WS #225 Gender inequality in meaningful access in the Global South

Summary

This discussion focused on the gender gap in digital access and usage across different regions, particularly in low and middle-income countries. Presenters from Research ICT Africa, CETIC Brazil, and GSMA shared findings from their surveys on internet and mobile phone usage. Key points included that while overall internet access has increased in many countries, significant gender gaps persist, especially in Africa and South Asia. The gaps widen at each stage from basic access to regular, diverse internet use.

Barriers to women’s digital inclusion include device affordability, lack of digital skills, and safety concerns. Even when women have access, they often use the internet less diversely than men, particularly for economically beneficial activities. The presenters emphasized the importance of collecting gender-disaggregated data through household surveys to understand these nuanced gaps and inform targeted policies. They discussed various models for funding and conducting such surveys, including partnerships with national statistical offices.

The discussion highlighted that progress in closing digital gender gaps is not guaranteed and requires sustained, targeted efforts informed by data. Participants stressed the need for more funding and support for data collection, especially in low-income countries where statistics offices are often underfunded. They also emphasized the importance of making survey data relevant and accessible to policymakers to drive evidence-based interventions aimed at achieving universal and meaningful connectivity for all.

Keypoints

Major discussion points:

– There are significant gender gaps in internet access and usage, particularly in low and middle-income countries

– Data collection and analysis is crucial for understanding and addressing these gender gaps

– Barriers to internet access and usage for women include affordability, lack of digital skills, and safety/security concerns

– Collaboration between researchers, policymakers, and other stakeholders is important for collecting relevant data and using it to inform policies

– More funding and support is needed for data collection efforts, especially in low-income countries

The overall purpose of the discussion was to examine gender gaps in internet access and usage across different regions, share findings from various research efforts, and discuss the importance of data collection for informing policies to address these gaps.

The tone of the discussion was informative and collaborative. Panelists shared insights from their research in a factual manner, while also emphasizing the importance of working together and with policymakers to address the issues identified. There was a sense of urgency about the need for more data and funding, but the overall tone remained constructive and solution-oriented throughout.

Speakers

– Relebohile Mariti: Research Fellowб Research ICT Africa

– Fabio Senne: Project Coordinator at the Regional Centre of Studies on Information and Communication Technololgies under the auspices of UNESCO (Cetic.br)

– Claire Sibthorpe: Head of Digital Inclusion in the Mobile for Development (M4D) team at the GSMA

Gender Gaps in Digital Access and Usage: A Comprehensive Analysis

This discussion focused on the persistent gender gaps in digital access and usage across different regions, particularly in low and middle-income countries. Presenters from Research ICT Africa, Cetic Brazil, and GSMA shared findings from their surveys on internet and mobile phone usage, highlighting the complexities of the digital divide and the importance of data-driven approaches to address these inequalities.

Key Research Projects and Methodologies

Research ICT Africa presented findings from their After Access project, which covered 20 countries in Africa, Asia, and Latin America between 2017 and 2022. Cetic Brazil shared insights from their ICT Households survey, which uses a multi-stakeholder model to define indicators and surveys individuals aged 10 and older. GSMA discussed their annual Mobile Gender Gap Report and State of Mobile Internet Connectivity Report, which provide global insights into mobile internet adoption and usage.

Key Findings on Gender Gaps

Claire Sibthorpe from GSMA emphasised that progress in closing the mobile internet gender gap is fragile and not guaranteed, underscoring the vulnerability of digital inclusion efforts to external factors and the disproportionate impact on women.

Fabio Senne from Cetic Brazil introduced a crucial distinction between basic access and meaningful connectivity. He stated, “Although we have 88% or 90% that had some access to the internet, when it goes to the meaningful connectivity, we can say that today in Brazil, only 22% of the population has a meaningful connectivity, and being 30% are in the 0 to 2 of this scale.” This insight reveals a much larger digital divide than raw access numbers suggest.

Sibthorpe highlighted that gender gaps widen at every stage of internet adoption and usage, with specific figures varying by region. For example, in South Asia, women are 41% less likely than men to use mobile internet.

Barriers to Women’s Digital Inclusion

The discussion identified several key barriers to women’s internet access and usage. Relebohile Mariti from Research ICT Africa emphasised affordability of devices and data as a primary obstacle. She also highlighted the lack of digital skills and awareness as major barriers, providing concrete evidence: “So when looking at don’t know what the Internet is, we see that 23% of females say that they don’t know what the Internet is, and this is slightly lower for males at only 19%.”

Claire Sibthorpe added that safety and security concerns significantly limit women’s internet use. She also pointed out that social norms and structural inequalities exacerbate barriers for women.

Importance of Gender-Disaggregated ICT Data

All speakers emphasised the critical importance of collecting and analysing detailed, gender-disaggregated data to understand digital gaps and inform effective policies and interventions. Fabio Senne advocated for a multi-stakeholder approach to ensure relevant data collection, while Claire Sibthorpe focused on using data to inform evidence-based policies and interventions.

Challenges in ICT Data Collection

The discussion highlighted several challenges in collecting ICT statistics, including limited funding, especially in developing countries, and difficulties in partnering with national statistical offices. Fabio Senne pointed out the challenge of keeping surveys relevant as technology rapidly changes and raised the sensitive issue of collecting data on topics like online violence, which requires careful approaches.

Policy Implications and Recommendations

The speakers agreed on the need for targeted interventions to address specific barriers women face in digital inclusion. Specific recommendations included:

1. Focusing on affordability, skills development, and creating enabling environments

2. Lowering mobile-specific taxes

3. Implementing handset financing initiatives

4. Increasing investment in gender-disaggregated ICT data collection

The discussion also touched on the importance of engaging policymakers effectively to use ICT data for decision-making.

Emerging Issues and Future Directions

The discussion highlighted the need to consider children’s access to smartphones and internet, with an audience member raising concerns about the appropriate age for children to have unrestricted internet access. This prompted a discussion about the importance of disaggregating data by age groups and considering the unique needs and risks for different demographics.

The speakers also emphasised the need for qualitative studies to complement quantitative data, especially for sensitive topics like online violence. The moderator noted the challenges in asking questions about controlling behavior in household surveys, highlighting the complexity of addressing certain aspects of the digital divide.

In conclusion, this discussion underscored the complex nature of the digital gender divide and the crucial role of comprehensive, gender-disaggregated data in understanding and addressing these inequalities. It emphasised the need for sustained, targeted efforts informed by data to achieve universal and meaningful connectivity for all, particularly women and children in low and middle-income countries.

Moderator: Asia-Pacific, on the other hand, the overall percentage is a bit lower, but the gap is smaller as well. It’s 68 against 64. The big gap, though, is in Africa, where 43% of the male population is using the internet against only 31% of women. And Rayleigh will talk to us about that later and come up with a few explanations, maybe, and some ideas how we can address this. We also have data on the percentage of the population owning a mobile phone, where we can see the overall percentages are a bit higher, but the gap is the same. 82% of the male population globally owns a mobile phone against 77% of the population. Earlier, I spoke about the difference by region, but, of course, regions are very heterogeneous. There are rich countries, poor countries, different types of countries. If you look at income, income is a very big factor in these differences. There’s a big correlation. I’m not going to say causation, but there’s a big correlation between income level of a country and gender gap. And here we can see that in high-income countries, almost everyone has a mobile phone, both men and women. In upper-middle-income countries, it’s 86% of male against 84% of women, so there’s a small gap. Lower-middle, it’s 77% against 66%. And in low-income countries, 60% of the male population against 41% of the female population, so a huge gap there as well. I will stop here with the barrage of data, which is a bit hard to get, especially when spoken without any slides. In our session today, we’re going to look deeper into these issues based on data. And eventually, what we’re trying to answer are the following policy questions, or at least that’s where we should be leading, and maybe we can get something out of this session. Policy questions are, what are the most binding… constraints which hold women back from being able to equally participate in a digital economy. So we’re looking at barriers and barriers that are different between men and women. What policy interventions will create a more even playing field where women are as able as men to derive socio-economic benefits from digital interaction. So how can we solve it? How can policymakers solve it? And then which countries have provided evidence of providing an enabling environment for equal participation in the digital economy? And what were the key factors which led to this success? So learning from others. So these are the three policy questions. I would now like to give the floor to Relebohile Mariti from Research ISC Africa to talk about the situation in Africa. Rele, the floor is yours.

