The following are the outputs of the captioning taken during an IGF intervention. 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, but should not be treated as an authoritative record.
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>> MARTIN SCHAAPER: Welcome, everybody.
Today, we can talk about the differences between men and women. Using Internet or the mobile phone. We'll go deeper in depth by also looking at the barriers to access and then also the barriers to the benefits that we can all have from user. We have a panel with three speakers today. We have Relebohile Mariti, Claire Sibthorpe online, and I'm Martin Schaaper.
Before that, I want to talk about my own organisation. I'm Martin Schaaper. We have the social economic background and varieties and gender in the case. Without data, we collect the counties from the gaps. We estimate data so that we can compile global and regional aggregates. We published it once a year in the publication calls Facts and Figures. The Facts and Figures 2024 just came out three weeks ago.
The first one is: Internet use. We can see that globally if you look at split between man and women, 70% of the male population uses the Internet and 65% of the female population. There's a gap there. You can also express in different ways. I invite you to look at publication. If we then look at various regents in the world, we can see that in the Americas in the CIS countries and in Europe, the overall percentage is very high. The gap between men and women is small. There's a gap. One or two percentage points.
If we go to the region where we are today in the Arab states, we see a bigger gap. We see that 75% of the male population is using the Internet against 64% of the female population. Remember that globally it is 70‑65. The gap here is bigger than the global efforts. It is 68 against 64. The big gap though is in Africa. 43% of the male population is using Internet against 31% of women. And available to talk to us about it later and some ideas that we can address this. We also have data on the percentage of the population owning a mobile phone. Where we can see the overall percentage is a bit higher.
But the gap is the same. 82% of the male population globally owns the mobile phone against 77% of the population. Earlier, I spoke about the difference. Regions are rich counties and poor countries and different types of countries.
If you look at income, income is a very big factor in the differences. There's a big correlation. There's a big correlation between income level of the country and gender gap. Here we can see in high‑income countries, almost everyone has a mobile phone involvement in women and in upper, middle‑income companies, there's a small gap.
In low‑income companies, 60% of the male population versus 41% of the female population. I will stop here. It is hard to catch especially when spoken. Eventually, what we are trying to answer is the following policy questions. That's where we should be leading and maybe we'll get something out of the session. Policy questions are the most binding constrains which hold women back from being able to equally participate in the economy.
We're looking at barriers. Barriers are different between men and women. What policy interventions will create more even playing field where women are as able as men to derive socioeconomic benefits. They have an environment for participation in the economy. These are the policy questions. I will now give the floor to talk about the situation.
>> RELEBOHILE MARITI: Thank you, Martin.
As was already said, I will be sharing the evidence. I will be presenting the findings from the interesting and important work that we've been doing in Africa. Apologies. We're trying to move the slide. So what we see from the data is that despite the increased digitalisation around the world and even in Africa, the policies in Africa in most African countries have fallen short in addressing digital inequalities.
So as a result, we still see a lot of disparities in how this technology are dictated and used. Countries across Africa and in countries. What we find is that the digital inequalities are maybe driven by inequalities in structural inequalities. These are the differences in income and education between different groups within the countries.
And at the same time, we see that the COVID‑19 has exacerbated the structural inequalities by widening the digital inequalities. What we've been doing at Research ICT Africa is to collect data on how individuals use the digital technologies and the adoption of digital technologies and we look at what barriers they face.
For those who already have access, what limitations they face in trying to use this technology in the most productive way? And so we contribute that for African countries to achieve universal and meaningful connectivity, there's the impulse need. Just to give an overview after the access project. This is just to give an overview of the products that looks at the adoption and use of digital technologies across after can countries.
Research says CTCHA has been collecting the data. They placed between 2005 and 2008. It covered African countries. So the second was between 2012 and 2010. It covered certain African countries. The third was between 2017 and 2018. You see the number of countries that we are covering is going down. This is because we're an organisation that's funded by other organisations. We need to invest more.
