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IGF 2018 - Day 2 - Salle XI - WS156 What does the data say? Analyzing the Gender Digital Divide

The following are the outputs of the real-time captioning taken during the Thirteenth Annual Meeting of the Internet Governance Forum (IGF) in Paris, France, from 12 to 14 November 2018. Although it is largely accurate, in some cases it may be incomplete or inaccurate due to inaudible passages or transcription errors. It is posted as an aid to understanding the proceedings at the event, but should not be treated as an authoritative record. 

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>> MODERATOR: Good morning.  We're here at today's panel, "What Does the Data Say?  Analyzing the Gender Digital Divide."  And we have with us Aileen Aguero from Latin America, Alison Gillwald from Africa, Muge Haseki from University of Pennsylvania, Helani Galpaya from Asia‑Pacific group, Claire Sibthorpe from GSMA.  What we will show today are the findings from a large survey, in 20 surveys from the 2017‑2018.  Also some case studies.  Um ... this is in terms of the after access survey, this is around the fifth round of surveys around, Asia, Africa, comparatively finding from Asia, Africa and Latin America.  The world case studies will show who are connected, what works, how to connect, unconnected with a focus on women.  We have practitioners, researchers and think tanks.  This is particularly interesting from the demand side perspective, what are the inequalities in terms of gender, they usually mirror the inequalities of the world and enrich the policy design.  So let's start.  Alison?  Thank you. 
     >> ALISON GILLWALD: Good morning, everyone. 
Good morning, everyone.  I think we usually don't start the panel until there are more people in the audience in the panel is sort of our thought on this.  I think we have just got there.  So we can begin.  Thank you very much for getting here early to attend this session.  I'm going to just introduce the after access surveys that were done over 2017‑2018.  This is the first time the demand site surveys have been done using the exact same methodology across the global south countries we cover.  Traditionally Asia and DOCI have done bottom of the permit studies.  So they have gone back some way.  We have done these several years in Africa so we have longitudinal data.  The original grants covered from the IDRC, international development research center in Canada, are the ones ‑‑ blue ‑‑ sorry the ones not in yellow, completed.  The other studies completed by Swedish CETA are under completion.  Some are completed and will be on the after access website shortly.

Just a few points about the countries that are being studied and the methodology being used.  This is a nationally representative survey.  We work off the national census display.  And do a nationally representative sample and do a proportional sample and a listing of the numerators, identify the households, and there are three sampling periods to make sure the data is representative. 

Perhaps it distinguishes us because there is a lot of gender data out at the moment.  Historically studies done by the GSMA and Claire will talk about the studies done.  There is another study out using Facebook data.  Big data.  What you will see is that the social networking data and access data connectivity data mirror each other.  There is enormous similarity there.  The point is you can get the basic connection data, although historically there have been problems with the supply side data.  And with the certain Sims.  The only way to find out who it belongs to, get the data, model that data ‑‑ which is in relation to the big data used.  The big data can identify the connectivity from the algorithms and data that we're receiving, they can determine probably the likelihood of that person being a man, woman or other.  But what they can't do is actually say what they're doing, what a barrier to use, those kinds of things.  That is information we can only get from the demand side data.  I want you to emphasize that.  We will see similarities with some of the data.  The problem is we don't have data at the global level.  We only have the country, the regional insights.  And the country insights are actually even more specific.  The context is actually critical at a country level. 

Thank you.  So just to show you the very high level data, that is the integrated data for everybody at the national level, you will see that essentially, Africa is still continues to lag the other countries.  There are some similarities across the African and Asian countries.  Latin America is far ‑‑ you know, the penetration levels are far greater than in the other areas.  Essentially, what we're seeing is Internet penetration, mobile phone penetration and media use, the little blue block you can see there, it actually track GNI or GDP per capita.  The countries doing ‑‑ that are richer, basically, have better penetration rates than the countries that are poorer.  There are anomalies there that are quite important that we should also see.  For example, South Africa fits from a GNA point of view more comfortably in the Latin America countries, but the penetration rates are not as high.  There are enormous inequalities that are masked in some of the figures that you don't see.

Interestingly, in the other slides people will speak about some of the other regional variations.  For example, Rwanda which is highlighted as a connectivity example by the World Bank, ITU, et cetera.  Has less than 10% penetration.  The lowest penetration of the countries, with the highest gender gap, in fact, of 60%, very like the Asian countries that Aileen and Helani will speak to.  We'll some back to some of these, but basically, what we're seeing at the global level is correct in terms of some of the other data coming through.  But we can't go beyond the connectivity data, just the descriptive data from the big data or supply side data.  So we need to do this demand side data where we can actually do the modeling and we can identify the exact points of policy intervention.