Relebohile Mariti: Thank you and thank you to the participants for taking your time to join us today. As Martin has already said, I will be sharing the evidence from… Okay, so I’ll be presenting our findings from the interesting and important work we have been doing at Research ICT Africa. Okay, apologies, we’re trying to move the slide. Okay, so what we see from the data is that despite the increased digitalization around the world and even in Africa, the policies in Africa, in most African countries, have fallen digital inequalities. And so as a result we still see a lot of disparities in how these technologies are adopted and used across countries in Africa and within countries. And so what we find is that those digital inequalities are mainly driven by structural inequalities. These are the differences in income and education between different groups within countries. And at the same time we see that the COVID-19 has exacerbated the structural inequalities by widening the digital inequalities. And so what we have been doing at Research ICT Africa is to collect data on how individuals use these digital technologies and the adoption of digital technologies. And we look at what barriers they face. And for those who already have access, what limitations they face in trying to use these technologies in the most productive way. And so we conclude that for African countries to achieve universal and meaningful connectivity, there’s a need for effectively regulated and competitive and innovative industry that will respond to consumers needs. So to just give an overview of their after access project. To just give overview of their after access project. This is the only nationally representative household and individual SAFE. that looks at the adoption and use of digital technologies across multiple African countries. And Research Health City Africa has been collecting this data, and so the first round of the After Access Surveys took place between 2005 and 2008, and it covered 17 African countries. And so the second was between 2012 and 2010, and it covered 13 African countries, and the third was between 2017 and 2018, and it covered only 10 African countries. And you see that the number of countries we are covering is going down, and this is because we are an organization that’s funded by other organizations, so we really need to invest more on this. So today I’ll be presenting the findings from the fourth round of the After Access Surveys, which took place between 2022 and 2023, and we covered seven African countries. But today I only have results for six African countries. So the survey provides a detailed account of the adoption of digital technologies, and how individuals use these technologies, and what barriers they face and limitations they face. And for each of the countries surveyed, the household and individual survey is accompanied by micro-enterprise surveys. So the individual and household surveys are nationally representative, but the micro-enterprise surveys are not nationally representative, because we don’t have… because of the lack of nationalistic… of micro enterprises in different countries, but then we were able to cover a large number of micro enterprises in each of the countries, so because of this the insights are really important. So just to give the high-level findings, what we find is that the internet is mostly accessed through smartphones, but those devices do remain inaccessible to majority of their population in Africa. For instance, in 2022, 72% of the adult population in Nigeria did not have access to a smartphone, and this is even higher in countries like Ethiopia and Uganda, where we find that 84% of the adult population do not have access to a smartphone, and so because of this, this limits access to the internet, and in those countries where we have low levels of smartphone adoption, we have low levels of internet access. More than 50% of the population, of the adult population, do not have access to the internet, and when looking across countries, we see different gaps. We see significant gaps across countries, and also there are significant gaps within countries. We find that men are still more likely than women to use the internet, and thus the gender gaps are more significant in countries where we have low levels of internet access. So the main barriers to internet access are the price of devices, and the lack of digital skills, and lack of awareness of what the internet is. So when we talk of lack of digital skills, it’s the basic literacy required to navigate the internet. So we still see individuals who said they don’t know how to use the internet, and those who say they don’t know what the internet is. And also when doing the supply side analysis, we find that most of those countries that we have, Ethiopia, Nigeria, and Uganda, they rank in the top 10 countries in Africa that have the cheapest prices of data. But those online indicate that they’re not able to use the internet as much as they would love to because of high data prices. So then this is low data prices do not equate to improved access and use because of the structural inequalities. And also when doing the supply side analysis, we find that when looking at the quality of internet that is experienced by end users, there are disparities. Those in urban and capital centers enjoy better quality than others. So because most internet users access the internet through smartphones, it is important that we understand what the level of smartphone ownership within countries and how that has evolved over time. So overall, there has been increase in mobile phone ownership across countries. And we see that in some countries, 90% of the adult population have access to a mobile phone. So when looking at the bar, the red part of the bar shows smartphone ownership and the gray part shows basic phone or feature phone use. So where we have the red part being bigger than the gray part, that says in that country we have mobile phone ownership being dominated by use of smartphones. But if we have a gray part being larger than the red part, it means we have… mobile phone ownership being dominated by use of basic or future phones. So we still see that in some countries we have low levels of adoption of smartphones. For instance, when you when you look at Ethiopia and Nigeria and Uganda, you see you see that mobile phone ownership in those countries is dominated by use of basic phones, which limits access to the Internet. Only 16% of the adult population in Nigeria, I’m sorry not Nigeria, in Ethiopia and Uganda had access to a smartphone and this was 28% in Nigeria. So not only do we have devices being inaccessible, but even the level of access differs across groups within the same country. So when looking when looking across gender, we find that men are more likely than females to have access to a mobile phone, but those gaps are more pronounced when looking at smartphone ownership specifically. So when looking at the buys, the right buy for each of the countries, the right buy represents mobile phone ownership among males and you find for some of those countries there is a difference and an exception is South Africa where we see that there’s almost parity in smartphone use. So this low levels of access to smartphone among females limits their access to Internet enabled services and opportunities. So then when looking across all countries, we find that the main barrier to smartphone ownership is the price of these devices. So across all countries, a significant share of individuals who do not have access to smartphones indicate that those devices are too expensive for them. So when looking at the trends in internet access, so when looking at the trends in internet access, we see that the internet access has been growing across all countries, and some of the countries have reached more than half of the adult population. And however, what despite the increase in internet access across all countries, what we see is that the level of access differs across countries, and even the rate of growth of internet access also differs across countries. It is growing faster in other countries. For instance, when you look at the level of internet access in 2018 in Ghana, Kenya, and Nigeria, you find that they had relatively similar levels of internet access. But between 2018 and 2022, we see that in Kenya and Ghana, the level of internet access doubled, and in Nigeria, there was a marginal increase. So then, because of this positive trend in internet access, the gender gaps have also been declining, but they still remain. insignificant, with males being more likely than females to have access to the Internet. In some countries, like, these gender gaps are more pronounced in countries where we have low levels of Internet access. So then when looking at the barriers to Internet access across all countries, we see that the lack of access to devices comes out as the main barrier. But even though this is the main barrier, we still see the lack of digital skills and the lack of awareness of what the Internet is being the main barrier. So when looking across gender, we see that more females than males say that they don’t know what the Internet is. For instance, when looking at don’t know what the Internet is, we see that 23% of females say that they don’t know what the Internet is, and this is slightly lower for males at only 19%. So there are slight differences across countries. For instance, when you look at Ethiopia, Nigeria, and South Africa, the lack of digital skills, that is individuals who say they don’t know how to use the Internet, that is the main barrier. But when looking at countries like Ghana, Kenya, and Uganda, we see that the lack of access to Internet-enabled devices remains the main barrier. So when looking at how individuals are using the Internet for those who are already online, we see that across all countries the Internet is predominantly used for social networking. So nearly all Internet users report using the Internet for social networking. very few report using the internet for online activities that have direct economic benefits like government services and online work. We only have 17% of internet users saying they use the internet for online work and 26% say they use the internet for government services. So we still see that the use of the internet for meaningful activities still remains low. So when looking across gender, we see that when it comes to activities that enhance leisure, we see that there are no differences in how male and females use the internet for those activities. But when we look at other, when we look at those online activities that have direct economic benefits like government services, online work and using the internet to access the news, we see significant gaps with males being more likely to use the internet for those activities in comparison to females. So when looking, so we also had a question that asked internet users if they are able to use the internet as much as they would love to. And what we find is that majority of them say they feel limited in the extent to which they can use the internet. And the main factor leading to this is the prices of data. So we see that across all countries, the main limitation to internet use is data prices. So when looking at the use of digital technologies by micro enterprises, we find that in most of the countries The use of mobile phone ownership is dominated by use of basic phones. So in Nigeria and Ethiopia, we see that most micro enterprises that report using mobile phones for business activities, most of them only have basic phones as the most advanced phones and very few have access to smartphones. When looking across different groups, we see that female-owned micro enterprises, those located in rural areas and informal micro enterprises are the least likely to have mobile phones. And these differences are more pronounced when we look at smartphone ownership. And so when we look at South Africa and Ghana, we find that mobile phone ownership amongst micro enterprises in those countries is dominated by use of smartphones and there are slight differences across groups. So then we see the differences that we have in mobile phone ownership and smartphone ownership are also reflected in internet access. So what we see is that the countries that have low levels of smartphone ownership, we also have micro enterprises having low levels of internet. So in Ethiopia, only 5% of the surveyed micro enterprises were using the internet for business activities. And this was only 13% in Nigeria. And there are significant gaps across gender and locations as well as formality. in which we see that informal micro-enterprises and those established in rural areas, and those that are female-owned, are the least likely to use the internet for business activities. And so also, we still see that even in Ghana and South Africa, they had slightly higher levels of internet access amongst micro-enterprises. But they are higher when compared to other countries, but overall, across all countries, the use of internet for business activities by micro-enterprises is low. Because when looking across all those countries, you find that 60% of the established micro-enterprises were not using the internet for business activities. So also then, what we find is that we have micro-enterprises that have smartphones, but are not using the internet for business activities. So when we look at this specific group, we find that the main barrier to internet access is data prices. So for instance, when you look at Ethiopia, 26% of micro-enterprises reported using smartphones for business activities, but only 5% of them were using the internet. And so then, this says there is a need to look at data prices. So in conclusion, the analysis that we have emphasises the importance of having demand-side data. Without demand-side data, we are not able to determine the social and economic factors which limit the adoption and use of data. of digital technologies, and these factors are invisible to the supply side, so it is very important that we invest in demand-side data so that we can be able to monitor progress and identify gaps that are existing and be able to know what targeted interventions are required in order to promote universal and meaningful connectivity. And in doing this, we need to pay more attention to those at the intersection of these inequalities, particularly these are least educated females who are living in a poor rural household. So if we want to have universal and meaningful connectivity, there is a need to pay attention to this group. Thank you. I’ll hand over to you, Martin.