Today, I'll be presenting the findings which to place between 2022 and 2023. Today I have results from six African countries. This provides a detailed account of the adoption of digital technologies and how individuals use the technologies and what barriers they face and what limitations they face. The household and individual survey is accompanied by the microenterprise rates. So the individual in household suffers a nationally representative, but the enterprise service is not nationally representative. Because we don't have because of the lack of listening in other countries. We were able to cover enterprises in each of the countries.
Because of this, they are really important. Just to give the high‑level findings, what we find is that the Internet is mostly accessed through smartphones. Those devices do remain inaccessible to the majority of the population in Africa. For instance, in 2022, 70% of the adult population in Nigeria did not have access to the smartphone. This is even higher in countries like Uganda. We find that 84% of the adult population does not have access to the smartphone.
Because of the access to the Internet, there's no levels of smartphone adoption. 50% of the adult population does not have access to the Internet. We find that men are still more likely than women to use the Internet. The gender gaps are most significant in countries where we have low levels of Internet access. We have the devices and the lack of digital skills and what the Internet is.
When we talk digital skills, they are required to look at the Internet. There's those who say they don't know what the Internet is. We find that most of the countries that we have Ethiopia and Nigeria. But those online indicate the low data is not for improved access and use when looking at the quality of Internet, that's experienced, there are disparities. They enjoy a better quality.
Because it is important that we understand the level of smartphone ownership within countries and how that has evolved over time, there's ownership across the countries. We see in some counties, 90% of the adult population has access. They show the feature phone use. Let's they we are dominated by the use of smartphones. We have ownership be dominated by the use of the phones. We see in some countries we have low levels of adoption of smartphones.
When you look at Ethiopia and Nigeria, it is dominated by the use of basic population had access to the smartphone. This was 28% in Nigeria. Not only do we have devices inaccessible, but we have the level of access across the group in the same country. These gaps are more pronounced when looking at smartphone ownerships.
When looking at the right by for each of the countries, it represents ownership among males. You find for some of the countries. There's priority in smartphone use. The low levels of access limits to Internet enabled services and opportunities.
When looking across the country is the smartphone ownership is the price of the devices. All of them indicate they have expenses. When looking at the trends in Internet access, when looking at it, we see some of the countries have reached more than half of the adult population. However despite the increase in Internet access in all countries, we see the level of access develops across the countries. Even their rate of Internet access is across countries.
For instance, when you look at level of Internet access in 2018 in Ghana, Kenya, and Nigeria, you find they had relatively particular levels. We see in Kenya and Ghana; the Internet access doubles. In Nigeria, there's a marginal increase. Because of the gaps, it is declining. Males are more likely than females to have access to the Internet.
In some countries, these gender gaps are more pronounced where we have low levels of Internet access. Then when looking at the barriers to Internet access across all countries, we see that it is the main barrier. We still see the digital skills and the lack of awareness of what the Internet is being the main barrier.
When looking across the gender, we see that more females than males say they don't know what the Internet is. For instance, when looking at don't know what the Internet is. We see that 43% of females say they don't know what the Internet is. This is likely lower for males at 19%. There's slight differences across countries.
If you look at South Africa, the lack of individual skills that don't know how to use the Internet. That's the main barrier. But when looking at countries like Ghana, we see the lack of access to Internet‑enabled devices is the main barrier. When looking at how individuals are using the Internet for those that are already online, we see across all countries, the Internet is used for social networking. They report using the Internet for social networking. Very few report using the Internet for online activities. 26% say they use the Internet for government services. We're still seeing that the use of the Internet remains low.
When looking across the agenda, when it comes to activities that enhance, we see that there are no differences in how male and females use the Internet for the activities. When we look at other and both online activities that have direct economic benefits, like government services, online work, and using the Internet to access the youth, you see significant gaps.
With those being more likely to use the Internet for females, we asked the Internet users if they were able to use the Internet as much as they would like to. The majority is limited to the extent that they use the Internet. It is mainly the prices of data. We see across all countries, the main limitation to Internet use is data prices.
When looking at the use of digital technologies by the enterprises. It is dominated by the use of basic phones. We see them report using them for mobile phones and activities. Most of them have basic phones as the most advanced phones. Very few have access to smartphone.
