in International Development here at CIRED, The Center for International Research,
Education and Development at Virginia Tech for part of Outreach in International Affairs and
I want to introduce Lumbini barua who you see up there with that same beautiful backdrop that she
put together for us. She's my graduate assistant a Ph.D. student in the School of Education here.
So welcome to The Virtual Women and Gender in International Development Discussion Series. This
is our second event this Academic Year and we're very happy you could all join us for Dr. Hale Ann
Tufan's presentation and discussion. This event is co-sponsored by CALS Global at Virginia Tech
and the Women and Minority Artists and Scholars Lecture Series also at Virginia Tech through the
office of the Provost. So as of this morning, we had 48 people registered for today's event. Zoom
is a Fickle thing it's very easy to register we never have all the people that sign up actually
show up but we'll see who will but of those people it was a very diverse group including people from
Bangladesh, Canada, India, Kenya, Mexico, Nigeria, and Pakistan, and of course people also in the
United States. So welcome to everybody. Please note that our event will be recorded and available
on our website uh later um a couple weeks later um so by staying on now you are consenting to being
recorded if you don't want your image included you can shut you know close down your image, turn
off your camera. The full calendar and any updates are available on our um on our website for the WGD
Discussion Series Lumbini will surely put it in of course she's ahead of me. So before introducing
our speaker I invite you to reflect on Virginia Tech's land and labor recognition statement. so
Virginia Tech acknowledges that we live and work on the Tutelo / Monacan People’s homeland and we
recognize their continued relationships with their lands and waterways. We further acknowledge that
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explicit material commitments falls short of our institutional responsibilities. Through sustained,
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must also recognize that enslaved Black people generated revenue and resources used to establish
Virginia Tech and were prohibited from attending until 1953. Through InclusiveVT, the institutional
and individual commitment to Ut Prosim (that I may serve) in the spirit of community, diversity,
and excellence, we commit to advancing a more diverse, equitable, and inclusive community.
um so okay some housekeeping notes this discussion will last approximately 45 minutes our speaker's
presentation will be 20 to 25 minutes followed by about 20 minutes of discussion and Q/A.
You're welcome to post any questions at any time in the chat box because we put them into a Google
doc and I will read from them later so as your questions come up feel free to put them in. If
we run out of the questions that people have written to the chat box I will ask for people
to raise their hands and ask questions or engage in discussion um with our speaker.
So in order for our discussion to be as rich as it can be we need everyone to be respectful
and treat all participants with kindness and consideration without discriminatory behavior.
So again we're being recorded and you will have access to it via our website. Okay so in advance
I ask you, I beg of you to please fill out the survey that you get a link to at the end. It's
very important to us to raise funds and to help us with um planning as well as fundraising and
you can tweet us by tagging us and Lumbini is going to put that in at WGD_VT. Okay now what
you really are here for, I'm going to introduce our speaker uh Dr. Hale Ann Tufan is an associate
professor in Cornell University's School of Integrative Plant Science and very active in
international research for development projects in our work with plant breeders, social scientists,
and research institutions. Tufan explores how agricultural research processes and
outputs can positively contribute to gender equality and social inclusion.
Through her research to develop methods and approaches she enables gender plus analysis
and agricultural Innovation while advocating for inclusive agricultural research by
challenging power and Norms in the research ecosystem. Her work focuses on building
gender responsive crop improvement systems through curriculum development and training,
leading research on priority-setting, market research, gender research, and on-farm testing.
She is a priority-setting co-lead for the Feed the Future Innovation lab for crop Improvement
also a principal investigator of the gender responsive researchers equipped for agricultural
transformation known as GREAT, a principal investigator for the Muhogo Bora: Cassava for all,
survey division lead for the NextGen cassava project and gender research lead of the feed
the future insect resistance eggplant partnership. She was awarded the Borlaug field award in 2019
uh to recognize her work to ensure women farmers and researchers are
fairly represented in agricultural research for development, and the title of her talk today
is "Beyond women's traits analyzing gender and social differences for inclusive crop
varietal design." Please welcome Dr. Hale Ann Tufan! Thank you so much Maria Elisa, very nice
um introduction and thank you for the invitation to give this talk. Welcome everyone so uh I don't
need to introduce myself more but today I'll just go over very quickly what I'll be talking about.
So as a brief outline there's so much to talk about in this space it was really hard to narrow
down but I'll do a brief introduction of gender and technology development just to set the scene
you know what how does this work get situated in that broader context, talk a little bit about
the gendered science of crop improvement and what that means um and then highlight basically kind of
two or three different sets of work that map to that one is the power dynamics and crop reading
teams and talk a little bit about methods around cassava traits and adoptions and Seed systems. So
knowing this is a diverse audience I thought I would start with my favorite story and that is
this crash test dummy. So meet the 50th percentile crash test dummy. This um the reason I'm raising
this is in all craft simulations globally the body of the 50th percentile male from the 1970s
in the U.S is used as the norm. What that means is the body of this man is what's being used in
all crash test simulations globally well had been used. um and what does that mean? That means that
the male body is normative and that results in women being 70 percent more likely to be seriously
injured in car crashes globally and I'm raising this just to say when we think about this gender
and technology development gender and technology more broadly there's so many poignant stories like
this crash test dummy that really positions men as being the norm especially North American men
being the norm especially in health sciences and technology development and another example
that I like to highlight is an introduction is this book by Caroline Criado- Perez you may have
read called Invisible Women and here she talks about data gaps and heart attack symptoms this
is kind of a second example if we think about gender and technology, gender and health what
we know is common heart attack symptoms kind of on the left here are common for women and men so the
crushing chest pain the sweating, the nausea, the radiating pain, but what we don't talk about in
Physicians don't talk about often enough are these specific symptoms that women experience fatigue,
shortness of breath, flu-like symptoms and again as she really poignantly describes in her book
what's happening is and I'll just quote from her book because I think she puts it so well "only now
it turned out that our cultural positioning of men as the default humans was corrupting science and
as a result women were dying" because again women are more likely to die of heart attacks than men
because they're common their symptoms the common symptoms they're experiencing are not recognized.