Moderator: Thank you very much. That was very interesting, very rich as well. At this point, I would like only questions for clarification. The general debate will come after the three presentations. So are there any questions for clarification in the room? I have one question, though. How do you define micro-enterprises? So in this study, micro-enterprises are those enterprises that have at most 10 employees, that is 10 or less, and are not part of a franchise. Okay, thank you very much. With that, I think we can move to another part of the world. We are moving to Brazil, and Fabio will tell us about their survey in Brazil. Fabio.

Fabio Senne: Hello. Good afternoon. Thank you very much for the invitation. It’s a pleasure to be here also with Martin and the other colleagues. I think I’ll be standing to see my slides, and if a colleague can help me. So, thank you. So, I’m from Cetic.br, which is a research center based in Brazil that is responsible for collecting ICT data in Brazil for the past 20 years. So, we are monitoring this field for the past 20 years and I don’t need to repeat Martin and really in a sense that to say that why do you need this demand side data, how useful is to have this data, especially in a data-driven society where we wanted to, we are discussing AI and how to train models with data, but we still need to have at least some equality in the way the data is collected and these types of inequalities are very important to monitor. So, my presentation here, if you can go to the next slide, if I have one main question or main message, it will be that we also need to innovate, of course, in data collection, but 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. So, I would like to show some examples of what we are doing in terms of measuring meaningful access and meaningful connectivity in Brazil so that we can say that even what can we do with those type of demand side data when we have this data available. So, I’ll talk about more or less what we are doing and then talk about how is the structure of 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 in scenario for the internet in the past 20 years. So, just to compare, if you compared 2008 to 2025, we passed through, from having 42% of households connected to the internet to almost 98% of households connected. We had, in the past, we had 48% of the internet users using the internet outside home, in cyber cafes and other environments, and now it’s just 7%. And also with the mobile phone connections, we went from 40% in 2008 to almost 88% now. So there’s a very fast changing scenario in the country. And if you take the differences, at least in the use of individual access to mobile phone, you can see that there’s not much difference between males and females when you compare the two figures, being in 2008 and 2024. So we can argue that there’s no gender gap, there’s no relevant gender gap when you compare just the access, so the access to smartphones, or the access to the internet in Brazil. But our point, okay, but how do you measure, apart from the access, now that we have almost 90% of the population connected, how do you measure effectively how significant this access is, how meaningful this access is to people? So we decided to develop, in the next slide, please. We decided to develop a scale that is a very simple scale based on nine items that we classified using ITU’s frameworks and other organizations’ frameworks to define meaningful connectivity. And we decided to classify these nine indicators in four. dimensions. So the dimension of the affordability, so this connection is affordable to the people that have it. The access to devices, so are there devices that 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, at work, at home, at school, and etc. So this is, we use a sample survey, a normal sample survey that we have in Brazil, and we classify these nine items. And for each person in the population, we set a scale of 0 to 9 points, which means that 0, it’s a very low meaningful connectivity, and 9, it will be the minimum connectivity understanding that we have affordability, the access connection, and devices. And when you calculate this in the next slide, then you can see very huge inequalities, because although we have 88% or 90% that had some access to the internet, when it goes to the meaningful connectivity, we can say that today in Brazil, only 22% of the population has a meaningful connectivity, and being 30% are in the 0 to 2 of this scale. We can see that traditional differences appear, for instance, urban areas and rural areas are very different in terms of meaningful connectivity. You can have here also the regions in Brazil vary a lot. We have the poorest regions with less meaningful connectivity. But take a look at male versus male. If in the access there are no difference, when it comes to meaningful connectivity, we have almost 10 percentage points more male with meaningful connectivity than female in the country. So this is very important. So when you do compound indicators and do more sophisticated analysis of the data you have, then you see very huge inequalities. And you can understand how to face those gender inequalities. In the next slide, please. We did the same scale. And we compared also, OK, so you have a more quality connectivity compared to those that have a low quality connectivity. What happens with your activities online? So if you go to using social media, or sending instant messages, or watching videos, the more communication and entertainment activities, there’s not much difference. There are some differences, but the differences are smaller. Then if you compare to more transactional activities, such as public services, financial services, and studying online, more or less the same what happened in Africa if you compare with the data that was shown before. So when it comes to doing the more important activities online that has more benefits to people, the connectivity is correlated. The low meaningful connectivity is correlated with low performance of those types of activities. And also the skills, which is very important. So those that have reported less digital skills are also those that have low levels of digital connectivity. Of course, those things are correlated. You don’t know what comes first. You don’t have skills, and then you don’t go for connectivity or the opposite. But this is important to understand the situation and to do policy recommendations in the field. And the next slide, just to say that, of course, we have very traditional, as was mentioned before, very traditional inequalities that also affect the online world. So this is still happening, and we need to, that’s why we need disaggregated data. We need very, you need to just not look. into the big picture but also disaggregated data. So here we can see when you break by level of education, for instance, and you compare the list of ITU digital skills that ITU recommends as to be measured by the countries, you can see that there’s a very huge gap between those that have more education and less education when it comes to digital skills. So this is another point arguing that we do need more sophisticated and disaggregated data to understand the digital inequalities. The next slide, please. Here, just to say, we have another survey with children and I have just one figure here to mention. It’s interesting to see among children how also the capabilities of recognizing the digital world still need to be developed and this need to be discussed and enhanced among children. So when we ask children, if you think that everyone find the same information when they search for things online, or if the first result of an internet search is always the best source of information, we have more than the half of children nine to 17 years old agreeing with this statement. To see that although you can have access, you can be online through social media, it’s another type of skills to understand how the algorithms work and how the digital world works. So this is another example of how we can be more sophisticated in the analysis. And to sum up, just to say a few words about CETIC. So we are a center based in Sao Paulo, Brazil that for the past 20 years is producing data on the access of the internet by different parts of the population and also by companies, by governments, by… schools and healthcare facilities and we are also a UNESCO Category 2 Center cooperating with Latin American and African countries in order to produce those type of comparative data. You can have all of this information available online if you want. And in the next slide, just to mention that we also have a few interesting programs of capacity building for researchers to apply these types of surveys and to produce comparable data and comparable information on the field of the Internet. But I’m not taking too much more time on this so we can have more discussion on the discussion phase. So thank you very much.