When looking across different groups, we see that female owned enterprises are the least likely to have mobile phones. This is when we look at smartphone ownership. When we look at South Africa and Ghana is generated by the use of smartphones. They are also reflected in the Internet access. We also have enterprises with the low levels of Internet.
Only 5 with were using the Internet for business activities. This was 30% in Nigeria. We see the enterprises and those established in the areas are least likely to use the Internet for business activities.
Also. we still see that even in Ghana and South Africa, they had slightly higher levels of Internet access amongst microenterprises. But they are higher when compared to other countries. Overall across all countries, the use of Internet for business activities by microenterprises is low. Because when looking across the countries, you find that 60% of the enterprises were not using them for business activities.
Also, what we find is we have microenterprise that is have smartphones. I'm not using the Internet for business activities. When we look at this specific group, you find that the main barrier to Internet access is data prizes. 26% of microenterprises reported using the smartphones for business activities. Only 25% of them were using the Internet. There's a need to look at data prizes. It is the importance of demand side.
With the demand side data, we are not able to determine the social and economic effective which limit the adoption and use of digital technologies. This is invisible to the supply side. So it is very important that we invest in demand‑side data, so we can be able to monitor progress and identify gap that is are existing. We can be able to know what type of interventions are required in order to provide universal and activities.
During this, we need to pay more attention to those of the intersection of inequalities. Particularly this list educated females who are living in the household. If we want to have universal and meaningful activity, you need to pay attention to this group. Thank you. I'll hand it over to you, Martin.
>> MARTIN SCHAAPER: Thank you very much. That was very interesting. Very rich as well.
At this point, I would like only questions for clarification. The debate will come after. Any questions for clarification in the room? I have one question; how do you define migrant parties?
>> RELEBOHILE MARITI: Thank you for that. They have moved ten degrees, that's ten or less and are not part of the franchise.
>> MARTIN SCHAAPER: Thank you very much.
With that, I think we can move to another part of the world. We were moving and Fabio can tell us.
>> FABIO SENNE: Hello. Good afternoon. Thank you very much for the organisations available here with Martin and the other colleagues. Thank you.
It is in Brazil and it is responsible for collecting ICT data in Brazil for the best 20 years. We are monitoring this for replacement years. I don't need to repeat Martin and really in the sense to say that why do you need this demand side data? How useful is this to have this data?
Especially, in the data driven society where everyone is discussing AI and how to train models with data. If I have one question and main message, it will be that we need to innovate the person and data collection.
Also, in the data analysis of what we collect in order to understand the gaps and the consequences and the correlations that we want to address with policy. I would like to show some examples of what we are doing for meaningful access in Brazil. We can say what can we do with the type of demand side data when we have the data available. I'll talk about more or less what we are doing and then talk about how is this measurement in Brazil?
On the next slide, just to mention that in the case of Brazil as we saw in Africa, there was a very fast change of scenario for the Internet in the past 20 years. Just to compare, if you compare 2008 to 2025, we passed through from having 42% of households connected to the Internet to at least 98% of households connected.
In the past, we have 48% of the Internet users using the Internet outside of the home in the cyber affairs and other environments. Now it is just 7%. Also with the mobile phone, we went from 40% to 88% now. There's a very fast changing scenario in the country.
If you take the differences, at least in the use of the veto access, there's not much difference between males and females in the two figures. Being in 2008 and 2024. We can argue there's no relevant gap. It is in Brazil. How do you measure apart from the access?
Now, that we have 90% of the population connected, how do you measure the connectivity? How significant is this? How meaningful is this to people? We decided to develop in the next slide. Yes. We decided to develop a scale. Using it to define a meaningful connection. The connection is affordable to the people that have it. The access to devices. Are there devices? They are capable of benefiting from the Internet. The quality of connection including the download speed and so on. And the usage environment.
If you have Internet in different spaces and at work, home, school, et cetera. This is we use a simple survey that we have in Brazil and classified the nine items. For each person in the population, we said a scale of zero to nine points. Which means that zero it is a very low meaningful connectivity and nine to be the minimum connectivity understanding that you have for the access connection.
