Page 49 - ITU Journal - ICT Discoveries - Volume 1, No. 2, December 2018 - Second special issue on Data for Good

ITU JOURNAL: ICT Discoveries, Vol. 1(2), December 2018

In the following sections, we describe two case limited than that on Internet access. Data from the
studies that both use online advertising audience GSMA, a trade body representing the interests of
estimates from Facebook. However, the same mobile phone operators worldwide, on gender gaps
general approach has been applied using LinkedIn in mobile phone ownership were available for only
to obtain statistics on gender skill gaps in the US 22 countries. In light of these shortcomings of
[17]. existing data sources, the Data2X initiative at the UN
Foundation identified gender-disaggregated data
3. CASE STUDY 1: INTERNET ACCESS for access to Internet and mobile phones was
GENDER GAPS identified as one of the most pressing gender data
gaps.
5
Achieving gender equality by 2030 is Goal #5 of the
Sustainable Development Goals. One of the targets In this data sparse context, data from Facebook’s
for this goal is to “enhance the use of enabling online advertising audience estimates, which can be
technology, in particular information and queried for aggregate statistics on the number of
communications technology (ICT), to promote users of the platform by gender, age and device
the empowerment of women” . Corresponding type, have been leveraged to measure and ‘nowcast’
4
indicators of interest relate to gender- gender gaps in Internet and mobile access [19].
disaggregated statistics on Internet usage and Nowcasting refers to the idea of ‘predicting the
mobile phone ownership. The adoption of these present’, especially in the case of indicators where
SDG targets related to gender and ICT use real-time information is useful but where there is
acknowledges that even as the use of ICTs has likely to be a significant delay or lag in producing it
rapidly expanded, significant gender gaps in access [20].
to these technologies persist. The International
Telecommunication Union (ITU), the UN’s The Facebook data was used to generate a
specialized agency for ICTs, estimates that some “Facebook Gender Gap Index” (FB GGI), an indicator
200 million fewer women are online compared with of the number of female to male Facebook users in
men, with Internet use gender gaps being a given country. For example, in Belgium we
significantly greater in less developed countries observed an equal number of 3.1M female and male
[18]. However, the paucity and irregular production monthly active Facebook users, whereas for India
of gender-disaggregated data on Internet and there were 40M female and 133M male monthly
mobile phone access, particularly in less developed active Facebook users as of October 2018.
country contexts, present significant challenges
towards monitoring the progress towards these While the FB GGI reflects gender gaps in Facebook
goals. use and not Internet access per se, in practice these
Facebook indicators are highly correlated with
Currently, the best available data source for officially reported statistics on Internet (from the
gender-disaggregated statistics on Internet use is ITU) and mobile phone gender gaps (from the
compiled by the ITU, based on surveys fielded by GSMA) for the countries for which this data is
the national statistical agencies of ITU member available. This suggests that these online, Facebook-
states [19]. Although year-to-year availability of derived indicators are useful measures that can be
this data for different countries vary, estimates for used to inform predictive regression models that
at least one year in the period 2011 to 2015 was are validated against official statistics.
available for 84 countries (out of 218 in the world). Furthermore, the FB GGI appears to capture gender
The most limited coverage was for low-income inequalities in Internet access most effectively in
(data available for 2 out of 31 countries) and lower- less developed countries where access to the
middle income countries (data available for 11 out Internet is most unequal by gender.
of 53 countries). Data availability for countries in
sub-Saharan Africa (4 out of 48) and South Asia
(1 out of 8) are especially limited. Statistics on
mobile phone ownership by gender are even more

4 See the description of goals, targets and indicators at 5 See https://www.data2x.org/what-is-gender-data/gender-
https://unstats.un.org/sdgs/indicators/indicators-list/. data-gaps/.

© International Telecommunication Union, 2018 27