We see from the modeling, for example, the main drivers of the inequality are education and income.  And so addressing the gender issue is actually about addressing the education and income.  You have to do the modeling to get to that data.  Let's go back to the descriptive statistics.  (Off microphone)
     >> Okay.  To begin with, we wanted to show data on smartphone ownership.  You can see in this slide, basically Latin America, most people have ‑‑ they know ‑‑ they own smartphones.  This is important because this is an opportunity for them to come online.  While in Asia and Africa, there are still more challenges in that regard. 

When we look at the smartphone gap ...
This is the smartphone ownership gap, the male‑female gap.  As we can see, in Latin America, again, this gap is not that significant.  But you will see later that this gap ‑‑ smartphone ownership gap is much smaller than Internet use gap, for example.
Still, there are challenges, for example, for India, Pakistan, Bangladesh, Mozambique, and other examples. 

This is another gap in terms just mobile phone ownership.  Here, we find the gaps are a little bit larger.  Again, in Latin America, not that significant.  All‑over indicators ‑‑ you will see ‑‑ I'm from Latin America.  So the thing is that even though we find this ‑‑ this rather small percentages in terms of mobile phone and smartphone ownership or maybe you will see there in terms of Internet use and social media use.  There are many issues that are masked in these figures.  From qualitative studies, we have found that there are still challenges for women when they are online.  We will see that the situation is the same in Asia and Africa.  All the stereotypes are reproduced in the online world.  Women are expected to just use the Internet for beauty tips or help children with their homework.  Or to look for recipes, things like that.  But men, they're expected to use it for work, yeah, to get to the news.  Many things like that. 

These opinions come both from men and women, so this is a really hard challenge.

Going back to this is the (?) gap, which is much larger.  We not only have the problem for women, but also for those in the rural area.  In Latin America particular, maybe you want to commit on Asia and Africa.  These are related to geography isolation, it is not economically viable to offer the service there.  Especially my country, where I come from, like, in Peru, there is the Andes, the jungle, this is a very hard issue to deal with.  Would you like to comment something on this?

     >> Perhaps differently, in Africa, we have seen in many countries, there is actually 90% GSM broadband coverage, 3G, 4G, and yet we have penetration rates of less than 20%, even though they might be smartphone ownership of 50% from in situ for example.
Although technically available, it has reached ‑‑ in the rural communities, it covered large parts of the court reporter, large urban areas where people cannot afford the service or the device.  It is not only coverage and reach issue.

     >> So I think Asia is interesting.  India has a high gender gap, as does Myanmar.  Myanmar is the most receipt  ‑‑ recent country rolling out a network.  They have done well in reaching out.  The rural areas still need coverage.  The 33% gap.  India, same, rural area is ongoing.  Pakistan, Bangladesh are the interesting case here.  Pakistan has historically had one of the few successful universal service funds in the world, properly managed and actually connecting up rural areas.  So that is why you see quite a lower rural gap in Pakistan.  Bangladesh, which is incredibly flat.  There are operators after covering two areas went completely rural and started covering ‑‑ it has never density in most areas to cover in the rural area, you see population dynamics working as well.

     >> Thank you.  We wanted to show the divides or gaps in terms of Internet use and social media use.  Yeah, it is here.  We had to separate model social media.  We found out during the pilot phases, in many cases people didn't know they were coming online with social media.  They said we use Facebook and WhatsApp but don't use the Internet.  Without knowing it, they were having an opportunity to use and get benefits.  This is a much larger gap with the smartphone ownership. 

Again, as I was saying in Latin America, even though the figures are not as large as in Africa and Asia, there are many, many problems to deal with. 

Finally, we wanted to show the gender gap in terms of mobile money use.  You can see in Kenya, it is really small because of the tradition that is there in this country.  It is still high in India ‑‑ in Nigeria.  In Paraguay, it is not that high, the gap, because of the special focus on promoting mobile money.  They had a special regulation, and they are trying to get more people into using this, especially women. 

Now, we will continue into the next one.  Why is it that you don't have any kind of device?  Not a smart one, but why do you not have a phone?  You can see ...
The most common reason given in most of the countries is affordability of the phone.  So even though we're talking about even smartphones being under $30, the Chinese and Indian‑made smartphones.  They're incredibly affordable when you look at national level income statistics.  When you go to the lower percentiles, they're increasingly unaffordable.  And these are cheap phones that are less than the $40 smartphone.  If you talk about a country like Myanmar.  They want the $300 Samsung.  They will delay purchasing until they can afford the expensive thing.  Not asking about the price, but people's perceived affordability.  Affordability in the multidimensional ways is still the biggest barrier. 

The second biggest ‑‑ that is the yellow boxes I had. 

The next one is not knowing how to use a phone.  They asked people for the main barrier.  In about five countries, you see quite a significant barrier as the main reason, which is I don't know how to use it.  These are things that can be addressed ‑‑ sorry.  The slides have a life of their own.  Ha‑ha.  And interestingly, in Africa, as you can see, the red dotted line, Nigeria, Rwanda and Mozambique, we have electricity as a barrier.  This is interesting, something you don't really hear in Africa.  Not being able to charge the phone because of no electricity in the house.  You see the regional differences when it comes to other supporting infrastructure.