When you calculate this in the next slide, then you can see very huge inequalities. Although we have 88% or 90% that had some access to the Internet, when it goes to the meaningful connectivity, you can say that today in Brazil only 22% of the population has a meaningful connection. Zero to two of the business scale. We can see that traditional differences appears, for instance, urban areas and rural areas are different in terms of meaningful connectivity. You can have here the regions in Brazil. We have the poorest regions with less meaningfully connectivity. Take a look at male rests.
When it comes to meaningful connectivity, we have 10% points more with meaningful connectivity in the country. This is very important. When you look at the indicators and are more sophisticated, then you see very huge inequalities and you can't understand how to face the gender equalities. In the next slide please. We did the same scale and compared also.
Okay. So you have a mark quality and collectively compared to those that have a low quality connective. What happens with your activities online? If you go to sending and receiving social media. If you compare to the finance services, the same was happening in Africa.
If you compare with the data that was shown before. When it comes to doing the more activities, there's more for people. The low meaningful score related with the performance of the types of activities. Also skills. It is just very important. Those that have less than the reported less the skews are also low levels of these collectives.
Of course, those things are correlated. You don't know what comes first. You don't have skews and then you don't go for the collective. This is important to understand the situation and to do the public policy with you. The last one or the next slide just to say that we have very traditional and as well as I mentioned before very traditional inequalities. This is still happening in unit two. This is just not looking into the big picture, but disaggregated data.
Here we can see when we break by level of cooperation, for instance, and you compare the list of ITU skews that ITU recommends as to be more but by the counters. You can see there's a very huge gap between those that have more implication and less implication when it comes to the skews. So this is another point arguing that we need more sophisticated and disaggregated data to understand the inequalities. The next slide please. Here just to say that we have another survey with children. I have just one figure here to mention. It is interesting the digital word needs to be developed. This needs to be discussed. And enhanced them.
So, when we ask children if you think that you'll find the same information. It is always the best result. We have more than half of the children 7‑19 years old. Not green with the statement. To see that although you can access, you can have and be online to social media. It is another type of skew to understand that how the network and things work and how the digital world works. This is another example of how to be more sophisticated. They are not.
To sum up, just to say a few words. We are a center based in Sao Palo, Brazil. Also by companies, countries, schools, and health care facilities. We are cooperates with UNESCO and countries to use the data. We can have all of the information available online, if you want.
In the next slide, just to mention that we also have a few grams of capacity building for research. To apply these types of service and to produce comparable data and comparable information on the field of the Internet. I'm not taking too much time on this. We can have more of a discussion.
>> MARTIN SCHAAPER: Thank you, Fabio. If there aren't any questions for clarification at this point, nothing? Then I suggest we move on to Claire who is online. Who will talk to us about the resource for low and middle‑income countries.
Claire, I hope this works. The floor is yours.
>> CLAIRE SIBTHORPE: Thank you. Can you hear me?
>> MARTIN SCHAAPER: Very good. Very well.
>> CLAIRE SIBTHORPE: I'm sharing some slides. I'm Claire from GSMA. I lead the digital inclusion programmes, including the connected woman programme. We publish the annual report on the mobile gender gap. We conduct national representative surveys on women's access to and use of mobile Internet and the barriers. I thought it was useful to start by highlighting the trends.
As you can see from this slide, we started measuring the gender gap from 2017 that the ‑‑ it had the mobile Internet gender gap. It had been consistently narrowing up until about 2020. When it stood at 50%.
>> MARTIN SCHAAPER: Can you put it on full screen shot?
>> CLAIRE SIBTHORPE: Yup. Absolutely. Is it better now? Is it showing up as full screen for you now?
>> MARTIN SCHAAPER: Yes. It is.
>> CLAIRE SIBTHORPE: Great. This was good news. It was a high‑gender gap. We saw during the first phase of COVID. There was the lockdowns. People were stuck at home. Reduction of the women's gender gap. As they were having women to go online and educate their children.
After COVID, you know, for two years after that kind of period ended, we saw that progress had stalled. They were disproportionately and significantly impacted. The gap widened in 2022. We showed it narrowed back to 15%. They are 15% less likely to make use of the Internet. I would like to highlight the trend. Progress is fragile. We need to have a conservative effort.
