHub. Because of that, people from marginalized
groups tend to hang out in diversity in tech spaces, like Women Who Code,
Latinx in Tech, or other private groups.

Making those groups aware of your project requires having a direct
connection with someone from that group. That's why word of mouth is so
important in bringing people in. That's also why word of can be so
devastating to efforts to increase diversity. If one person shares a
negative experience with those private groups, say because someone compared
diversity efforts to the measles, that can really damage the community's
reputation.

Sage Sharp
Outreachy Organizer

On Wed, Jun 26, 2019 at 11:35 AM Ted Dunning <[email protected]> wrote:

> A more nuanced analysis takes into account how much virality there is and
> how it persists.
>
> If we train 100 people, now many will they train? And will that multiplier
> hold up in succeeding generations (it usually doesn't in marketing
> situations due to declining incentives).
>
> In the simplest case of constant virality, the ratio of indirect effect to
> direct effect (i.e. how many do the 100 train versus the 100 we trained)
> has some value k. If this value is greater than one, the number of people
> trained grows exponentially without bound. If k < 1, then the total number
> of people who are ultimately trained is 1/(1-k) times the number you have
> directly touched. To approximate the time dynamics, you need to know how
> long a generation is. If it takes time T before a new generation is passing
> on the torch, then your exponential growth will have an exponential growth
> constant of about k / T.
>
> The ASF itself appears to be an example where k > 1 and we have an apparent
> growth rate of 1.16/year. Cholera and measles are examples where k >> 1.
>
> In the real world with distractions and such, it is rare for marketing or
> organizational virality to extend more than 1-3 generations unless you have
> specific mechanisms in place to renew the vigor of transmission. With
> diseases, virality is limited by growing herd immunity.
>
> The whole point of the way we natter on about community is to build those
> renewal mechanisms into the structure of Apache itself. It isn't at all
> clear that we have succeeded since we still have 0-th generation
> individuals who are very active, although their focus has changed a lot
> over time so that they focus a lot more on community now. It is also a fact
> of life in strongly growing organization that these early voices are a
> smaller and smaller part of the overall community.
>
> On Thu, Jun 20, 2019 at 10:11 AM Awasum Yannick <[email protected]> wrote:
>
> > .... Now what you
> > might not see is that some of those people you have trained will go on to
> > train others..You see... Network effect. Growth here over 10 years is not
> > linear but exponential ...
> >
> > Every new Under represented person you empower is a potential data
> > point(noo...really a node) on a graph. They will go on to empower more
> > people like them maybe helped by unconscious bias.
> > For the $5000 spent for an Outreachy Intern, you are potentially
> creating a
> > whole new sub graph of its own which develops organically.
> >
> > I don't know if this makes any sense to you all?
> >
>

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