Then we asked them ‑‑ that was about the device.  We asked them, why do you not use the Internet?  And in this green highlighted, these are by the way, the high population countries.  We have India, Nigeria, Pakistan, Bangladesh, Ghana, but still.  In all the countries, not knowing what the Internet is, is a huge barrier.  There is an awareness barrier to be crossed.

Then if you look at the bright blue that I have highlighted, you can see most of them are kind of to the left.  So the richer countries.  Because this is ordered by richer to poorer.  The barrier is not knowing how to use the Internet.  So they know what the Internet is, unlike Nigeria and Pakistan.  But they don't know how to use it. 

In some of the poorer African countries, interesting South Africa, which is not poorer African country.  You have a large percentage of people that say I don't have a device, and that's my main barrier.

We had a module on other use.  We asked them what other applications you use, we asked them about what things put money in the pocket, save money and increase efficiency.  Here are two things, about the usage of apps related to transport and trading.  e‑Commerce.  And this is about the use of these as a consumer.  Not the selling of labor as a driver, but the ride sharing, for example.
Have you used this?  You will see these are low levels of use.  Most of these countries will have the ubers, and big grab, we think they're common.  We come here, we use it.  We go to Myanmar and use it.  It is incredibly low use, that is the first trend.  This is about using.  I can't tell you the people that are selling their labor, selling their goods on the Internet, getting jobs on the Internet and earning income because they're statistically low numbers.  It cannot be discussed.  It is not pervasive, the impact of earning through the Internet.  As consumers, there is use, in the 30, 40 range in Peru.  That is high.  Everyone else really below 20%.  Some of the gender gaps, you know, you need to take it with a grain of salt.  2% and 3% that is huge, but that is within the margin of error.  Others, there is large gender gaps, Peru, Ghana, et cetera.  On average, men are more likely to use the apps than the women are.

Let's not try to read this, but let me talk to this.  We asked a module about what is your social media behavior?  What do you share online about your level of trust, so on?  As you can see, in most countries gender, real name, edge, and some the platforms force you to share it, you don't have a choice, especially if you post photos.  Almost all countries, religious, sexual orientation, political views these are shared the least to a public group.

Don't try to read it.  This is red in a country that is lower.  Green is higher.  You can see quite consistently, if you look at a country like India and Pakistan, women are continuously in the red column.  That is they share less consistently less all of the things compared to men.  In Pakistan it is the same, in Mozambique, it is the same.  Other quality research we know.  In Asia more questions about harassment.  Men report higher incidents of harassment as a percentage of men.  That is interesting.  The question is problematic.  Have you been harassed in these ways, five types, physical, threatening, sexual harassment, but men are online more frequently.  We need a better measure, like airlines, the seats, and miles flown.  The number of times they're online, this will equate out.  When people are harassed, where are you harassed?  Mostly social media, the platform.  The reaction?  The problem is I limit my use, I completely go offline are answers we get.

In countries like Myanmar, Cambodia.  Minorities have a majority account.  Muslims have Buddhist accounts.  Some people have two accounts they use every day.  It is not just I have an account.  In participating in religious and other discussions, there is a different identity for the public sphere because of the problems and harassment many of the people face.  Alison?

     >> ALISON GILLWALD: So the thing about the research, as we were saying is we have shown you here some of the high level statistics.  We have desegregated the data.  The descriptive statistics can mask things that the modeling allow us to see.  The important point of what we're seeing here, about the participation and inequality of the participation actually relates to, you know, fundamental development issues we faced all along, correlation of inequalities of income and allow you to participate.  Interestingly, as we move from the voice to data to Internet world, the complexities of it, the challenges mean that the human development challenges become even greater than they were with voice.  That your ability to participate not only from consumption, which we mainly focused on here, but your ability to produce on the Internet, optimize the Internet for well‑being and also national growth, et cetera, are very dependent on addressing some of the fundamental issues.  So, you know, the central policy question is that in fact, as we are connecting more people, a central paradox, is as we connect more people, we see greater inequality.  Not only inequality of those online and offline, but between those producing on the Internet, using it optimally and those barely online, able to just connect for a few minutes on the price of the data they've been able to buy. 

