I began my journalism career in August 2017 as a trainee multimedia reporter at a small newspaper, the Hertfordshire Mercury. I arrived down a non-traditional route, without the usual qualifications – I had not studied journalism or taken a National Council for the Training of Journalists course. In my early days, with no contacts and inexperience on my side, I found open data a great way to generate stories. I would read national newspapers for data-driven stories that I could try to track down figures for and localise. I learned firsthand however how difficult it can be for stretched local news journalists to find the time to get to grips with and interrogate data when faced with day-to-day news cycle demands within a shrinking workforce.
From here I moved onto a role as data journalist for Radar AI, the Press Association’s local data news agency. Here I learned to use Natural Language Generation software to produce data-driven stories on a mass scale for hardpressed newsrooms across the UK. I found open data, nosed out stories, cleaned and analysed datasets and fed the figures into the NLG CMS where I wrote conditional scripts that would cover every scenario the data could throw up for each local area within the dataset. That could range from 43 police forces in England and Wales, to 350 lower-tier local authorities, generating a story for each locality that would then go out to hundreds of clients. I stayed at Radar for more than two years, rising to senior reporter after one year, before taking up a new position as data and investigations editor at JPIMedia, where I have been since October. During that time I won data journalist of the year at the Regional Press Awards for a portfolio of stories which included reports on failures by local authorities – and in particular the private companies they employ – to carry out safeguarding interviews for children who go missing from care, and on allegations of abuse of vulnerable patients within care homes.
I am not a data scientist and do not pretend to have training and skills to that effect – I am a journalist with a strong local and national news sense who can mine data for the nugget of a story, contextualise it and present it in compelling copy that tells the reader the human story behind the numbers. With this approach, I’ve made use of the vast and underutilized wealth of open data in the UK to provide public interest journalism to newsrooms up and down the country – both while at Radar, where I would generate hundreds of ready-to-print stories at one time, and now at JPIMedia, where I distribute data and copy to all our 100+ titles and support newsrooms with data journalism and their coronavirus coverage. In the past four months that I have been with JPI I have turned towards data visualisation tools for the first time, using Flourish to create a wide range of charts to illustrate my stories and bring data to life for readers.
I believe I should be considered for this award based on the strength of my data-driven portfolio, the breadth of my reach and track record bringing high quality and impactful data stories to underserved communities, and the fact that I have done so without any formal training in data journalism.
Description of portfolio:
Data journalism exploded into every newsroom in 2020, with many unprepared journalists having to adapt to serve an increasingly data literate audience. With coronavirus case and death statistics coming thick and fast, I have tried to deliver data-driven stories that approach the pandemic from an angle, contextualising the impact of the health emergency on different groups and communities.
This has included:
An analysis of NHS data that showed referrals to mental health services had fallen by 57% in April, as medics and charities warned people were struggling to access support during a time of increased stress and anxiety
An analysis of cuts to local authority public health budgets in the years leading up to the pandemic and how this could have weakened councils’ preparedness to respond
Exploring the prevalence of overcrowding in each council area in England and Wales at the start of the first national lockdown, and the challenges it presented for poorer households trying to follow self-isolation guidance
An overview of existing understaffing of children’s social services amid concerns the pandemic would only make children more vulnerable
An analysis of the use of zero hours contracts among care workers, and unions’ fears that it could prevent staff self-isolating
Analysis of the number of retail jobs lost in every council area in Great Britain, as news broke of the collapse of Debenhams and Arcadia (this threw up some interesting lines in local areas, such as a surge in jobs in bakeries and butchers in Yorkshire)
The story I was proudest of in 2020 however was a national story I wrote for the Press Association on domestic abuse. I was trawling through a large NHS dataset on hospital admissions due to an external cause. While reading through the list of diagnosis codes, one caught my eye – ‘Y07 – Other maltreatment’. After looking up the code in the International Classification Disease dictionary I discovered this was a category that encompassed domestic and sexual abuse. Analysis of the figures showed admissions among female patients had increased by a third in five years, and it was the second most common cause of female assault admissions. Meanwhile admissions of women for rape and sexual assaults had increased by 89%. When I spoke to domestic violence charities, it transpired they had not been aware this data existed, and the story I wrote was an exclusive and broke new ground. Once published, the story generated a lot of interest among domestic violence organisations, women’s charities, and the Victim’s Commissioner for England and Wales. The charities believed the figures strengthened the case for independent domestic violence advisors (IDVAs) in hospitals, as medics were clearly routinely encountering abuse victims. I have since returned to this topic and I am now undertaking a more indepth project, using FOI requests to obtain data at a hospital trust level and to gather new statistics on how widespread the use of IDVAs is at present.
Please note that many stories do not carry my byline as Radar was a news agency. I can provide screenshots/downloads direct from Radar’s wire service however of the original article with my byline. I have selected ‘big organisation’ as JPIMedia is a large organisation however the bulk of the work I have submitted was produced at Radar, which was a team of fewer than 10.