So over and over again really in three slides summarizing Decades of work what we're seeing
and for those of you more interested in the space I'm going to kind of forward you to
this website called Gendered Innovations out of Stanford, there's many case studies
really documenting this bias in health, technology, engineering, environment,
the systematic bias that really causes our science to be incomplete and there's been big movements
especially I would say in health and technology to change this. Right? So at this day and age
as we're thinking about you know kind of maybe 10/20/30 years of shifts and changes in the space
and the documentation even there's an editorial in nature from about three years ago that says
unless you consider sex and gender analysis in health interventions it's not good science.
So as I'm reading all of this and we're looking at the landscape of how things are changing around
agriculture and agricultural research what we really see is plant breeding is a little
bit behind or agricultural Innovation is a little bit behind to put it mildly
and basically the same concepts of the gendered science and the gendered health science the
gender technology really does apply to crop Improvement as well. So I'm going to title this
the gendered science of corrupt improvement and go a little bit through what that exactly means.
Yeah so starting this section again with a quote and I quote this because Rex Bernardo is I would
say currently one of the lead thinkers in plant breeding and is really theoretically
strong and kind of influences a lot of the plant breeding thinking especially in North America
and he describes in one of his big Publications about plant breeding and the latest status of
plant breeding. Plant breeding is the genetic Improvement of plants for human benefit and I
think that's compelling because the word human is applied here yet we spend probably not enough
time really thinking for which humans and what kind of benefits. So really unpacking
the assumption that underlies and a lot of the gendered assumptions that underlie which humans
and what kind of benefit is really what we're trying to do in a lot of our analysis and work.
So can we talk about the gendered science of plant breeding and there's not a lot of work
out there are those of you not familiar I included a definition of Science and
Technology studies here because I realize that may not be familiar to everyone but
really taking a critical look at the science of plant breeding using a more STS lens. So
STS is an interdisciplinary field that really examines creation, development,
and consequences of Science and Technology. It really posits that they're situated in historical,
cultural, and social contexts. So really in essence thinking about how and who carries out
research really impacts the design especially of agricultural Innovations in this case.
Taking an STS lens to plant breeding is fairly new. It's an emerging field I would say but
there's an older example from Ann Ferguson in Michigan State from 1995 looking at being
improvement from a project in Malawi so what she saw there was really critically examining
the process of being Improvement in this project and she saw first of all that there were really
gendered assumptions around the distribution of farmers knowledge. So the scientists themselves
were making these assumptions around who held knowledge about beans within farming households
then that was followed by kind of um assuming or accepting or deciding that the knowledge of men
farmers was superior to that of women farmers. So kind of this is the process that she's documenting
as a result of course the information that they're gathering was biased. They're gathering more
information from men and this is quite classic in this field I would say and it is changing rapidly
but this is just kind of a nice way to lay it out and subsequently influence the initial proposals
for plant breeding strategies that resulted. So really you see this kind of causal effect
of having that initial gendered assumption and bias that was held by those breeders and those
scientists and how that really carried through the whole process all the way to the decisions
they were making and priorities they were setting around their plant breeding strategies.
So this is one example where you can kind of end at those decisions being made but you know
the so what what happens after that, what are the implications of that and I would say again
there's not a lot of systematic documentation of the after effects of being quote unquote gender
blind or not considering these systematic biases in project design and implementation. But there's
one example to me that stands out that I think is quite nice in a way that it really documents from
start to end is the story of nerica rice. This is the work of Johanna Bergmanloden from 2012
and nerica rice is a new type of rice variety that was really developed by International research
centers and released in this case in Uganda. So this is kind of a case study from Uganda.
So what they saw was of course these nerica rice varieties were yielding higher and they
documented initially the household income gains from adopting this rice. So these are household
level gains that they were seeing higher incomes from adopting households but what she then did was
layer that with a much more qualitative in-depth study to say is that true? Are
there different individuals within the households experiencing different effects from that adoption?
and what she documents is really interesting because this new type of rice variety the
nerica rice was a lot more susceptible to bird infestation, and as simple as that may sound
what was happening was she was documenting birds were attacking these rice varieties
a lot significantly more than they were that kind of traditional varieties grown by these
farmers and as a result women and children were having to spend a big portion of their
day chasing away these birds right? So then she's documenting this exacerbation of time,
poverty, drudgery that went with that and really kind of preventing the formation of their social
and human capitals because they were spending so much time on managing these fields and here I just
want to pause to say in plant breeding and crop Improvement spaces this kind of critical analysis
of the gender nature of the research as well as the consequences of that is still pretty much
in its infancy because as you can see we're still looking at this at least do no harm level of you
know don't make these mistakes so you're adversely affecting the adopters of these new varieties
and having said that plant breeding is also rapidly changing. So the examples I'm showing are
probably more from public sector plant breeding, food security oriented crops, more agriculture
research for development and plant breeding they're in. What's happening over the last
five years to this plant breeding space again this is more for agricultural research for development
plant breeding is that it's becoming really shifted towards what's called the business of
plant breeding. So you see a lot of the adoption and this is somewhat donor driven the adoption of
a lot more industry North American plant breeding large multinationals and how they approach the
business of plant breeding has kind of infiltrated these small public sector food security breeding
programs and we can go into depth about two hours on this topic alone but I'm raising this because
it's changing the context within which were they doing these analyses and actually directly
affects it. What does this mean in practice? I'm kind of drawing from a presentation here of this
adaptive process, this is a modified version of syngenta seeds stage plan. What this means
is syngenta is a kind of giant multinational Seed Company. This is how they develop their
new varieties again, commercial European U.S sector. So this is a process which they follow
and what's happened over the last kind of five to seven years is this process has been quote
unquote adapted to public sector programs. What you're seeing here is kind of a sequential product
design development release and management cycle and this makes a lot of sense for kind of the
context that it's been developed in. Well you have a lot of market research right? So
companies really approach this as an investment decision. They look at the commercialization,
they look at the seed sales, they make decisions on investing or investing into or away from a
variety that they may be designing mostly based on their market research. So that's why I've kind
of circled this here but the interesting thing is what does market research mean in the origins of
this thinking it's seed sales so you can track to see how successful your variety is in the market.