So the other important thing we haven't had much chance to speak about, but Helani has spoken about it.  The quantitative data, it will address certain issues and unable to address certain other issues.  The quality of research that goes to understanding some of these is equally important.  And also reflected on our various websites.  But I think the most important thing that is possible through the modeling and also required far more extensively in the qualitative work is understanding the intersectional nature of inequality, once you begin to overlay in a quantitative and unsubtle way, gender, rural, all of these things, you can do with the data, one can see, you know, it is rural women in certainly areas that are more marginalized than others.  It also provides a granularity.  For example, in some countries, poorer urban women have greater access than rural men, for example.
So they ‑‑ you know, rural urban divide is as important and equally important and very much attached to income ‑‑ and one needs to understand the way to address them from a policy point of view.  Essentially, you know, we keep speaking about getting things equal online.  Digital rights online.  Digital equality online.  In fact, these are restricting structural equalities and economies in society that need to be addressed and often require much bigger political and policy interventions than simply a connectivity, infrastructure, you know, reduction of a service price.  Although those are important things.  Broadly, on the last point of the broad policy implications of this are, yes, there are inequalities of men and women generally across the enormous data sets with qualifications and variations in different contexts, but that inequality really, you know, we require multiple strategies to get everybody online, because women are concentrated in the bottom, concentrated amongst the disconnected.  The strategies that get everybody online will get women online, too.  We saw that with mobile phones and mobile voice as you approach saturation.  Everybody was online.  You got a quality between men and women, actually, women had more access than men in several countries.

Short term strategies are really about finding different models that can reduce prices, finding ways to reduce the barriers.  So the taxations that we see in the social networking taxations, the taxation on handsets, the countries committed to digital divisions.  That is no good.  We need low‑cost devices, we need affordable, public access.  Increasing public Wi‑Fi strategies, so people can buy the cheap device, buy the data they can afford, and access various other services, communication services through public forums.  We need to find ways to reduce spectrum and find ways to reduce cost generally, so we can get more people online.  That will bring more women online, too. 
     >> MODERATOR: Thank you, Alison.  Move on. 
So Muge Haseki from the University of Pennsylvania. 

     >> MUGE HASEKI: Good morning, everyone.  I'm Muge Haseki and with one world connected.  Today, I will be giving some examples and sharing some stories from our case study project.  So to begin with here, you so a photo that shows what happens when there is heavy rain in rural areas.  Especially with poor infrastructure.  But what you also see here are two men on their bikes getting around the muddy roads. 

So one of our projects actually show that just along with the findings in existing research, infrastructure affects women more than men.  So one of the projects we have focuses on rural areas and (?) for which health centers are provided mobile phones, the health work ares are provided mobile phones to help with pregnant women.  But when there is heavy rain like that in rural areas, it is much harder for pregnant woman to be mobile and access to health center.  They cannot, you know, actually get on the bike, go to the health center to use the resources.

So after this challenge, they came up with a different idea.  They decided to give the mobile phones to young health workers, so they can get on their bicycles and go to the houses of pregnant women in rural areas.  But then what happened is the young woman who were given ‑‑ young health workers who were given bicycles got some resistance from the community, because men and local opinion leaders, very resistant to the idea that women are riding their bikes in rural areas. 

So this is just an example to show not only the difference of what happens, like, the inequality between men and women like the structural inequalities, but also there are differences we see within women.  In terms of their age or sociocultural norms like that.  Or their marital status.  That affects them from accessing resources.  So our ‑‑ the couple of arguments we draw from our key study, which is along with what Alison Gilbert emphasize on entire sectionality.  Women in terms of access and use, there is constraints with respect to demographic, such as age, education level, marital status, geography and social cultural context.  Relaxing one barrier may not improve use, and therefore, sample target for the group of women may not be effective or cost‑effective.  We need an entire sectional approach to interventions and policy and we should look at the immediate local context of the women.  Let me back up and give you little bit information about our project at the University of Pennsylvania.

Over the past couple years, we have been identifying and compiling grass root level initiatives that focus on connecting the unconnected communities and facilitate adoption and use.  We have identified more than 1,000 projects and conducted 120 in depth interviews with the grass root level organizations.  And these focus on gender, education, literacy programs, agriculture, e‑Government and as well as supply side intervention such as extension of coverage.  So these are ‑‑ I'm sorry.  (?)
     This is the snapshot of the 15 case studies from across the world.  Which I will give some examples over the course of my talk, mainly why we should focus on entire sectionality, I will be sharing some stories from the case studies why this is the case.  When you look at the existing literature or research from surveys.  There are some overlapping barriers to women's ICT access and use, such as infrastructure, financial constraints, safety and security, digital skills, perceived benefits, sociocultural barriers.

As I open up in terms of infrastructure, when you look at the specific barriers, women also face some unique challenges and maybe those challenges exacerbate for certain group of women in certain areas. 