Moderator: Thank you very much Fabio. Again, very interesting presentation, very rich in detail and in the types of data that you’re collecting and what you can do with it. Same procedure, if there are any questions for clarifications at this point? Nothing. Then I suggest we move on to Claire, who’s online, who will talk to us about the GSMA results for lower middle-income countries. Claire, I hope the connection works and the floor is

Claire Sibthorpe: yours. Thank you. Can you hear me? Very good, very well. Okay, perfect. And I’m sharing some slides. Yeah, so I’m Claire from GSMA. I lead our digital inclusion programs, including our Connected Women program. And one of the things we do is we publish an annual report on the mobile gender gap, where we conduct nationally representative surveys on women’s access to and use of mobile Internet and the barriers they face across low and middle-income countries. So I thought it’d be useful to first start by highlighting the trends. As you can see from this slide where we started measuring the gender gap from 2017, that it had the mobile internet gender gap, so had been consistently narrowing up until about 2020 when it stood at 15%. Can you put him at full screen, Schleitz? Yeah, sorry, let me do that. Is it better now? Sorry. Is it showing up as full screen for you now? Yes, it is. Thank you. Okay, great. So this was sort of, I mean, good news. It was a high gender gap, but it had been reducing. And, in fact, we saw during the first phase of COVID when there was the lockdowns and people were stuck at home, a real reduction of the gender gap because, as women were, you know, having to go online to educate their children and such. But the fact is, and I think it was highlighted in the presentation by Rhea, you know, after COVID, you know, for two years after that kind of lockdown period ended, we saw that progress had stalled. There was a slowdown in digital inclusion for women and progress in the mobile internet gender gap had stalled because women were being very disproportionately negatively impacted by the immediate aftermath. And, in fact, the gap widened to 19% in 2022. Last year, when we published our latest data, we showed the gender gap narrowed back down to 15%. So women are 15% less likely than men to use mobile internet, bringing us back to where we were in 2020. And I really, I think I wanted to highlight this trend because it just shows how progress in closing the mobile gender gap is fragile and it’s not guaranteed. So what we really do need is we need to have concerted, targeted effort. And I think by having this data and showing the trends, we can see how different global events affect. affect it, but it’s, you know, while the recent narrowing shows a promising shift compared to two years, it’s absolutely not clear if the gender gap is going to, women’s adoption is going to continue to increase and the gender gap is going to still go. So, and I think it’s also important to note that even though, you know, we’re back to 2020 levels, it’s still quite a wide gender gap. There are still, according to our data, 265 million fewer women than men using mobile internet in low middle income countries. And I’m talking specifically about mobile because that’s the primary way that most people in these, in these regions access the internet. So now I’m going to go into sort of what it, what it means at different regions. And as we, as we show that there’s, this is, there’s a lot of differences in the gaps, depending on the country you’re in, the region you’re in and where you are in a country. So it’s, so that kind of 15% mass, you know, really big regional and national gender gaps. The majority of the women who are not using mobile internet, 60% live in Sub-Saharan Africa and South Asia. So these are the regions that have the biggest gender gaps. So in South Asia, it’s 31% and in Sub-Saharan Africa, 32%. This compares to a 0% in, in Latin America and the Caribbean. And in Sub-Saharan Africa, so we saw a lot of the reduction in the gap has been driven by South Asia and Sub-Saharan Africa. There hasn’t been a, there’s been some changes year on year, but there hasn’t been a really big difference from, in terms of the gender gap from what it was in 2017. So now it’s 32% in 2017, it’s 34%. So I think that just also highlights that, you know, it can, it’s, it can be difficult to make big differences. And, and as, as I highlighted in the previous slide, it’s, you know, any reductions are not guaranteed. And as was, I think, mentioned previously, you know, these gaps also grow and vary within countries. So in rural areas, the gender gaps are much higher than in urban areas. But it isn’t just about whether women are adopting the Internet, is it, are they able to use it to meet their life needs? And I think we see, again, we see that there are big gaps that we have kind of created this sort of high-level journey in terms of, I mean, recognizing it’s not necessarily linear, but in terms of going from owning a phone to kind of being aware of the Internet and using it and using it for diverse use. And what we see is that the gender gaps widen at every stage. So even if there might not be a gender gap in mobile Internet adoption, there is a gender gap in regular diverse use of the Internet, typically. So it’s important to understand these. We see that in our survey, once men and women become Internet users, the vast majority tend to use it every day, but that’s sort of often for a limited range of purposes. And in fact, in our recent research report, we asked whether people would like to use it more, and women were more likely than men to report that they would like to use it more than they currently do. This was true for sort of more than half of mobile Internet users in some of the countries we surveyed, like Ethiopia, Kenya, Bangladesh, India, and Pakistan. So I think in terms of addressing these gaps, it’s really important to understand what stops men and women from adopting and using the Internet, and I think it’s not a surprise that our data is very consistent with what research at ICT Africa says. What we’re being told in our surveys is that once women are aware of mobile Internet, the top barriers that stop them from adopting it are affordability, primarily of handsets, Internet-enabled handsets, and lack of literacy and digital skills. These are the same barriers that men face, but more and more women face these barriers than men because they’re more likely to be offline. And they also experience these barriers more acutely due to social norms and structural inequalities like education disparities in education and income. And then last year, for the first time, we actually asked what is the barrier stopping people, women from using it more, men and women from using it more. And the barriers aren’t as clear cut. So in terms of mobile internet adoption, very clearly handset affordability, literacy and skills are the top barriers across the countries. It’s not told as clear cut and it does vary by country more in the kind of use them for further use. But overall, safety and securities was a top reported barrier. And in fact, it’s one of the top three barriers in all the survey countries. And concerns around this includes like concerns around reliability of information found online, scams, fraud, information security, unwanted contact from strangers and fears of being exposed to harmful content. The second was affordability. This was primarily of data, but also of handsets. And I think we also had previously done some research just to kind of build on what was said before, looking at female microentrepreneurs and what’s stopping them from using. We also saw that similar to research, ICT Africa, female microentrepreneurs are much less likely than male microentrepreneurs to use mobile for their businesses. And even when they were using some of these services in their personal lives, they were not using it for business often because they weren’t even aware that it could be used for business. So I think again, it highlights that these barriers also differ depending not only in country, but your context and who you are. And we shouldn’t be painting women as a kind of homogeneous sort of group. So that’s at a high level. We have a lot more data in our report, and I’ll share that. as well as the report we published on female microentrepreneurs. But I think, just to get to kind of what do we think we can do. So, at a very high level, and again, we have more recommendations, but at a high level, we just really need to focus on this and set real targets. You know, as I showed in the trend slide, you know, we can’t be complacent. You know, it’s not guaranteed that the gender gaps are going to continue to decrease. And as has been highlighted many times, absolutely gender disaggregated data is critical to measuring and informing policies and investments and action to do this. So, while, you know, a number of us have surveys, as we’ve been saying, there’s a lot more data that’s needed to understand women’s mobile use, their needs, their barriers, and how this differs in different contexts and for different groups of women. So, we definitely need more data. And 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. So, for example, if you look at the barriers that we’ve mentioned, affordability, you know, can be improved by policies and initiatives that lower upfront costs for internet-enabled handsets, for example, lowering mobile-specific taxes or handset financing initiatives. And it’s also skills literacy and skills. There’s a lot that people can do to address that. But to kind of flag that our experience is that these barriers need to be addressed holistically. It’s not you need to think of both the affordability, the skills, the social norms, and all those things when you’re trying to tackle it. And kind of finally, you know, we all need to work together and partner with different stakeholders. No one group can do this on their own. So, I mean, just, I guess, to conclude, I think we need more informed, targeted action and investment by stakeholders. And I shared earlier that that the gap is big and it’s not always reducing. So I wanted to end on a slightly more positive note, which is that it is possible to make a difference. We do feel that this informed targeted action can make a difference. We have mobile operators who’ve made connected woman commitments to reduce the gender gap in their mobile internet and mobile money customer bases. And they have set clear targets for doing so and then are tackling these barriers. And since 2016, when these commitments first started to be made, we’ve seen that they have actually succeeded and have reached over 70 million additional women with mobile internet and mobile money services. So when having the data and taking that targeted action, it is possible to make a difference. So I hope we can continue the conversation here on what we all need to do. So I will stop sharing now. That was me.

