Champions tracking gender balance

BBC 50:50 UK, Global

The BBC releases its 50:50 challenge impact results annually.In late 2016, BBC presenter Ros Atkins started to experiment with improving the gender balance of the sources featured on his TV programme, Outside Source. His team started to collect data on who appeared in each broadcast, identified subject areas and stories where women were underrepresented

and expanded their network of highly qualified women sources. As a result, women sources featured on the programme went from 29% to 51% in the space of four months. And while the BBC’s broadcast rankings went down 2% in two years, Outside Source’s rankings went up 25%. Since then, more than 500 BBC programmes have joined the project, dubbed 50:50, and more than 20 external media partners have signed up to replicate the idea.

The methodology behind the 50:50 project is relatively simple. Production teams independently collect data on the gender balance of their broadcasts, using a measuring system adapted to the nature of their programme. Data is shared each month among all those who participate. Given that the programmes which take part range from news to music to politics, the measuring system can be adapted to suit the nature of each broadcast. For instance, in a television show where the presenter is controlled by the network, he or she would be excluded from the final count, whereas a production team that can determine who presents the programme may include presenters in their figures. Atkins’ reasoning for allowing these adaptations is that teams are more likely to trust and act upon the data they collect if they have a say in establishing the methodology.

Naturally, the data collection has to be credible enough for teams to believe in the numbers, but the data itself is not the end goal of the project. Rather, it serves as an engine to help drive change and motivate participants to increase the number of women in content.

FINANCIAL TIMES UK, Global

When the Financial Times (FT) defined the size of its women audience for the first time in 2016, it found that it was relatively small and disengaged. Viewed as both a concern and a business opportunity, this realisation brought about several projects aimed at changing women subscribers’ perception of the brand, increasing women engagement and driving internal cultural change. One of these projects is the JanetBot, a machine learning tool that uses facial analysis software to identify the gender of people in images used by the FT. It shares gender classifications with editors via coloured on-screen flags and gender balance data via a Slack channel.

Within the organisation, the bot’s goal is to raise awareness of gender imbalance in home page pictures and encourage journalists to increase the number of images featuring women. It also serves as a tool to boost engagement among their women audience – FT analysis shows that women are more likely than men to click on stories illustrated with pictures of women. The FT has learned several lessons from launching the JanetBot. For starters, those who will be using the product need to be involved in the design process from the start. Once it has been developed, ironing out features that users find unhelpful can be hard and that hasn’t been possible with the JanetBot due to limited resources.

As a result, the bot’s purpose has now shifted towards raising awareness of gender balance among newsroom staff rather than data collection, reminding journalists to consider the gender balance of pictures early in the life of a story. The FT has also been experimenting with bots to track the number of women and men contributors featured in stories to help journalists achieve a more balanced split.

The bot She Said He Said, launched in 2018, keeps track of the gender balance in sources by counting men’s and women’s pronouns and names, sharing data automatically with FT teams. However, encouraging them to look at this data and take action has proved challenging. This has led the FT to explore a manual approach to tracking and improving gender balance instead, having signed up to the BBC’s 50:50 project this year. Although the experiment is still in its early stages, the 50:50 methodology seems to raise awareness of

imbalances and engage colleagues more effectively than the automated approaches. (See The Financial Times Deep Dive)

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