These are two different case studies.  This is from Nepal.  They provide mobile phone applications to facilitate communication between pregnant women and the health workers in rural areas in Nepal.  On the right‑hand side, you see a young woman in Ghana at the telecenter, they are provided some digital literacy skills.  It is a project by Africa ICT write.  So when you think about the financial constraints, the two different groups of women face different challenges when it comes to financial barriers or access.  So in the case for Nepal, for instance, when people are married to Nepal, they move to their husband's house and most of the time, their access to mobile phone is controlled by their husbands and their mother‑in‑law.  So when they want to get data for instance, their mother‑in‑law thinks okay, if you have the data, so other woman in the community would come and like to use and ask or request to use your phone.  So that will be like costly.  So they discouraged them from getting data for that reason.  But then, when you look at this young woman on the right‑hand side from Ghana, so they get more constraints from their parents.  Because they are taught they are already provided ICT classes in their schools.  You know, they don't think they need to pay extra money for them to attend these classes.  Sometimes the classes are free, for them, instead of going to the free classes, they can use their time to work outside of the home or to help the family.  When it comes to safety and security, we see women from different social and cultural contexts face different barriers.

This is one project, one case study based in Bangladesh.  It is by isocial.  So initially, they came up with the idea of opening telecenters to facilitate women's access and use in rural Bangladesh.  What they found out from the first photo here, when they open the telecenters, only or most of the time, men use the telecenters than women.  So then they again, they had to adopt the project for which they provided bicycles to women who can go and visit young woman in their homes to provide them resources.  They provide one‑on‑one digital literacy training or provide one‑on‑one information on their tablets to those women.  Again, they face resistance in the community by their opinion leaders.  Similar to the case in azul that women are not encouraged to use bicycles.  Especially young women who are single. 

So for young women in Bangladesh, the most safe place to do that is home.  In Sri Lanka, they have the different information in terms of what is the best place to access the Internet.  Or whom they feel comfortable with talking.  Again, in Bangladesh, in rural Bangladesh, women mostly need the kind of information about like woman related health information.  They only feel comfortable with woman.  Like the case in Sri Lanka, they found themselves more comfortable at telecenters around the temple with people whom they already know.

In terms of perceived relevance and benefits.  Again, when the programs create the curriculum, they need to take into concentration the needs of the woman they're targeting.  On the left, you will see a woman from rural Rwanda, who is a farmer.  And they usually need mobile phone to access information about the sellers and buyers in their areas.  Or the cost prices.  These are mean ‑‑ kind of like information they need through the mobile phone use.  Whereas, this is another project in South Africa, they are provided a mobile application for information about maternal and infant health.  They may need mobile phones to communicate with other mothers to ask for advice, recommendation or get information related to health. 

So when you ‑‑ even providing just one like ‑‑ like one structure curriculum, the targets all might not be useful because they think that targets or addresses their needs.

So when the interventions or digital training programs just focus on basic, you know, literacy skills or how to use the Internet to find jobs or how to like search information in general, that would not be ‑‑ that would not be useful for them.  They would not see any perceived benefit.  So the programs, again, should address, you know, what the needs of the woman are and how they can create a curriculum that woman would find the most useful. 

And in terms of sociocultural context.  This is a photo from grand mark, in India, a community network.  This photo shows that they facilitate the access of woman to the network, especially in the dark.  So this is a house they identified in their community where they can all gather to access the network.  And the one benefit of the community network leader is a woman, so they find more comfortable to speak with.

One of the questions we found out, one of the most common questions that come from woman was questions about abortion.  Which is again, taboo for woman to speak with other people in their community.  So when they ‑‑ and most of the time because they share their phones with their husbands, they don't want that kind of information to be visible to them. 

So what they are asking to the community leaders is how I can search information on abortion and yet my husband would not see it on the history.  So these are the kind of sociocultural barriers even when they share a phone they cannot or are scared to search for information they want, because they don't want it to be seen by their husbands. 

Again, when we think about access, they may have Internet, they may have data, they may have device, but again, they would not be able to search for information if they know for fact that their husbands or their mother‑in‑law will not see that information. 

So going back to our main arguments.  So woman, based on where they come from, whether it is rural or urban, whether they are single or married, they have different aspirations, motivations and needs.

For that reason, relaxing just one particular barrier, infrastructure, access or sharing devices may not improve their access and use.  Therefore, the policies just target mainly woman and thinking woman is a homogenous community would not help all of them.  Therefore, just along with Aileen Aguero ‑‑ Alison Gillwald words, we need to create more access in creating the programs and policies.

     >> MUGE HASEKI: Thank you so much.  My contact information, if anyone would like the 15 case studies on gender, I would be happy to share.

     >> MODERATOR: Thank you.  Claire?

     >> CLAIRE SIBTHORPE: I'm with the GSMA, as Alison mentions, we do a lot with that specifically.  I lead the program that looks at gender gap.  We know mobile is the main way people are accessing the Internet and may be of ‑‑ many of the services.  It is important to look at what is happening in terms of the gender gap.

We do an annual study in terms of gender gap and ownership and use.  We have the same findings.  It is great to see we do the big studies and find the same issues, which is good, and slightly alarming about the challenges we have to address.