Moderator: Thank you very much, Claire. That was very, very insightful as well. So we had three presentations, three different contexts, three different ways of collecting data, and basically all coming up with the same issues. First of all, are there any questions for direct clarifications to Claire? If not, I suggest we can move to a general debate. So I would like to ask the audience if there’s any issues they would like to raise, any questions, any suggestions, how to make the step from data to policy or some policy examples online. Yes, there’s a question there. Can we get a microphone there? If you can also please introduce yourself.

Audience: Hello, my name is Papa Second. I’m from the Virginia Institute of Economics. firsthand international data exchange, a vice-chair of the International Organization of Studies and Linkages, and also a chair of the European Police Parliament in this studio. from UN Women, Research and Data. Hi, Martin. Good to see you again. Good to see you, too. No, really interesting presentations and a lot to digest. And so just, I guess, a couple of questions from me. One is just wanted to understand, because I think each of you presented work that you’re doing, but I just was wondering how much of this is, for example, linked through official data through the National Statistical System? Do you work with the National Statistical Offices in the countries where you work at all? And if so, what has been your experience? And I’m asking because our experience working with NSOs is, again, has been, there are good things and bad things as well. And sometimes it was also using new data sources, including citizen-generated data, has really helped. So I was just wondering what has been your experience. And the second point is really more on, essentially, I mean, have you seen in your research or did you collect data on monitoring behavior, right? So this is linked to violence against women and controlling behavior where, essentially, a male husband, for example, may want to control what his wife does online. We’ve seen that when we try to measure online violence against women, online and offline, and as part of monitoring behavior. And I was just wondering whether this was something that you’ve looked at in your studies, and if so, what did you find? Thank you.

Moderator: Thank you very much. Those are two excellent questions. I have something to contribute on the first question, but I will first go through our panel. Maybe we start the other way around. So Claire, maybe you can tell something about how you collect the data, if there are any interactions with the NSO. We’ll take the questions one by one. So first, we tackle the first question, then the second one.

Claire Sibthorpe: I’ll answer. So the first one, the data I’ve shared is from our nationally representative surveys. We don’t collect the data from the statistics office, but we do refer to and look at the ITU data that was referenced earlier, which does come from the government. So we, but we don’t directly engage with those departments.

Moderator: Thank you, Fabio.

Fabio Senne: Thank you for your question. So, yes, in our case, Cetic participates in our expert groups, so we developed a model that I think is very interesting for highlighting these issues, that is a multi-stakeholder model for collecting or defining what to measure and what types of indicators are needed. So we have groups that the NSO participates, but the statistics regarding the ICTs are made by Cetic, but the NSO also has a few indicators and a few data on the ICTs that it also collects. So we work in partnership and the NSO validates and participates in the data we produce.

Relebohile Mariti: Thank you. So what we do is to work with national statistical offices to collect data. We go to individuals and households as well as micro-enterprises to learn of how they use these technologies and what barriers they face. So in our experience with working with national statistical offices, we had good working relationships in some countries, and well, like any other journey, there are countries where we encountered challenges. So I think that is the overall experience, to say. And who’s conducting the surveys? So we have the national statistical offices hiring field workers to do the surveys.

Moderator: Okay, thank you very much. From the ITU perspective, we actually do not do a survey ourselves. We only collect the data that are collected by the country, and usually and often it is the NSO, not always in some countries and in more and more countries, it’s the regulator that is either funding the survey or in some cases even conducting the survey. And there’s advantages and disadvantages. The advantage is that the regulator has usually money because they have funding from the operators. So they have money to conduct the survey, but you need the experience from an NSO for the sample sizes, etc., etc., for all the statistical work. It’s absolutely crucial that you work with NSOs or that NSOs do the work, because what we do, where we don’t get data, we make estimates. But we only make estimates for the high-level number of people using the Internet. We just don’t do that. add the gender breakdown but we cannot go into any detail about what people are doing online, what kind of barriers there are, what kind of skills they have. It’s impossible to make estimates for that and even if we would make estimates the estimates would be bad and we see how important it is to go beyond the headline number and into the desegregated numbers. So yeah, that really is a crucial point and so we need countries to get involved, NSOs to get funded for surveys. Now on the second question, again let me go through the panel and see if they have addressed online violence in their surveys. The other way around this time, Rele, you can start.