By having the gaps, we can see how different global events affect it. They don't know if the adoption is going to continue to increase and the gender gap is still going to go. I think it is also important to note that we're back to 2020 levels, it is still quite a wide gender gap. There are still according to our data, 225 million men using the Internet. I'm talking about mobile. That's the primary way that most people in the regions access the Internet. I'm going to go into what it means. It is where you are at all in the country. It is big regional and national gender gaps. 60% of women live in sub‑Sahara. This is compared to 0% from 32%.
In the sub‑Saharan Africa, we saw the reduction in the gap that is driven by South Africa. There's been some changes year on career. There hasn't been a big difference in terms of the gender gap from 2017. Now it is 32%. In 2017, it was 34%. I think it highlights it can be difficult to make big differences. And reductions are not guaranteed.
As was mentioned previously, they grow within the countries. They are much higher than the urban areas. It isn't just about whether women are adopting the Internet, it is are they able to use it to meet their life needs? I think we see again there are big gaps. It is not linear.
In terms of owning the phone and using it for diverse use, what we see is the gender gaps widen at every stage? There might not be a gender gap in Internet adoption, there's a gender gap in regular diversities of the Internet typically. It is important to understand these. You see in our survey once men and women become Internet users, the vast majority tend to use it every day. But that sort of often for a limited range of purposes.
In fact, in our recent research, we asked if people would like to use it more. Women were more likely than men to report they need to use it more than they do. This was true for more than half of the mobile users in Ethiopia, Bangladesh, and Pakistan. I think in terms of addressing the gaps, it is really important to understand what stops men and women. Not surprised of the data and research. What we are being told in the surveys, once women are aware, the top barriers that stop them from adopting it affordability. And lack of literacy and digital skills. These are the same barriers that men face.
More and more women face the barriers than men. They are more likely. They also experience these more cutely lead to social norms and structural inequalities like disparities in education and income. Then last year for the first we actually asked what is the various topic? Men and women are using it more. And the barriers aren't as clear cut. Affordability is not as clear cut. It does vary by country more in the use them for the further use.
But, overall safety and security was a top reported barrier, it is one of the top three barriers in all of the survey countries. And concerned around this influence concerned about reliability of information found online, scams, fraud, information, security, unexpected contact from strangers, and fears to being exposed to harmful content. The second was affordability. This was primarily data, but also handsets. These are ‑‑ we also have previously done some research just to kind of build on what I said before like the female entrepreneurs and what is stopping them. We saw similar to research; they are much less likely the male for the businesses.
And even when they were using some of the services in the personal lives, they were not using it for business often. They weren't aware it could be used for business. It highlights that these barriers also differ depending not only on the country, but your context and who you are and we shouldn't be pages women as a kind of homogeneous kind of group. That's at a high level. I'll share the report.
At a very high level, we just need to focus on this and set real targets. It is not guaranteed that the gender gaps are going to continue to increase. As has been highlighted many times, we gender disaggregated data is critical to measuring and informing policies and investments and action to do this.
While a number of us have surveys as we've been saying, there's a lot more data that's needed to understand the women's mobile use, needs, and how it differs in different context and for different groups of women. We need more data.
When it comes to kind of designing products, services, policies, we really need to consider women's needs, circumstances, and the challenges that they face and the different barriers. For example, if you look at barriers that we've mentioned, affordability, crown, can be improved by policies, initiatives that lower upfront costs. For Internet enabled handsets.
For example, lowering the specific taxes or financing initiatives. It is also skills, literacy and skills is a lot people can do to address that. But to kind of flag that our experiences that these barriers need to be addressed holistically. It is not you need to think of affordability. We need to work together and partner with different staying holders. No one group can do this on their own.
Just to conclude, we need more targeted action and investment by stakeholders. I shared earlier the gap is big and not always reducing. I wanted to end on a slightly more positive note. It is possible to make a difference. This is informed targeting action that can make a difference. We have mobile operators who have made connected women commitments to reduce the gender gap in the mobile Internet and mobile money customer bases. They have set clear targets for doing so and are tackling the barriers.