Our research shows that there is an ownership gap, which is preventing women from having basic access.  But a much bigger usage gap.  So if you look at low, middle income countries, women are 26% less likely to use the Internet on their mobile phone than men.  That is a local ‑‑ low, middle income figure, it depends on where you are located.  In south Asia, women are 70% less likely than men.  These are staggering numbers for women that are excluded. 

There is financial information for women that can't get access.  Women are 33% less likely to use mobile phone.  On the fin dex data.  We have research on this topic.  We do household surveys, qualitative research to understand that there is a problem, you have to understand the reasons why and what are the opportunities to drive closure of the gap.  After we published our 2015 study, which looked at the issue, the members that connected women commitment initiative.  They're making formal commitments to reduce the gaps.  They set a baseline and target.  That is important.  It is not just sufficient to say we will tackle this issue and address women, you need concrete data to inform it.  What is the baseline, the current state of affair.  What is the target?  What are you aiming for?  How do you measure that?  If you don't have clear targets, it will be hard to work on that.  We're delighted.  We had 36 offers to reach 56 commitments to reach women.  They have now reached more than 12 million more women through the efforts.  What have they been focusing on?  The issues that our research is identifying.  That is also why this data is important.

First of all, to make the commitment they had to know the gender gap for their customer base.  You would think that is easy, it is difficult to have it from the surveys but the specific customer bases it can be a challenge.  Many cases especially in south Asia where social norms prevent a woman from going to a store and get talked up.  Many men are registering on behalf of their wives and daughters.  You might know the customer that is registered but don't know who is using it.  At GSMA, we have an algorithm where it will look at the data, predict.  Over 85% accuracy predicting what is the actual user of that SIM card.  Because that is an important step in terms of aggressing this issue.  It is a tool kit that is publicly available, it is always available.  Our members are starting to use that.  It can be used by anyone that has ‑‑ I think it is important for anyone that is ‑‑ anyone that has customers to look at that.  How to correctly identify the gender.  Once you know what the problem is, and you kind of looked at not just the kind of national level, but also looking at urban, rural, different age groups, women are not homogeneous.  You need to tackle the barriers women are facing.  The structural inequalities with men and women, education, strong social norms.  Having said that, as Alison was saying, you know, there are some practical steps that be addressed while the big problems need longer term intervention.  Our research shows similar affordability is the number one barrier in terms of ownership of phones and data costs of accessing Internet data.  One needs to tackle affordability.  Women have often lower incomes or less control of the finances.  Our research shows that even in contexts where women are earning income, in some context because of social norms they're not the decision‑makers around the purchasing of phone or data.  There are constraints around that.  The barriers are affecting men and women, but affect women disproportionally because of the norms.

The accessibility, it is access to I.D., access to agents, as in context, women can't go out of the house as easily.  What women are doing is having female agents in contexts where it is not appropriate to meet with a male agent, roaming agents, tiered IC.  Policies to make it easy for your people to access the services. 

Another key issue reflected in the conversation is behind relevance.  How do you assure the products are relevant to women.  People understand what is it women are using.  Research in south Asia and countries in Africa, that locked at if you removed affordability, looked at a certain income group, removed lack of networks, what is stepping women from using the Internet?  They can afford it, they're in an area with coverage.  What is stopping them?  What is the opportunities?  We highlighted the main desires and needs for what was triggering their use.  A lot of it was behind having video calls with friends, family, practical things people were wanting to do.  I think understanding what is relevant to the different segments and groups is critically important.  Skills, again, another big issue.  Not just the skills to use the Internet but awareness of how it is relevant to them.  A lot of the research highlights that is something for others, what rich people in the cities do.  So you know, how is it relevant to people's lives, making sure we understand how it can be used. 

Another big barrier is around safety and harassment.  We did a study in 2010, it wasn't a barrier.  In 2015, the third larger.  It is seeing it increase.  Online bullying, of women.  Harassing calls from strangers, more people have access and these issues grow in experience.  Some of the members are doing practical things like call blocking services, anonymous pop‑ups you don't need to give away your phone number to reveal you are a woman to try to make yourself feel safe and protected.  That is an issue of growing experience.  There is a range of issues, it needs to be tackled holistically, ours is similar to what University of Pennsylvania was sharing.  You node a holistic approach and we see partners tackling them in a holistic way across the barriers, that is the biggest impact.  You can't just tackle one.  It nodes a lot ‑‑ it can't just be done by private sector allow, it is interventions needed from many other groups, like the system issues that are being faced, which is a longer term to tackle.  It needs a multistakeholder approach and strong focus and intervention, based on the data.  The data can really highlight where the issues are, what to do to address them.  In absence of that ‑‑ sadly, there is too little of it ‑‑ it is hard to both take action and measure progress.

     >> MODERATOR: Thank you.  It is incredibly rich set of data in depth data.  And a lot of us, I think, you know, we have been studying this affordability and all of the barriers to connectivity, know about.  But what we see here, I think that is where the different level of in depth about knowing the details of the barriers and the ‑‑ you know, the drivers in general.  So we'll open the questions, the Q&A for the audience.  But just a small question to keep in there.  And we'll gather some in the audience and with the remote participants to the panel. 