But that's a problem because this is a review from 2019 again by pretty prominent breeders I would
say publicly accepting the flaws and some of this thinking by saying in the private sector breeding
programs numbers of units sold or market share or common metrics of success but such information is
difficult to obtain for public sector programs particularly in developing countries and comes
with the added socio-economic complication of calculating who benefits and how equitably and
how the benefits are equitably distributed. So I'm raising this just to say there's this
giant shift in the plant breeding space and I won't go into the depths of it for those of you
interested I'm just going to flag this paper kind of taking a critical look at these shifts
and how this demand concept of demand in markets has infiltrated this world, but the second point
I want to make here is that because there's an absence of market data or market intelligence as
it's sometimes called in the public sector what's happening is this thinking in this shift is really
leading to social scientists and gender researchers being tapped more heavily by
breeding programs and that's what we'll talk about a little bit in the next sections because there's
this hunger for market data and the understanding of that is so different that you really need to
design and over research to understand what are the market demands and forces and that
even looks like in an informal seed system for food security crop is a whole other discussion.
But looking at this what I'm seeing in some of these programs and this is work of the next gen
cassava project is the social scientists coming into this core team of breeding you know can
create some problems because suddenly you have interdisciplinary teams working together, you
have your economists with your social scientists with your breeders and the idea that you can put
all these people in a room and they'll cohesively make equitable decisions together as a big
assumption. So I think that's kind of slowly being revealed. we'll talk about that a little bit too
but it to circumvent a little bit of that joint decision making you see again some
industry thinking coming in here to say how do we make decisions? can we think of decision rights?
So these are also not just the frameworks, but the processes from industry coming in.
So what you're seeing in some of these programs and I'm pulling this out from a report
this is kind of this team this breeding team particularly in West Africa for cassava is
listing different standardized disciplines that would be involved in decision making for plant
breeding right? And this is to decide to progress or not along a product development pipeline so
everything is changing and how these teams are being constructed, how they're working together
and what you're seeing is there's probably I would say for the first time a formal list of
disciplines but also what's called decision rights. This was kind of a consultant from
private sector coming in and talking about how can we bring in decision rights and mapping and the D
means an ultimate decision maker and anyone with an A is someone who has to agree to that decision
before it can progress and it's interesting to see here for example that you see gender and social
sciences, the market economist is the decider the gender social scientists person who's presumably
in the room has a veto right, right? So you really have this formalization of roles, formalization of
teams and how they're supposed to function together and this is kind of a fascinating
space in other projects too so next I'll shift to looking at this question of how do you bring all
these different disciplines into a room to make a decision together in a very complicated setting.
So it's this question that drove us and this is the Innovation lab for crop Improvement I won't
go into the depth of the project but to say we're feed the future Innovation lab based at Cornell.
We have different crop mandates and we work in four centers of innovation as we call them across
five countries, our website has very in-depth information on all the programs and all the
work we do but I'm bringing this up to show you know we're walking across many different programs
many different crops and the center kind of the idea of this program is quote unquote improving
the breeding efficiency right the process.So we have phenomics people, we have genomics people,
we have informatics people that do kind of the backstopping for the breeding
but we also have a group that works on what's called priority setting and cross-cutting issues
and we really look at this question of how do these programs set their breeding priorities?
Coming back to that First Column that I just showed you how do you decide what's important how
do you understand what demand is and what's kind of impactful before you even start the breeding
process and a lot of these programs you know are national. These are all national programs in all
of these countries and the presence of social scientists and their teams is quite thin and
I would say mostly economists that do adoption studies historically and on to these teams we're
layering further complications saying don't just think about your breeding priorities but
think about impact. So we're bringing what are they called the cross-cutting issues
um this is led by Deborah Rubin and her team there as a part of the The Innovation Lab really saying
how can you set priorities that don't just look at productivity and yield but bring in resilience,
gender equality, nutrition, youth, inclusion. I'm bringing this up to say these teams are often you
know loaded with a lot of information and a lot of different new topics that they really hadn't
um traditionally handled and I'm just going to stop here to say that that you know can cause
a little bit of disruption because I think we don't often think about power dynamics in these
breeding teams so as we're bringing some of these topics in and specialists who specialize in those
topics into these core teams that have worked kind of in isolation together autonomously there can of
course be ensuing power dynamics and struggles and what that looks like for interdisciplinarity and I
want to say it's what no one really wants to talk about because there's this assumption that you put
everyone in a room and everything works great. So I see a lot of this kind of sugar coating
of the interdisciplinarity in plant breeding and how that's changing and improving things
without really looking at the critical dynamics of what may be happening with these shifts.