Relebohile Mariti: Okay, thank you and also with the last question, just to clarify, when I say we have the national statistical offices hiring, they do the hiring process but we have Research ICT Africa paying for the labor costs. So with online experiences, we did reports for individual countries and what we find in some countries, we find that there are cases where we find males be more likely than females to experience online threats but what we find is that this is more linked to what kind of information they share online. So in countries where we find that females are less likely to share their real name, their gender and their political views, that is where we find males being likely than females to experience online threats but in countries where we find that there are no differences in what information individuals share on social media, we find that females are more likely than males to experience online threats. Thank you.

Fabio Senne: Thank you. Now in our case in Brazil, we don’t have any specific survey on this on this thematic, although we have a few qualitative studies on this showing more in-depth analysis. It’s a very difficult topic to include in a typical survey because the responders tend to underestimate the rates of those cases. So we do need to combine more qualitative and quantitative analysis and we do have an experience with children. We run, since 2012, the Kids Online Survey, which is a survey with children from 9 to 17 years old and in this case we ask for a few we have a strategy for sensitive data collection with self self-administrative service with children, and we have a few data from things related to violence online and related to children on that. But regarding gender, we see some trends, for instance, in the case of Brazil, although we don’t see many differences in terms of the risks they feel online in terms of, for instance, for sexual violence, but when you talk about parent mediation, you can see that parents are more worried about the girls than the boys, the rates of mediation with girls is higher in the country, and also girls also report more cases of feeling bad online or having a problematic experience of usage, so we have a few experiences with children, but not with the overall adult population.

Claire Sibthorpe: Thank you. Claire, do you have anything on this subject? Yes, we do. We have a whole series of varied questions that we ask around, both on the kind of safety and security issues and whether it’s a concern that’s stopping you from either going online or using the internet more. We also have questions around whether family approval is an issue or not in terms of going online, and last year we asked some questions, extra questions, to look at, you know, this, so this, we see that this is a concern for both men and women, the safety and security concern, and as people get online, it becomes a more of a concern once you’re online, and so we asked some questions last year about whether people had personally experienced the safety and security issues, or whether it was a concern, and I don’t… wasn’t any big kind of big gender differences but although I would say that a lot of I think I think there’s two aspects to this in terms of preventing women from going online there’s a there’s the reality of it happening and you can see from our last report you know how many women versus men report this happening in reality to themselves and there’s a concern that it will happen and I think in our research we’ve seen some of the sort of gatekeepers or family members are concerned about their wives or daughters going online because of these risks so I think so I think it’s both the concern and the reality but it’s certainly an issue that is stopping women from going online and I think concerns some of these concerns are limiting their ability to go online or their online use and their use is limited in certain ways you know in an effort to sort of to address this perceived risk also I should say we did some research a number of years ago that looked at digital skills and what we found is that women were much less likely to know how to protect themselves online so they didn’t know there were things like privacy settings on Facebook and such and they they actually their skills levels and some of these ways to keep to keep themselves protected online were lower than for men so that’s also an issue thank you

Moderator: the only thing I would like to add to this question is that I see some issues in actually asking the question especially if this goes into a household survey where the survey may pass by the head of household who’s actually controlling it so either you don’t get the answers or you may not get the correct answers for the right answers because the women may not feel free to say whatever they want so that that’s a difficult issue in always in this this type of sensitive issue so you have to find a way to actually reach your target population in a way that they are free to answer but it’s it’s very important subject and investing in are there any other questions in the room please… Thank you very much.

Audience: I would like to ask if their research was only based on adult access to mobile phones, or even children. Because in most of the southern countries, in households, you find that even kids got access to smartphones even more than their parents. So maybe the access to internet may be maybe higher than the access to internet by parents. So I’d like to know if their research was only for adults.

Moderator: Yes, very good question. Fabio, since you have the mic, you may answer it.

Fabio Senne: Yes. Well, in our case, the survey I showed, it is covering 10 years old or more individuals. So we screen the household, and we select randomly one person that lives in the household that can be from 10 years old or more. So that’s what we cover in this data. And of course, we have data from what smaller children are doing online. We have data from reported by adults. So we ask adults if the children are using the internet. So we have also estimates from the youngest population. But you’re right that if you take the youngsters and young people use more intensively the internet than the adults, we can also disaggregate out all of this information for these age groups.

Relebohile Mariti: OK. OK, thank you. In our case, what we did was to only conduct interviews with individuals who are at least 15 years.

Moderator: Claire?

Claire Sibthorpe: Yeah, for our Mobile Gender Gap Report, it is adults. But I’ve just put in the link on the line. We have our State of Mobile Internet Connectivity Report, which looks at connectivity, and it does separate out adults versus those who are under 18 and how that makes it and also shared phone access and such. So it has more detail. It’s not. It has more detail on that, a bit more detail on that point.

Moderator: And in the case of the ITU, we collect whatever the countries are doing. So we depend on the service done in countries. We recommend, we have a manual. We recommend starting at the age of five because, as we know, children have different attitudes, different behavior than older people. But there are also legal issues in some countries where you can only start serving people starting at 15 or 16. So in the EU, for example, the age cut-off, it’s 15 or 16 to 74 often, although countries now are voluntarily also going below and above that. Certainly for 15-year-olds, 15- to 24-year-olds are much more likely to use the internet than other age groups. Below 15, it’s actually different. So the there’s really a point where all the children get online and a point where not all the children are online. So it’s actually very important to cover all those age groups so that you can see it in your data. Thank you for that question. Any other questions? Still no questions online. Let me ask a question, because we keep on saying that we need this data, and we do need this data for policy purposes. And Claire really gave a few directions of where policy should go. But it would also be good to know if the data are actually used by policymakers or if there are barriers there. And maybe Brazil is a good case here, because you do work with the policymakers, I understand. And how is the interaction with policymakers? How are your data used by the policymakers? And how do the policymakers ask you for specific data? Fabio.

Fabio Senne: Thank you, Martin. Yes, we have this multi-stakeholder model that I think it’s useful, because we do think that we do need to conduct surveys that are really useful for policymaking. So what we do is that before going to the field, in each iteration of the survey, we call an expert group composed by policymakers, and academics, and private sector, civil society. And they go deep into the survey to understand. Some of the indicators, of course, we keep because they are recommended by ITU or by international standards. So we want to have a time series of fixed indicators. But we also develop new indicators of new aspects that are relevant for policymakers in the field, so that we can be more responsive to that. I think this is useful, not just because the results are used more by the policymakers, but also because this gives legitimacy. to the survey process and also helps in the funding part of it. So how they, the more that they think that the results are useful, the more you can argue that they should fund, that there should be a guaranteed fund for keeping the survey occurring. And I think another important part of this is being very dynamic, because the field changes very dynamically. So the uses of what people do online changes. So, and we have to be very fast in incorporating these new trends in the survey so that you can give results that are more relevant to the policy makers. So that’s why this more participatory way of consulting the communities is good for keeping the survey relevant.

Moderator: Thank you. Rele, do you work with policy makers or how are the data used by policy makers?

Relebohile Mariti: So once we are done with doing the reporting, we do presentations, we disseminate our findings to the policy makers in their respective countries. And they have been, they have shown interest in using the data. And also after we have done the presentation, they always get to know what police interventions they can implement to address challenges in their respective countries.

Moderator: Thank you. Claire, I know you have some issues in actually hearing us, but, and you already mentioned some of the streams of policy interaction, but maybe you can elaborate a bit more or repeat what you said before about the interaction with- I think the question was, how do we engage with policy makers on this issue, if I’m correct?