Since 2016, when these commitments were starting to be made, we've seen that they have actually succeeded. They have additional women with mobile Internet and services. When having the data and taking that targeted action, it is possible to make a difference. I hope we can continue.
>> MARTIN SCHAAPER: Thank you. We had three people coming up with the same issues. Are there any questions for the director? Yes. That's a question. We have to be mindful here.
>> AUDIENCE: I have research and data. It is great to see you again. Thank you for the presentations. This is a couple of questions from me. I wanted to understand. You work with the national offices. Sometimes it was data sources including computer generated data. I was wondering what has been your experience. The second point is have you seen the research or did you collect the data. This is linked violence against women. When they try to get the difference. They have the questions one by one. They have the first questions.
>> CLAIRE SIBTHORPE: The data that I referred to was the survey. We looked at the data that was referenced earlier that comes from the government. We don't directly engage with the departments.
>> MARTIN SCHAAPER: We have the stakeholders. This will also collect the working partnership.
>> RELEBOHILE MARITI: Thank you. We use the national data to collect how do you do? It is in some countries. Like any other countries where we encountered challenges. I think that's from all of the salesperson. We have statistical offices.
>> FABIO SENNE: We have the additional regulator that's funding the survey or in some cases not the survey and advantages. Et cetera, et cetera. They have to work for the data. That's the high level just after the break now. We see how important is the number. That's the second question.
>> RELEBOHILE MARITI: Also just to clarify when I say we have the national, statistical offices. We have Africa paying for the labour costs. The online experiences and reports for individual countries.
In our cases, it was experienced online. What can hold the information they have online. It will share the agenda and the political piece. That's where we find the most experience online. In countries we find there's no defences in what information individuals share on social media, thank you.
>> MARTIN SCHAAPER: In our cases, we don't have a specific courses. It is effective to combine more higher data collection. This is what you'll see the difference for themselves. The stakeholders in terms of sexual violence. Also those report and align with the road map. There's the adult population.
>> CLAIRE SIBTHORPE: Yes, we do. We have a whole series of barrier questions that we ask around both on the kind of safety and security issues and whether this is a concern that's stopping you from going online or using the Internet more. We have questions on whether family approval is an issue or not in terms of going online.
Last year, we asked some questions and extra questions. We see this is a concern for men and women. The safety and security concern. As people get online, it becomes more of a concern. Once you are online. We asked the questions last year about whether people had personally experienced the safety and security issues and whether it was a concern. There's two realities for online. There's the reality of this happening. There's a concern it will happen. They are concerned about the wives or daughters going online because of the risk. It is the concern and reality.
It is certainly an issue that is stopping from going online and I think concerns some of the concerns are limiting their ability or their online use and use is limited in certain ways in an effort to sort of address this perceived risk. I should say we did some research. We found that women were much less likely to know how to protect themselves online. They didn't know there were things like privacy settings on Facebook. There's skills leveled in some of the ways to keep themselves protected online. They were lower than for men. That's also an issue.
>> FABIO SENNE: There's the household. If they don't have the answer. There's this type to find the way. That's a great subject. Maybe that's the access to that. That's the session open.
>> MARTIN SCHAAPER: Thank you for the question. You left your microphone. They select to leave the house. They have data online and data from the processed demands.
>> RELEBOHILE MARITI: Okay. Okay. Thank you. We conducted interviews.
>> CLAIRE SIBTHORPE: For the mobile gender gap report, it is adults. I've put in the link online. We have connectivity report. It does separate adults versus those who are under 18 and shared phone access. It has more detail on that point.
>> FABIO SENNE: Whatever they are doing. It is different.
(Audio is distorted and soft)
>> FABIO SENNE: That's therapy also. It is the under aged group. It is actually very important. Any other questions? This is what they go to. They need the data. Maybe that's the case there. You work with the policymakers.
>> MARTIN SCHAAPER: Yes.