And why am I asking about power? Many of you may or may not be familiar with the gender
dimensions framework developed by cultural practice and D Who's involved in our team
and their work over the kind of last decade or more and really the reason is as you look at
gender-based constraints and opportunities in ag research for development let's say specifically
there are multiple dimensions that come into play beliefs, perceptions, access to assets, practices,
institutions, laws, and policies. All of these really apply to a lot of the interdisciplinary
teams that we're talking about and the center of all of those kind of different dimensions that
cause gender-based constraints to manifest is power. So we really want to bring this thinking
to our examination of the power dynamics within some of these plant-breeding themes. So really
borrowing some from of this um broader thinking and really asking if we're looking at priority
setting and how teams set priorities in an interdisciplinary manner we have to be honest
to say you know we know there are different priorities at play, we know there's different
dynamics at play in the nexus of all that coming together really is not a well-thought-out process.
So is this kind of pilot project we ask the question how do power dynamics and breeding
teams and institutions affect interdisciplinary and specifically the voice of social scientists?
For this work we're working with two Consultants Beth Cullen and Catherine Snyder who are really
digging deep into Power Theory, looking at power dynamics and interdisciplinarity. So I'm pulling
this slide from from a literature review they prepared on the topic and just pointing out
some high-level bullets of what is known what is out there what has been documented in this space.
What we do know is institutional arrangements do not promote interdisciplinary collaboration.
Scientists are often rewarded for scientific outputs and not interdisciplinary collaboration
it's just not set into the promotion and kind of structures of most
institutions especially National AG research institutions. We also know that hierarchies
among and preconceived conceived ideas about other disciplines can affect collaboration and
integration of knowledge. What does that mean? I see this all the time in the work that we do
that kind of there's this preconceived notion of what qualitative gender research may look
like? how valid it is? how is it generated? is it scientific? There's all these kind of very loaded
ideas and biases and again the power still lies a lot of the time with the Breeders and they're
able to make take or not on board some of the ideas and thinking coming out of these spaces.
And part of that is also kind of how disciplines are perceived and there's some documentation of
social science more broadly within the CG for example of being perceived as service providers
right? This is the usual the last minute people going to researchers who may have experience
in gender research and saying can you write me my gender paragraph? or can you do this little
study? and with little to no funding. So really not looking at these disciplines and scientists on
the teams is producing relevance, standalone strong science but really just service providers. So again
these are existing things from the literature that we're pulling out here. And at the end of the
day what does this mean that these disciplinary hierarchies really reflect who sets the research
agenda, who's defining the research questions and who's allocating the budgets and the answer to a
lot of those in plant breeding is clear right? It's still really dominated by plant breeding teams.
And how do you actually look at this because we know that these hierarchies especially are more
strongly felt if you're a woman social scientist in these breeding teams. Again this has been
documented as the double marginalization right? In the agricultural sector we know it's historically
been male dominated and this great paper by Farl and Rickards calling it deeply masculinized and
shaped by anglo-male scientists. So this is kind of the history of agricultural research
manifesting itself but for social scientists who may also be women in these spaces, who may be
gender experts specifically, the struggle to make their disciplinary perspectives heard is really
difficult. And Verma et al. in 2010 really called us the double marginalization in terms of power,
decision-making, and access to resources. So we're taking all this background ideas and saying okay
drawing on what's known in these interdisciplinary teams, drawing on we know the gendered basis
of plant breeding and how science is gendered itself in contextual and situated
we're kind of taking some of the power theory and applying it through research, primary research
with breeding teams but also doing some power mapping to say how is power felt, how is power
operating, how is it manifesting right? And using the skeventus power Cube Bethan and Catherine are
really digging deep to unpack various dimensions that may be felt by these breeding teams.
So watch this space I'm not going to be presenting results at this stage from this work but just to
say this is an area of really intense interest as again the field is shifting and plant breeding has
become becoming more interdisciplinary and that is being much more formalized.
At this point I'm going to shift gears a little bit because the title of my talk is beyond women's
traits and I'm going to talk a little bit about especially methodology. So once you get
these breeding teams together into disciplinary teams together what kind of information do they
generate that the plant breeding decisions are made based on? So kind of taking away the
kind of unclarity or the theoretical aspect of that and really demonstrating what we're
talking about when we're generating some of this knowledge. So I'll take the work from cassava and
the next gen cassava project and talk a little bit about traits but also adoption.
So this is a methodology that we developed for the next gen cassava project and the idea here is
it's not enough just to kind of do a survey to understand traits and trait preferences right?
That there's a lot more complex research that we need to do and by all means this is not perfect
but we're trying to cover all different bases. So the first set of work that we did and this
is the work around six seven years now is do a lot more qualitative work together with what's
called the RTD foods project to do you know what in that project is called gendered food mapping so
really understanding kind of the product movement and who's involved and how but also taking really
qualitative data at those stages for what an ideal cassava variety would look like. So this
is mostly qualitative information and I'm giving some quotes here from what's emerging in that work.
We then move on to add more quantitative layers to this to say okay if we can hone in on eight
to ten traits and characteristics that are really emerging from the qualitative work and understand
who is prioritizing what traits and how really generating calling typologies and we published
some of this work but not only looking at the different traits but adding a layer of this Roma
survey this is kind of a socio-demographic survey developer iata to start pulling apart more nuanced
social identities and how those may be driving the trait preferences. And as a last step not just
kind of doing the descriptor work and the typology but then seeing what happens on farm when we offer
respondents choices of different varieties, how are they making those choices of adoption or not.
So I'm going to really briefly present two or three slides on the kind of work
they were doing this space to really bring it home
Low and behold and not surprising we know that social differences drive trait preferences and
what I like in this kind of work that we've done is we've haven't just done the binary. You see
a lot of literature on men versus women in terms of trait preferences and many different co-ops in
many different countries. We wanted to move beyond that and for that we employed this roma survey
that allows you to not just kind of disaggregate your trait preference data what you're seeing
along the bottom here these are different cassava traits: taste, texture, color, swelling.
um but we're then looking at the top we have the sex disaggregation and then we also have
desegregation by poverty level, food insecurity status in a region. And the reason why we've shown
those four axes is kind of we did preliminary analysis to see where the greatest differences
were or kind of correlations with choices around traits. What this allows you to do and for
a breeding program this is compelling because you don't just present national level data to
say men want this and women want that which is not really useful for them to think in a binary
sense and it's not useful for us to present that data as such because it really oversimplifies.