Claire Sibthorpe: So, yeah, so obviously- We share our data with anybody who wants it. We’re keen to make sure people are doing evidence-based policies and programming. And we support governments on their policies. We run free training courses on both the digital gender divide as well as digital inclusion in general with policymakers, where we, again, share our data and recommendations. We have a whole report which outlines specifically policy recommendations in this space. So we’re very engaged. And we’re very keen that the data that we are lucky enough to be able to collect is available and accessible as much as possible to all stakeholders working in this space so that we’re all evidence-based in our work.

Moderator: Thank you. That’s excellent. I still see no questions. I’m going to ask one last question, and then we will wrap up. And it’s been mentioned already a few times, but it’s so important to have this data. And yet, we see so many gaps, especially in low-income and low and middle-income countries in countries collecting the data. And as I mentioned, the NSOs, they are usually underfunded. And ICT statistics are not a priority for them. So two questions. How did you manage to fund your data collection? And the second is, how can we make this maybe attractive to donors? Or how can we increase funding, especially to NSOs, to do this kind of data collection? And I think I will start with the positive example here. So Fabio, I’m going to first hand it to you, and then to the other two panelists.

Fabio Senne: Thank you. Martin, just to present on the Brazilian model, in the case of Brazil, the center where I’m from in Setic and it’s funded by NIC.br, which is the country code level domain .br register. So we use the funds that comes from the .br to provide society with more information, including service on the use of the internet. This is a unique model, and I think other country code level domains also invest in service, but this is something that can be done. But I do think that, as I mentioned, keeping the relevance of the indicators, I think is very important. It’s very interesting to see that if you go to all the, now you have very new strategies to measure AI readiness or AI capabilities of countries and all of them, in a sense, include data on connectivity on the capability of people to also be online and use the internet. So I think that the agenda changes, but we do need this very basic information on how people are dealing with the state. Now we have generative AI, so we are also expect to see some inequalities in the use of this type of tools, if you have surveys and data like this. So keeping the relevance and promote more stakeholder engagement throughout the process, I think there are good solutions and good ideas for making this type of data more available. Thank you.

Moderator: Maybe I first go to Claire.

Claire Sibthorpe: Sure. For our data, so, I mean, we feel that this data is really, really needed, and we just, we can’t do, we can’t really know what we’re doing and support our members without having it. So very fortunate that because of the lack of this data, especially gender disaggregated data. GSMA is funding the kind of core countries of our survey, our consumer survey, in the kind of core countries that allow us to do the modeling of the usage gap and gender gaps, because we absolutely need this data. And then we have we’re fortunate to have support from some of our donors to add some countries that they’re interested in to be able to compare across more countries, and also to do the modeling so that we can model these gender gaps. So that’s UK Department for International Development and UKAID and Swedish International Development Agency support us in terms of being able to add additional countries and do this modeling in these reports that we’re able to publish with the core countries coming from GSMA. But it is, you know, I think it would be great if this data was just there and done in more countries and by more people. We all need this data.

Moderator: Yes, indeed. Thank you very much. Rele?

Relebohile Mariti: So Research ACT Africa is a donor-funded organization. And the latest round of this survey was funded by the World Bank and the Bill and Melinda Gates Foundation. And so there is really a need for investment in this kind of data. And to make it attractive to funders, I believe what we can do is to stress the importance of this data and also show how this data can be used to create value. And again, as Fabio has already said, there is a need for collaboration and make the data easily accessible. So the data that we have is publicly available on Data First. for everyone to access it. Thank you.

Moderator: Thank you very much for that. I can add something from the ITU perspective. So we collect data from countries. We don’t have our own survey. We don’t fund our own service. We’re not a funding agency. We have tried a couple of times to see if donor agencies are interested in funding servicing countries, but they always say that that has to come from the countries, not from the ITU, and that’s reasonable. But it is important that there’s also a request for the data intrinsically from the countries themselves, from the policy makers, as we discussed. And we now have a project funded by the EU that’s called Promoting and Measuring Universal and Meaningful Connectivity. And in that project, we’re really trying to make the connection between the policy makers and the statisticians. We do a lot of workshops. We do a lot of advocacy. We explain what UMC is, Universal Meaningful Connectivity, how to measure it, but also why it’s important for policy makers. And we’re trying to get, at the country level, a dialogue going between the policy makers and the statistics people. So hopefully that will help as well. Before wrapping up, I’m going to give a last chance to the audience or online for a last question. I see none. So before thanking the panel, I would like to conclude that there is a difference in gender in how men and women access the Internet, how they use it, how many use it. But also, once they are online, men seem to make more of it than women, more activities than women. So how do we know that? We know that because of the surveys done in countries. And if we want to address it, if we want to move to a world where there’s gender equality in access and use of ICTs, you need to have the data to be able to address it. So we need more data, we need better data, we need survey data. And then once we have the data, we need to analyze the data at the detailed level, like, for example, we’ve seen in the presentation of Brazil, and everyone can do that. It’s not a difficult analysis, but you need to have the data. So the data is fundamental. There needs to be more funding for data from donors, but also from countries themselves that they see the importance of the data so that they can get some of the government funding, can go to data collection. There are different models, there are different ways of getting that, and we heard some of them here. But fundamentally, we need the data, countries need to have the data. With that, I would like to warmly thank the panelists, Rele from Research ICT Africa, Fabio from Cetic Brazil, Claire from GSMA, Zahra for the online moderation, and the organizers here. With that, let’s give a big hand for everyone, and thank you very much, everyone. Thank you.

Agreement Points

Gender gaps exist in internet access and usage

Moderator

Relebohile Mariti

Claire Sibthorpe

Fabio Senne

Persistent gender gaps exist in internet access and usage globally

Gender gaps are wider in low-income countries and rural areas

Progress in closing mobile internet gender gap is fragile and not guaranteed

Meaningful connectivity shows larger gender gaps than basic access

All speakers agree that significant gender gaps exist in internet access and usage, with these gaps being more pronounced in developing countries, rural areas, and when considering meaningful connectivity rather than just basic access.

Importance of detailed, gender-disaggregated data

Moderator

Relebohile Mariti

Claire Sibthorpe

Fabio Senne

Detailed, gender-disaggregated data is crucial for understanding gaps

Nationally representative surveys provide key insights

Data needed to inform evidence-based policies and interventions

Multi-stakeholder approach helps ensure relevant data collection

All speakers emphasize the critical importance of collecting and analyzing detailed, gender-disaggregated data to understand digital gaps and inform effective policies and interventions.

Affordability as a key barrier

Relebohile Mariti

Claire Sibthorpe

Affordability of devices and data is a key barrier

Gender gaps widen at every stage of internet adoption and usage

Both speakers identify affordability of devices and data as a significant barrier to internet access and usage, particularly for women.

Similar Viewpoints

Both speakers highlight how lack of digital skills, awareness, and social norms create additional barriers for women in accessing and using the internet effectively.

Relebohile Mariti

Claire Sibthorpe

Lack of digital skills and awareness is a major obstacle

Social norms and structural inequalities exacerbate barriers for women

Both speakers advocate for targeted, collaborative approaches involving multiple stakeholders to address the specific barriers women face in digital inclusion.

Claire Sibthorpe

Fabio Senne

Targeted interventions needed to address specific barriers women face

Multi-stakeholder collaboration is key for effective policymaking

Unexpected Consensus

Challenges in collecting data on sensitive topics

Fabio Senne

Claire Sibthorpe

Collecting data on sensitive topics like online violence requires careful approaches

Safety and security concerns limit women’s internet use

Both speakers unexpectedly highlight the challenges and importance of addressing sensitive topics like online violence and safety concerns in data collection and analysis, despite their different regional focuses.