(Audio is distorted and soft)
>> MARTIN SCHAAPER: The situation to call on next. It is for society and then go. They are recommended by IT and by the standards. They have that firm. It requires and I think another important part of this is very dynamic. The user that changes and service that is available. That's why it is the regulatory way.
>> FABIO SENNE: We have the policies helping with the barriers.
>> RELEBOHILE MARITI: We reported the examination to the perspective countries. They have shown interest in using the data. Also after we've done the presentation, it is eager to know which interventions they can implement to address challenges in their respective cultures.
>> FABIO SENNE: Thank you. I know you had issues in hearing. You already mentioned some of the mistakes of the interaction. But maybe you can
>> CLAIRE SIBTHORPE: I think the question is how do we engage with policymakers? Obviously, we share our data with anybody that wants or keen to make sure that deem are doing evidence‑based policies and programming.
We supports government on their policies. We run free training courses on both the digital gender divide as well as in general with policymakers. We share our data and recommendations. We have a whole report which outlines specifically policy recommendations in the space. We're very engaged and keen to the data that we are lucky enough to collect.
It is available and accessible as much as possible to all stakeholders in the space. They are all evidence‑based in our work.
>> MARTIN SCHAAPER: I see no questions. We're going to wrap up. As we mentioned already, it is important to have the data.
Yet, we see so many gaps, especially low income and middle‑income countries. As I mentioned, they are usually underfunded. Two questions. Did you manage to get your data collection and the second is how can we make this may be attractive to increase the funding to do the kind of data collection. I think I'll start with the positive example here.
Fabio, I'm going to hand it to you and then the other two panelist.
>> FABIO SENNE: Thank you. Just to present on the Brazilian model. In the case of Brazil where I'm from, it is funded by nick.PR. It is the countercode level domain registry. We use the funds that come from the .PR to provide society with more information, including service in the use of the Internet. This is a unique model. I think other domains invest in service. This is something that can be done.
I think that as I mentioned, keeping the relevance of the indicators, I think, is very important. It is very interesting to see that if you go to all of the ‑‑ now you have very new strategies to measure AI readiness and all of them. In a sense or including the connectivity to also be aligned and use the Internet. I think the agenda changes. We need this very basic information on how people.
If you have service and data like this, keeping the relevance. They are making this type of data more available.
>> MARTIN SCHAAPER: Thank you. Maybe I'll first go to Claire.
>> CLAIRE SIBTHORPE: Sure. We're already there. We feel the data is really, really need. We can't know what we doing and support our members without having it be very fortunate. Especially the gender aggregated data. GSMA is funding the core countries of the consumer survey. Now they do the modeling of the usage gap and gender gaps. We absolutely need this data. We are fortunate to have support from some of the donors to add countries they are interested in and build and compare across more counties and also to do the modeling, so we can model the gender gaps. That's UK, department for international development, and Swedish agency support us in terms of being able to additional countries. We do the modeling and the reports that we are able to publish. It is great if the daughter was just there and done in more counties. And we all need the data.
>> RELEBOHILE MARITI: Research ITU is the latest organisation. It was funded by the world bank and the Bill and Melinda Gates Foundation. So there's really a need for invest many in this kind of data. To make it attractive is we can stress the importance of the data. We can show how it will be used to create value. It is in it for collaboration. Make the data easily accessible. It is publicly available for everyone to access it. Thank you.
>> MARTIN SCHAAPER: Thank you very much for that. I can add something from our perspective. They are interested in funding. It is important the data and for them themselves will be discussed. We now have a project funded by the EU that's called mesh and meaningful product. We're trying to make the connection between the policymakers and we explain we do a lot of workshops. We do a lot of focusing. We explain what it is.
Before wrapping up, I'm going to give the last chance to the audience online to ask the last question. I see none.
Before thanking the panel, I would like to conclude that there's a difference in gender in how men and women access the Internet and also once they are online, men seem to make more of it than women. More activities than women. You are going to address it in gender equality. You need to have the data. We can analyse it. Everyone can do that. It is not a difficult analysis. You need to have the data. They see the importance of the data. They can get some of the government funding.
Thank you for online moderation and organizer chair. With that, let's give a big hand for everyone. Thank you very much.