We're able to start pulling out especially we see in Nigeria for cassava where the state is coming
from you see huge regional differences in trade preferences. So we can start seeing women in the
Southeast who are in poor but food you know insecure households these are the different
priorities of traits. Likewise in the South South for non-poor food insecure. So you can
start pulling out much more nuanced trait level data and this is interesting for programs because
as they're deciding on what to breed for they have a lot more granularity on the kind of data
that we're presenting to them they can be much more intentional about their design decisions.
Layered on top of this we also do a lot of kind of the gendered food mapping work which is really
kind of looking at who's involved where and how along kind of value chains for cassava and Nigeria
and we can look at the on-farm data to see who's adopting what kind of crop or or cassava variety.
This is a very complicated graph on the right. So take it with a grain of salt but the bottom
line is the value chain role and gender together drive trait or drive varietal preferences. What
does that mean the choice of adopting one of these many different varieties is that we've
presented as options to farmers using the tricot method. Interestingly the most significant kind of
bifurcation in the data what that means the most significant differences are not by the sex of the
farmer growing the crop but who they're selling to and that's a really compelling new kind of piece
of information because it's something we hadn't thought about before. We always look at the sex
of the farmer and who's growing the crop but we don't really think what happens next so what we're
seeing is there's more kind of variability in the data explained by who that person who you're
passing your product onto then who's actually doing the growing. So we're really again trying
to tease out some of this nuance to say you get differences in types of varieties chosen
based on who you are and who you're interacting with along the value chain. Again we can start
presenting this to breeding programs so they can understand how to make some of these choices
and lastly, this is really interesting work that that we recently submitted looking at
who do you ask about what and how really matters and this is data that we've mined from a study
that's about seven years old now about cassava adoption in Nigeria. Again so really what we're
showing here is this is all publicly available data that we went back through and analyzed
and the top row here is looking at all plots and how much cassava is grown on those plots
and we had interviews with husbands and wives kind of from the same households pulled together.
What you see there's kind of significant differences in reporting of how much cassava
has grown between men and women and which one of those plots is managed by men or women right? So
there's a disagreement within the household about how much cassava has grown or if cassava has grown
on those plots and who's managing them and the interesting part here is the plots with improved
varieties there was a specific question on do you grow improved cassava varieties you see the
same thing. So what does this mean what this means is there's a over or under reporting depending on
how you look at it or how many plots or how much of the plots managed by women are grow are growing
improved cassava varieties and vice versa with men. And again what that means methodologically
is traditionally if you look at adoption studies and you know a lot of adoption studies ask the
head of the household for what kind of varieties they're growing what you see here is there's a
significant disagreement within a household about adoption or not. So again this really raised a flag
for us to say well what does this mean for our methods that we're employing for adoption? Can
we think about how we could modify or improve them and again methodologically looking at this
some of the trait preference data I showed you we did you know similar kind of inter-household work
there where we asked men and women within the same household husbands and wives these were kind of
um uh dual-headed households what kind of trait preferences they had? So we had the rankings of
the different traits. What we did was have those interviews individually and then have them joined
to see you know how do things change in a joint interview versus the individual interviews.
And we use a trait ranking method called 1000 mines and what you see here is on the left these
are the different traits going down the middle here and on the left you have what the ranking was
for women individually women you know the wives and the husbands on the right and what happens
in joint interviews and what you see is kind of an averaging out. So in the joint interviews a lot
of the movement away from the more let's say extremes of the ranking really ended up being
um enmeshed kind of averaging to a mean. And that was interesting to us because our initial
hypothesis was in a joint setting, in a joint interview with the men's preferences be more
dominant right? With this end number of the negotiated preference be closer to the men's
preferences and that's not what we're seeing. So again just to say here we're doing a lot
of methodological work to improve the types of data that we're getting and refining the
methods and how we're rolling out those methods to get some of this information.
So kind of concluding this part of my talk and thinking about what this all means for the fields
um I just like to end on this call I would say for a paradigm shift and I'm calling it
a paradigm shift because I think we've had a lot of safe discussions around gender, gender
integration into plant breeding without really talking about the heart of it which is really
looking at critically examining these research processes and using some feminist STS lenses
and really starting to say how can we improve the processes? how can we start talking about
structural inequalities and power? and really flip the paradigm and what that means is instead of
thinking about integrating gender interbreeding goals which is what we do now on this kind of
blue arrow to your left is we do gender analysis within plant breeding frameworks right? We do the
sex-disaggregated data everything that I've just shown you in fact can we think about the reverse
how can we integrate breeding plant breeding outputs really to contribute towards gender
equality goals? So how do plant breeding products themselves become an instrument towards gender
equality goals and this is a shift of thinking um that really requires us to look to see how we're
doing research and understand some of the dynamics that I was talking about earlier in this. So to
give enough time for discussion I will stop there and be happy to answer your questions. Thank you!
Excellent! Thank you so much Hale Ann!