Overall Assessment

Summary

The speakers show strong agreement on the existence of gender gaps in internet access and usage, the importance of detailed gender-disaggregated data, and the need for targeted interventions to address barriers. They also agree on affordability and lack of digital skills as key obstacles.

Consensus level

High level of consensus among speakers, implying a shared understanding of the challenges in digital gender inclusion and the importance of data-driven, collaborative approaches to address these issues. This consensus suggests potential for coordinated global efforts to bridge the digital gender divide.

Different Viewpoints

Primary barriers to internet access and usage

Relebohile Mariti

Claire Sibthorpe

Affordability of devices and data is a key barrier

Safety and security concerns limit women’s internet use

While Mariti emphasizes affordability as the main barrier, Sibthorpe highlights safety and security concerns as significant factors limiting women’s internet use.

Unexpected Differences

Overall Assessment

summary

The main areas of disagreement revolve around the primary barriers to internet access and usage, as well as the most effective approaches to data collection and policy development.

difference_level

The level of disagreement among the speakers is relatively low. They generally agree on the existence of gender gaps in internet access and usage, the importance of data collection, and the need for targeted interventions. The differences mainly lie in the emphasis placed on various factors and approaches, which could actually complement each other in addressing the digital gender gap comprehensively.

Partial Agreements

All speakers agree on the importance of data collection, but they differ in their approaches. Mariti emphasizes nationally representative surveys, Senne advocates for a multi-stakeholder approach, while Sibthorpe focuses on using data to inform evidence-based policies.

Relebohile Mariti

Fabio Senne

Claire Sibthorpe

Nationally representative surveys provide key insights

Multi-stakeholder approach helps ensure relevant data collection

Data needed to inform evidence-based policies and interventions

Similar Viewpoints

Both speakers highlight how lack of digital skills, awareness, and social norms create additional barriers for women in accessing and using the internet effectively.

Relebohile Mariti

Claire Sibthorpe

Lack of digital skills and awareness is a major obstacle

Social norms and structural inequalities exacerbate barriers for women

Both speakers advocate for targeted, collaborative approaches involving multiple stakeholders to address the specific barriers women face in digital inclusion.

Claire Sibthorpe

Fabio Senne

Targeted interventions needed to address specific barriers women face

Multi-stakeholder collaboration is key for effective policymaking

Key Takeaways

Significant gender gaps persist in internet access and usage globally, especially in low-income countries and rural areas

Key barriers for women include affordability of devices/data, lack of digital skills, and safety/security concerns

Gender-disaggregated ICT data is crucial for understanding gaps and informing evidence-based policies

Progress in closing the gender digital divide is fragile and not guaranteed

Meaningful connectivity shows larger gender gaps than basic access metrics

Multi-stakeholder collaboration is important for effective data collection and policymaking

Resolutions and Action Items

More investment is needed in gender-disaggregated ICT data collection

Policies should focus on addressing affordability, digital skills, and creating enabling environments for women’s internet access and use

Stakeholders should work together to keep ICT surveys relevant as technology rapidly changes

Unresolved Issues

How to sustainably fund ICT data collection, especially in developing countries

Best approaches for collecting data on sensitive topics like online violence against women

How to effectively engage policymakers to use ICT data for decision-making

Suggested Compromises

Partnering with national statistical offices, despite challenges, to conduct ICT surveys

Using multi-stakeholder models to fund and design ICT data collection efforts

Balancing the need for consistent indicators with incorporating new trends in ICT surveys

Although we have 88% or 90% that had some access to the internet, when it goes to the meaningful connectivity, we can say that today in Brazil, only 22% of the population has a meaningful connectivity, and being 30% are in the 0 to 2 of this scale.

speaker

Fabio Senne

reason

This comment introduces the crucial distinction between basic access and meaningful connectivity, revealing a much larger digital divide than raw access numbers suggest.

impact

It shifted the discussion from focusing solely on access to examining the quality and usefulness of that access, prompting deeper analysis of digital inequalities.

We see that the gender gaps widen at every stage. So even if there might not be a gender gap in mobile Internet adoption, there is a gender gap in regular diverse use of the Internet, typically.

speaker

Claire Sibthorpe

reason

This insight highlights how gender gaps persist and even widen beyond initial adoption, revealing the complexity of digital inclusion.

impact

It expanded the conversation to consider not just access, but ongoing usage patterns and barriers, leading to discussion of more nuanced policy interventions.

So when looking at don’t know what the Internet is, we see that 23% of females say that they don’t know what the Internet is, and this is slightly lower for males at only 19%.

speaker

Relebohile Mariti

reason

This statistic provides concrete evidence of a fundamental awareness gap between genders, pointing to deeper societal issues.

impact

It prompted discussion on the need for basic digital literacy and awareness programs, especially targeted at women.

After COVID, you know, for two years after that kind of lockdown period ended, we saw that progress had stalled. There was a slowdown in digital inclusion for women and progress in the mobile internet gender gap had stalled because women were being very disproportionately negatively impacted by the immediate aftermath.

speaker

Claire Sibthorpe

reason

This observation highlights the fragility of progress in digital inclusion and how external events can disproportionately affect women.

impact

It led to discussion about the need for sustained, targeted efforts to close the digital gender gap and the importance of considering broader societal factors.

Overall Assessment

These key comments collectively shifted the discussion from a focus on basic internet access to a more nuanced examination of meaningful connectivity, persistent gender gaps, and the fragility of progress. They highlighted the complexity of digital inclusion issues, emphasizing the need for targeted interventions, sustained efforts, and consideration of broader societal factors. The comments also underscored the importance of detailed, disaggregated data in understanding and addressing digital inequalities.

How can we increase funding for ICT statistics collection, especially for National Statistical Offices in low and middle-income countries?

speaker

Moderator (Martin)

explanation

This is important because many countries lack sufficient data on ICT usage, particularly gender-disaggregated data, which is crucial for evidence-based policymaking to address digital inequalities.

How can we make ICT statistics data collection more attractive to donors?

speaker

Moderator (Martin)

explanation

Securing funding is critical for conducting comprehensive surveys and ensuring consistent data collection over time to track progress in closing digital divides.

How can we better measure and address online violence and controlling behavior related to women’s internet use?

speaker

Audience member (Papa Second)

explanation

Understanding these issues is crucial for developing policies to ensure women’s safe and equitable access to digital technologies.

How can we improve data collection on children’s access to and use of mobile phones and the internet?

speaker

Audience member (unnamed)

explanation

Comprehensive data on children’s digital access and usage patterns is important for understanding overall household connectivity and developing targeted policies for youth.

How can we enhance collaboration between researchers, National Statistical Offices, and policymakers to ensure ICT statistics are relevant and used effectively?

speaker

Fabio Senne

explanation

Stronger partnerships can improve data quality, relevance, and utilization in policymaking to address digital inequalities.

How can we develop more sophisticated analysis techniques to uncover hidden inequalities in ICT access and use?

speaker

Fabio Senne

explanation

More nuanced analysis, such as the meaningful connectivity scale presented, can reveal disparities that are not apparent from basic access statistics alone.

What policy interventions are most effective in creating an even playing field for women’s participation in the digital economy?

speaker

Moderator (Martin)

explanation

Identifying successful policy approaches is crucial for replicating and scaling efforts to close gender gaps in ICT access and use.

Which countries have provided evidence of an enabling environment for equal participation in the digital economy, and what were the key success factors?

speaker

Moderator (Martin)

explanation

Learning from successful examples can inform policy development in other countries seeking to address digital inequalities.