There was many, many things.  I think we would need to write a book about all of these things.  Including, you know, striking things such as increasing connectivity and increasing equality.  And the intersection between all of these.  But I think ‑‑ Alison, you were mentioning the fact that the importance of a higher ‑‑ you know, an intervention at a more structural level.  Yes, it is long‑term but also urgent.  It does reflect structural inequality.  We talked many years about increasing spectrum and doing all the things we know in terms of regulation.  But we need an urgent intervention at a more structural level.

My question directly is, in your findings, do you see anything ‑‑ Helani, you mentioned in Pakistan, universal funds work.  Which is not always the concept in other countries.  It is because of the governments, spend the money or whatever.  Do you see an association between good policy and ‑‑ this is a more general question for the panel.

So should we open up questions from the audience here?  Do we have remote questions here? 
If not, maybe you can start with mine. 

     >> Um, yeah, I think, yeah, absolutely, there are short‑term things we can do.  You know, I think especially when one is doing the micro studies, as important as they are, it is important to have the systemic outputs, the systemic outcomes to address them systematically.  We speak about affordability, but we have to understand that in the context of the competitive markets, much the regulation that is there, if we're going to address them, we have to do it in a sustainable way.  For example, in many countries in Africa, what we are seeing now is the political pressure to reduce prices and prices have been reduced significantly.  What we're not seeing is further investments in the markets.  So that is actually expansion of the Internet is being inhibited, you know, because they are simply not the investments.  I think it is a tricky thing.  We have to actually be thinking out of the box in a new way.  We have to think about new ways of licensing, think about new ways of regulating the market and using universal access service funds.  They're not used effectively.  Not delivered to the poor.  Poor aren't (?).  Where are the big funds.

Let's use them for public Wi‑Fi, it could be something more successfully address, instead of the incumbents, in a very often expensive technology network.  We need to think about what technologies we use so we can get lower cost business models to use secondary spectrum, to enable community networks that are scaling and ready to offer services and move away from the big national licenses that, you know, don't use up a lot of the spectrum in the rural areas, but can be used at much lower case to reduce services.  Governments need to not speak out of both sides of their mouth.  Shouldn't be putting pressure on operators to not bring down prices and not make it available to them and bring down the prices to use the spectrum more cost‑effectively.  Also, same time, putting on the great big taxes on devices and now on social networking, which in Africa is used very much as a cost mechanism to overcome the high cost of voice and text services.  So data is expensive, it is much cheaper to use than your traditional voice and text messages.  So it is a really ‑‑ intervention, although made on the grounds of good taxation.  Not redistributed, not built into the system to support it, sustain it, extend it.  So just bringing down the costs will bring more people online, bring more proportionally more women online as well.  They're the ones offline.

     >> I will say one thing, again, the idea that at this point in most of Asia, if you increase connectivity in general, you are increasing the gender gap because it is mostly rural women not connected in Asia, right?  One of the biggest problems many operators will tell you is right‑of‑way.  So there are big incumbent operators that own fiber ‑‑ not even incumbents, large operators, maybe new ones.  They're not often forced to share it.  The remote base stations are running microwave.  Many have an interest in now running fiber.  You have to negotiate with 20 different government departments and maybe 50 farmers who have their rice fields between point A and B that you are trying to lay the fiber with.  The local governments do not facilitate this.  All of this increase time and cost for operators to deploy infrastructure, particularly in rural areas, where there is no other existing fiber.  This is Greenfield development.  In countries like Pakistan and Myanmar ‑‑ the last one is one of the biggest problem. 

     >> The situation is similar in Latin America, that is what Helani was saying.  Everything depends on who is in power and bringing together all the different sectors that are involved, like, for example, in Peru, we would have to bring that education sector, ICT sector.  The culture sector.  For example, we have found in our qualitative studies, in Peru and Myanmar, there is the stereotypes, things like that.  (?) the gender gap depends on education, occupation even.  Income. 

     >> I would like to add.  I think connectivity is important, I agree it is an economic problem.  I mean, the cost of rolling out the Capex and optic costs are twice as high.  Twice as much Capex and 10 times as much OPEX.  It is a problem to be cracked and think how do we get policy and regulatory environments to be cost‑effective.  No way to roll it out if not cost‑effective.  I think connectivity is an issue, but not just about connectivity, the access alone will not solve this problem.  There are over one billion people that don't live in areas with mobile broadband coverage.  But three billion that live in coverage that are not using it.  It is 3:1 around usage.  When there is coverage, there is a huge gap much bigger than the coverage gap.