Okay so I don't see questions in the chat box right now
and I feel like the questions that I prepare in advance are exactly what your presentation was
about. So um I'm gonna ask part of one of them because it's just more like specific. So okay so
so I've been working in this position as Director of used to be called women in development then
gender and development for 16 years and so as we know genders and I work on proposals that
we right now and we know that gender and social inclusion is a requirement now for pretty much
all projects funded by International donors as women's participation has been in USAID and other
funded projects for over 20 years. But often PIs and the teams in ag and the project see this as
you said call the person in or do provide the service, do the paragraph, so as a box to check
and something that competes with precious funding right? Because we don't have funding so let's cut
out the gender component and I mean the funding to actually do work in the field which actually does
cost money just like the other work costs money. So what are some strategies that you have used that
you learned that can get beyond this and uh like like actually because I've done four-day workshops,
I've done on field trips with plant scientists and then at the end somebody will make a comment
that it's just like oh my God! Has nothing really gotten into them? Like well you know, Maria Elisa
I kind of feel like you're trying to change their culture by addressing gender
as opposed to changing their culture by addressing crop preferences or whatever. Anyway that's my big
question um that's my big question yes and then Larry has raised his hand. Yeah I mean I don't have
a perfect answer to that so how we've approached that question at least with ILCI, and you know
I've learned a lot in that process as well so in our RFP and choosing some of these
uh centers of innovation that I talked about in these five countries, we really had a
strong and you know again like you're saying it's a strong requirement to have skilled analysts on
the team right? And we tried to stick to that. So we really reviewed CVs, we really looked through that.
I would say despite all of that effort and ring fencing of funding that's another thing budgets
huge contentious issue and there's still an issue even where we had ring fencing of those
budgets within those broader centers right we asked that that budget be put aside that budget
gets reallocated. So we're seeing that over and over again I would say I mean at this point um
it's really hard to answer what's worked well or not. One thing I'm seeing that's worked very well
actually and this is something I don't have enough out of it and so on but it's anecdotal is have an
equivalent levels and hierarchy and positions for a social and biophysical scientist to co-lead. We
have one team for example where that's the case so you have two faculty members from a university
both professors, both kind of very well established, both are kind of at the same level. Let's say quote
unquote they're co-leading one of those centers that has been very different than a situation
where you have a breeder leading and you have a social sciences on the team and that's the power
differential and the hierarchy that kind of raised these questions that we're asking can we pull
out some of that in the interviews. So what I'm thinking now if I had to redo some of that work.
I don't know how you would put that as in his condition because a lot of the centers don't
have positions that are equivalent your breeders are often in much higher level positions decision
making you know your economists are kind of relegated even if there are social scientists. So
it's not something we can replicate but in two different instances with a great program
and you'll see that has been probably by far the explanatory factor for where teams do
really interesting work and really come together is when we've had that high level engagement right?
The social scientists is at the similar level. I mean one thing with the budgeting that you said
one lesson that opened my eyes from the power dynamics work and some of the interviews we're
seeing narratives around I didn't even know how to budget for this from the social scientists
right? I was put under pressure, I had to prepare something for this proposal. I didn't even know
how to start budgeting for the kind of work that we were doing right? And what happened is I under
budgeted and now I'm in trouble. So what I've learned from there is you know maybe even some
help with some of those social scientists in these breeding teams in this particular context to say
you know what is your budgeting and planning realistic because that's when things went
south and some of those teams were they didn't have enough money to really complete what they
needed to they couldn't tap into the other resources and the training piece is really
important but I see that more as a long a long haul engagement. I don't really see it as short
term that when I've seen some of these breeders really become champions it's been five
years of work. Really diligently slowly working with them I don't think we can expect workshops
to do that. It's really kind of a much longer term and that just that just means we need to keep
reminding and engaging with them and not just say okay they're done right? They've had their gender
training so yeah that's I'll stop there. Thank you! uh Larry go ahead and uh unmute yourself and
Thank you, thank you Hele Ann. Splendid presentation! A lot a lot to think about and if you had presented
the question of power dynamics before you presented the the decision rights I would think
you were setting up the question and then here's the solution decision rights table it explains the
power dynamics, it controls power imbalances, it it fixes things and that doesn't seem to be the case.
So tell us a little bit more about how well the decision rights tables do work? what are
their limitations? uh are there ways to use them more effectively than you've seen them used? or
or what part of the solution are they not a part of? and what can they actually help us
with? That's a really good.. But Larry introduce yourself first and I'm sorry and I was going
to write a note to everybody. Introduce someone you asked questions so go ahead Larry, please.
I'm Larry Vaughn and I work with Maria Eliisa at Virginia Tech, Center for international research
for many years. We're just there's just one one small office between the two of us separating. Okay
um okay I think the decision rights work um is about six months old so I don't think we're
ready to evaluate the effectiveness of it. Having said that watching how that process unfolded I
was kind of an Insider Outsider watching these discussions as not someone facilitating them
but really observing them. I did see several pitfalls that could possibly come from
it and again I'm just going out on a leap of faith here it may turn out differently.
What I was seeing is often the people who were tagged with some of these job categories
especially the gender Specialists socioeconomics person some safe choices were made who was put
into that position. So I think the system itself is kind of the uh what do you call it the
deck is kind of stacked in the right way right? So I see a lot of choices being met saying oh here's
our gender specialist, check. They're on the team, they have a decision right, they're probably going
to vote with me no matter what. So I don't see it as fixing the problem because who's actually
overseeing, who's being put into these positions. You wouldn't ever dream of a um what
can I put like a biotechnologist being put in a breeding position and that would be fine but
you see a lot for the gender positions right? You see someone who has any relevance for any gender
researcher has gone to a gender training once they're suddenly your gender person on the team.
So Larry I don't think it fixes it, I don't think it addresses the power dynamics when
you do have qualified individuals making their cases but in that particular case I think it's
more about making safe choices and really making sure that the people on that list are not going
to veto or challenge right? um again I don't know if that's how it'll play out but I know the people
involved and I see that that's what's happening basically. Okay, thank you, appreciate it.Welcome!
Go ahead, and raise your hands if anybody here I know we have a lot of people here with a lot of
experience because I know some of you. um so we have about six minutes left so left to get a hand
I don't see any
Larry did you really raise your hand again? I did, if no one's gonna jump in I want to take two turns
in a row. Okay go ahead oh and then Sierra. Oh I didn't mean to jump in front of someone
but maybe this will be a quick question. Okay that uh four-dimensional graph showing the
geographic and sexually sex-disaggregated preferences just kind of dilutes everything there.
