Thoughtful Data Crunching with Tortoise Media - Key Takeaways
Our partner, Tortoise Media is a slow news organisation that focuses on matters that are driving the news, spending time reporting on the unseen.
Recently, I was fortunate enough to attend the very first exclusive Stack’d workshop for the Multiverse Community hosted by Luke Gbedemah, Tortoise Media Data Reporter.
We looked at Tortoise’s fresh approach to journalism, crunching down on the important data to call out what really matters. Luke took us through three Tortoise news reports to teach us how to error check as a form of fact-checking, how to pick data that is going to be interesting to your audience and how to use data to position your piece of writing to form an argument.
The session began by Luke posing two statements to us and asking us to think about what sources we would look to to sense check them:
‘The UK’s vaccine programme is ‘worldbeating’...’ and ‘Mental Health care isn’t accessible enough for young people…’
For the first statement, it is important that the measure or metric by which the UK’s vaccine programme is ‘world-beating’ is considered and for the latter there are a lot of implicit conditions e.g what makes you a young person? Both statements lack nuance around intersectionality.
To understand the process that data goes through in order to tell news stories that really matter, Luke took us through three stories produced by Tortoise that are empowered by data:
1. At a Tortoise Media open news event, a member said ‘Mental Health services, particularly during the Pandemic, are stonewalling people, they are not accessible enough and people are finding themselves in crisis.’ This was more than a tip, rather an observation of lived experience, Luke explained that it was vital to crunch down on the appropriate data that would back up this statement from a trustworthy source and to pick data that will position your piece of writing, the step by step process included:
- Accessing the Mental Health Monthly Statistics from NHS Digital to establish how many people are waiting for care and what are the waiting times. Luke established that 34,000 people in England had waited over 12 weeks for an appointment.
- To then take this data further, Luke looked at an alternative to the NHS, the private sector, to see how much it would cost the average person per hour for therapy. To do this, Luke used ParseHub, a free and easy to use Web Scraping tool that lets you repeatedly gather information from the site into a CSV. The data uncovered that the average price for an hour of talking therapy with a BACP registered therapist was £50.
- In order to corroborate this data, Luke then checked the ONS for the average weekly household income, which was found to be £562.
- To finalise this report, Luke then spoke with people who had previously spoken out through access to mental health care charities as they couldn’t afford private appointments but also could not wait 12 weeks for an appointment.
2. The next example that Luke took us through was around being thorough with your research to produce a robust article and this Tortoise Media piece was used to display how to do this:
Here, it is important to understand that for the companies, people and the matter in question, this is a private and sensitive topic, and executives may ‘prefer not to say’ out of fear of discrimintaion. However, we must remember that the subject is important as it shows a lack of visible leadership, the report is not centred around calling out the companies or the people who have chosen not to disclose but in fact looking at the bigger picture. So how did Luke make sure that the companies felt like they were treated fairly and that the reader understood what was going on?
- After partnering with The Valuable500, Luke then collected data from every annual report from every FTSE100 company and this was then sent over to each company.
- Luke then liaised with the companies’ Sustainability, Inclusion and Diversity representatives, inputting any amendments and responses into the report and analysing the findings.
3. The third and final story that Luke took us through was a data story centred around green finance which was a great example of data visualisation and how you can start with a big data spectrum and see something quite distinctive within that data, to go and investigate:
- The initial data in this story was collected from Crunchbase, an API accessible source of information around public and private businesses. This data story is the beginning of what will become a bigger investigation into how the green energy transition has happened over the past 10 years.
- The story begins by seeing the US as the clear leader in investment in renewable energy with steep rises in Russia, India, Spain and Canada. Following the data story through, it looks at the number of renewable energy startups / their funding and shows since 1994 the development of patents and where in the world they were being listed. China, which was previously underrepresented, massively accelerated their list of patents and renewable energy technology in 2008, massively outstripping other economies - leading Luke to investigate why this was.
The key takeaways to remember from this event are:
1. News has changed a lot in recent years:
- We read it fast
- We get over it faster
- We don’t always know where it comes from
- We don’t know if it’s been influenced or paid for
2. The reality is not many people will spend time thinking about what sources of data they can trust or sense checking themselves, so it is important that the data we provide is trustworthy and robust.
3. It is important to present the data in a way that positions your piece of writing and argument, yet still treats the parties in concern in a fair way.
Redeem your free membership!
We’re delighted to be partnering with Tortoise Media, giving our Community access to world-class journalism, mentoring and thought-provoking events. Redeem your free, 12-month membership (RRP £100) at this link and enter the code TEAMMULTIVERSE