If we tackle this gender gap, we need to figure out what is stopping people from using it, it is not ‑‑ it is phone costs, the social norms, the data costs, the lack of digital skills, those sorts of things.  I think it needs to be two‑pronged, but we can't just focus on getting networks out.  We need to use them, address the gap and see a huge gender issue playing out.  So ...

     >> Thank you.  I guess what you were also saying, you know, you need multiple strategies.  We know what they are.  Rights‑of‑way, spectrum out there, competition.  To go about the effectiveness of the regulatory policies, but it is also, I think, what I am thinking about what you said is really about an integral policy.  So I think that goes to education capacity building and what would you think of digital agency in terms of having the Internet as a general purpose technology, transversal to all the sectors.  You would need an agency, an entity that would monitor and lead an integral policy between the ministry of education and ministry of economics, and now thinking about Internets, about how to get the multiple strategies together.

     >> I was going to say, in relation to the beyond connectivity, or beyond access issues that we have been concerned with and were touched on, I think an interesting outcome of the studies was actually the section that looked at cybersecurity awareness, privacy and those kinds of issues.  I think in many the particularly gap and sessions we tend to focus on it with all the assumptions that these are positive outcomes.  I think the vulnerability of the less educated or poor, they are actually unable to assert their rights or protect their rights, very often in these circumstances.  That is if you don't have the technical awareness, the awareness is sometimes the technical ability to enforce it, et cetera.  It is increasingly important that alongside this very sort of positive connectivity discourse and theory, we develop in‑depth theories of harm that go along with each regulatory intention.  What are the aspects of bringing a lot of people online that are unable to, you know, protect themselves from surveillance or harassment or whatever the issues are.

It raises the issue ‑‑ it is controversial in the president's speech, but what is the role of the state of protecting the individuals ‑‑ all of the citizens' rights online.  There is a lot of resistance to content type agencies, board regulation of the Internet.  What are the ways that we are going to protect citizens' rights online?  Is it an integrated digital agency or something more cross‑cutting across societies, regulation ‑‑ it is not a sect issue, but it is a digital agency or digital economy is the thing that would have a component to take care of that.  I think the cybersecurity, these are in the Justice Departments or international relations and kind of siloed process.  Looking at connectivity, but not the aspects that are accompanying it.

     >> MODERATOR: Questions from the audience?

     >> AUDIENCE: Hello, I work at the CI sector at UNESCO.  We are also working on digital divide.  A short question for the panelists, are there projects that you see related to L.G.B.T. communities and this space, discourse maybe they're facing in getting access to information, things like that.  Thank you.

     >> MODERATOR: Great question.  One that we're actually picking up and doing further research together on the IDRC who are supporting a range of feminist literature and research.  Especially with the quantitative educator research, within the U.N. system, it is difficult to introduce nonbinary indicators.  So Judith was saying we were needing a book, and equals is producing a book with some of our research and other people's research is in that.  In that process, there was an attempt in the working group, peoples from across the world to try to introduce a nonbinary notion within the indicator within the ‑‑ self‑identification or something, because it is obviously enormous in some countries to have an extensive questionnaire that would allow that kind of thing.  India has a self‑identification "other."  In the official documents.  The U.N., to have ‑‑ to introduce L.G.B.T.Q., whoever, other and several identification indicators.  That is at one level.

APC has large amounts of research and other groups too.  From the measurement or indicator side, it is an enormous challenge.  We hope in the next round, in some of the countries where our country partners feel it is fair to do, et cetera.  We will introduce it.  That is in the next round.

     >> I will add something really quick to that.  We don't look at projects, per se, about inclusion, but when we look at phenomena, remote and micro work.  Doing translation remotely, graphic design, so on.  We looked at that data in qualitative and quantitative base, we see pockets in Myanmar, for example, a lot of the translators identify as nonbinary or L.G.B.T.Q.  You know?  They talk about ease of getting work because nobody knows who they are.  You can take one if you are (?).  Sexually female, you say gender male, you can post and nobody will bother you.  Those barriers are interesting removed because of the remoteness of the work you are taken at face value because of the picture.

On other platforms‑like Facebook, some of the highest shaming is faced by women and gender nonbinary people.  So very commonly ‑‑ very common form of harassment is your photos being taken and PhotoShopped, that is the term and reposted in a way to bring you shame.  Nonbinary women are in the group along with those whose photo was taken with animals, and others, it is.

     >> It is not part of the research, it was funded.  We did an informal sector survey in Peru in an urban sector.  We tried to introduce a way of how to include this group.  So we ‑‑ it was a challenge to find a question.  We were trying to find a way of addressing the question.  In the end, no one said something else other than female and male.  Quantitatively, it is hard.  I think we need to think of other ways of addressing this issue.

     >> MODERATOR: Do we have a remote question?  From the audience? 
Well, I think that ‑‑
Anything else you would like to ‑‑ well, congratulations.  Very, very interesting.  Lot more to learn.  So you need to do another round. 

     Thank you for coming. 

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