Were to me what would I choose what would I choose? and if you're really empowering everyone to make
their choice based on how they self-categorize you would probably have seven or eight
or a dozen varieties you would have to keep in production instead of one. So ultimately it comes
down to having to pick a few how do you how do you um honor the equity or quality of access
issues you're trying to solve when it boils down to the actual labor of producing multiple
varieties for many many different constituencies? That's a really good question. So that's one type
of data but there are many other ways you can come to that decision right? So a lot of the
times what's called the product profile and that's description of an ideal variety let's say in all
the characteristics that it has therein. Ultimately you take that trade data it's not like those trait
each of those rows is a different variety right? You might find some overlap and the range is
within those you know rankings are not that large. So you may find that you can start building what
are called pipelines right? You can start saying okay and there's different gender analysis tools
that are coming out now for the plant breeding that enable you to start saying okay do I need
to add or take away traits based on some gender analysis of the ideal variety that I'm thinking
about? So it's less about each of those kind of buckets being one variety and more about the
diagnostic of looking to see if there's anything I'm missing right? Is there a trait that's coming
out strongly or weekly that I need to adjust when I'm making my priority settings? So it's
the way that plant breeding works you won't have more than two to three pipelines for each crop.
um I would say that's average for a crop for a country so it wouldn't they would never accept
something like that and I would say that's where the push spec often happens is oh I can't breed
for all of that don't throw all that complex data in front of me but if you're able to say okay but
look there's something here right? The poor and food insecure households in the Southeast this
trade is really important don't forget it right? Put it in your essential traits that
you're breeding for so it's more of a kind of a it's that's not the be-all end-all but it's
a source of information for you to feed back to the programs. Yeah thank you. So Sierra Vercillo
is actually our next Discussion Series Speaker in about a month. So please what is your question?
Hi everyone! Thanks uh so much for this presentation. I'm furiously writing emails
and sending them off to people um based on your findings because it is um interesting.
Some things I hadn't thought about um I guess it's a big question but I was wondering if you
could speak more about the bias of the industry of seed breeding and how that structural bias
um shapes sort of the gendered analysis and the gendered findings the output of those findings
or how those findings are then used and I'm just thinking about um potentially the bias away from
public reading from open pollinate pollination and from the traditional systems that people share
seed especially when they're related to food and poverty in you know drought prone in all sorts of
other areas. So I know it's a big question but um that those sort of structural issues I think are
really important to consider in this analysis. Exactly, no thank you, thanks for the question.
um Right there's two pieces to that puzzle. I think the structural and the historical. I
would say that the let's see let's let me put it this way the private sector multinational
culture itself is problematic and that coming into the public sector breeding programs itself
is problematic the how the public sector programs have been structured themselves
um is not free of bias for sure. So what I would say is yes historically you've seen a lot of
pushback. I would say resistance active resistance or just ignoring data that's coming out some of
the gender analysis some gender research some of the red flags that have been raised over the
years I would say are mostly glossed over because again structurally the programs are not ready to
deal with that and the people in charge are the ones who may be perpetuating some of those those
systems right? So they really don't really want to be challenged so it's a challenge and opportunity.
I would say I take it as an opportunity this demand-led market-led breeding right? The framing
of that being more demand-led actually to me has opened the door to some of us to say hey you want
to talk about demand? you want to talk about market? you can't talk about that in isolation of these
social dynamics right? This so so that's going to be kind of an interesting way of challenging the
public sector structure for food security breeding. Now what you're talking about on the
other ending is open pollinated versus kind of hybrids. They're I think an informal and
formal seed systems. There's a lot of also seed systems interventions that's the under half of
the puzzle I'm talking about plant breeding you get to the variety what happens with that variety.
I'm also seeing a lot of worrying trends in terms of privatization of the seed systems, formalization
of seed systems for a lot of these food security crops which don't do any due diligence as they're
scaling right? And it's just like oh we just need more of this in private sector and
more and more more and kind of just get the seed out there and everything will be fine
counter balanced by a lot of critical work saying No this is very dangerous
and we can't be doing this. So I think you know the structural inequalities in the seed system
are pretty well documented but who's reading them I think that's an interesting thing that
people actually doing the work. Often I find when I raise some of these issues about seed systems
they're a bit taken aback and I don't know if that's just because they're not exposed to that
information they haven't thought about it a little bit of sensitization there I think goes a long
way but also there's another seed systems project that I'm involved in presenting the evidence right?
Within that context I think is really important so I haven't answered your question. The way I look
at is bite-sized challenges to the system work well and collectively you kind of take a little
bit of seed systems a little bit of breeding and you kind of build this case towards pointing out
those biases through the pipeline comes together and really does convince people I find at least
not everyone but the key decision makers um that's where the weakest point is. Yeah so
I just wanted to thank you for that answer and I appreciate your optimism. You know I am
thinking as a sort of the political economist ecologist uh of sort of the questions around
who's whose demand right is being recognized and the you know exclusion if the goal or the
aim underlying development seed breeding funding is too privatized and not necessarily to reduce
poverty is I think a challenge. So I but I appreciate you know the framing of it
as an opportunity for potential change. Yeah that paper I flagged the whose demand paper is really
interesting for that so there is more critical work happening in that space and I think it's just
slowly bringing that into the programs as a reflection point. So the way I look at it is
like we're working with practitioners and you you you can fundamentally question the system
but the way I look at is you can work within the system to make those adjustments more
gradually at the same time as generating the much more critical work that helps inform that
um yeah so thank you thank you um thank you Siera for your question and your discussion there.
Hale Ann, can I ask you to stay 10 more minutes? Yeah we have two questions um one is Muhammad
Hasibur I'm going to ask this person to unmute introduce themselves and then uh Keith Poe hmm
let's see Hello Muhammad! Hello
uh I am a plant pathologist and I am working in a research institute as a scientific officer.
so uh I am working in a disease assistant variety development so I am so uh interested to including
gender responsive in uh my breeding program so uh this is midnight in Bangladesh and
I am waiting for so much interested so that I am waiting for your discussion and this is uh
this is under responsible anyone can ask about what's about transgender anyone can ask this is
although it is in the responsive breeding system we are only uh discussion about female or male
and uh this is my question and how we can reducing gender gap in our agriculture system and in uh it
is a uh I think it is a devastating in uh this is rural area in African region that a woman's
is a 50-50 equality I think in their work but in South Asia but woman is dominated you know
they are so much dominated so we need to explore in his rural area where it uh they are working
in uh or they are participated in agricultural system and uh this is my question under my uh
some observation is gender transformation approach or the gender transformative approach is so much
needed for collective learning and participatory approach and for qualitative and quantitative
approach so that woman's impairment uh is gained and socio-cultural outcomes nutritional outcomes
and agricultural livelihood outcomes is gained from this gender transformative approach. Thank
you! Thanks for the question um I think in your case I mean it's hard to answer that
question right? Straight off it's a big question but what I try to do is what I'm seeing a lot
within a lot of the countries that we work in there are academic institutions where there is
kind of pretty interesting critical research happening around women's rights and gender
equality but often those University settings and academic studies are not linking with the
AG research centers and I think that's another systematic issue right? That those two
ends of the spectrum are really not meeting. So in your case I would think you know who or is
there someone in country because a lot of the issues would be highly contextual that would
need kind of further research and synthesis of knowing what the constraints and barriers and
what the issues are before you can formulate an intervention who is doing work around gender and
agriculture right? Here in Bangladesh so there's been a history of work in general agriculture in
Bangladesh is probably one of the most data rich and interesting places really drawing
on local expertise to say to ask some of those questions together right? Partnering with someone
in country who has that experience and you're in a particularly advantageous position in Bangladesh
because there's a lot of work that has happened over the years and really kind of working together
to formulate research to answer that question and then see how that comes back to your breeding
program> So I guess what I would advise you is you know just looking and I don't know how you
would do this through informal networks or formal networks to identify the right research partner
and then you can have a lot more long-term research together and that's worked really
well for other contexts where you do have that pairing of the in-country deep and knowledgeable
social scientists with the plant breeding institutions coming together to do research. Yeah
okay um Keith I'm happy to read your question but if you don't mind
um you're also welcome to unmute however you like and introduce yourself. Please
uh see I don't hear you I'm gonna go ahead and read it in case uh there's a problem on
your end with a mic or something. So Keith had written I was wondering about the practicality
of managing such a diverse geographical reach I assume that needs plenty of resources money
and time or does each geographical area have its own autonomy thanks for the question Keith
yeah um just to make sure I'm understanding this geographical reach in terms of the
varieties being released right? um is that or does the geographical have its own autonomy
um I need to understand the question a little bit more so in terms of if we're thinking about
plant breeding products and the reach and understand the social heterogeneity within
each country that's a huge undertaking. I don't think we can convincingly say we have a command
of all the countries and also social heterogeneity they're in usually what we try to do is start with
you know I'm thinking again this is super over simplistic and there's problems with that as
well thinking of the crop that you're breeding for plant breeding happens mainly in silos of
crops you breed crop by crop you don't necessarily breed for a farming system you breed for a crop.
So usually the way people start is you know the production zones where the highest production for
that crop is where you kind of stratify your sampling and then within that look to
see where there may be other limitations or other targeting. Maybe there's areas you haven't reached
um so I would say we don't really go for nationally representative data collection
if you're thinking about data collection if that's what the question was about
um oh I see I see you're on your map you're all over Africa and Latin America okay so they're the
so so what you're asking there is working across different contexts I mean that's less problematic.
I think because we're not actually driving the research there we're kind of working with
the institutions and each institution has its own team and that was a part of the RFP right? That
there's there's real contextual research in each country so we're not kind of going from country
to Country and designing research for anybody we're more of a backstopping kind of support
network right to see can we help link people where they need to be linked especially like
the example I gave in Bangladesh sometimes you have there's no one on my team how do I
link with the right person? can we start helping that happen sometimes. We identify consultants
in country but really the the research is highly contextualized and driven by the teams and country
um so each team has its own autonomy yes each team does its own research agenda setting and design
that has worked somewhat well really heterogeneous in some cases but that's the nature of kind of
how we designed it so yeah it can be really expensive and it can be really variable. Yeah
got it okay let's see am I still unmuted Yes okay great well thank you
um many of you have stayed on I know a few minutes here with us and thank you hale Ann uh wrote me
late last night saying she thought she had COVID she was feeling very sick and I was worried
she would not be joining us. Thank you so much despite your recent long trip and not feeling well
um you did a great presentation and we had a really nice conversation. So I really appreciate
that and thank all of you for attending um as you know as I've said we've got a short survey.
Lumbini, maybe you can send it out again and I went ahead and put in there the note for our final
um in November 10th we have um Siera Dr Siera Vercillo from the University of Waterloo who will
be presenting on some systematic a systematic review of literature 260 studies published by
the web of science on gender and climate change in Africa. So that's exciting. So look at our website
um if you do get um add yourself to our listserv we don't send anything out that isn't specifically
gender and international development you won't get spammed I promise. So thank you very much and
um I'll I'll be back in touch with you Hale Ann in a minute and uh great!
I appreciate all of you being here. Thanks for the invite, thanks for coming everyone!