Publishing research is a crucial way for academics to share their findings with the scientific community and beyond. However, this Carbon Brief analysis reveals that women and researchers from the global south are underrepresented in the authorship of highly cited climate science research.
As well as the data analysis, Carbon Brief interviewed a diverse range of experts at length to explore the reasons for the biases, their personal experiences, and their thoughts on next steps. Quotes from the experts are featured throughout the piece.
The article was picked up by a range of media outlets. BBC News and Forbes wrote articles on the analysis quoting its lead author, Ayesha Tandon, who also appeared on the BBC Global News podcast, Lancet podcast and Ticker News show for segments dedicated to the piece. Interest in the piece has been prolonged, and Ayesha is due to present the findings at a colloquia for Utrecht University later this year.
The main finding of the analysis – that men from the global north are over-represented in highly-cited climate science research – is unsurprising to many. However, by leading with eye-catching numbers, the article opens the door to a more in-depth discussion into the systemic issues in academia.
Importantly, the analysis emphasises the implications of the lack of diversity in climate science research – that the existing bank of knowledge around climate change and its impacts is skewed towards the interests of male authors from the global north, creating blind spots around the needs of some of the most vulnerable people to climate change.
Many scientists engaging with the article on Twitter empathised with it on a personal level, having faced many of the barriers discussed, and praised the effort made to amplify voices from under-represented groups.
Ayesha identified the most highly cited academic papers published over 2016-20 using Google Scholar Metrics data, and selected the climate science papers manually. She then recorded the gender and country of each of the (1,300+) authors in Excel.
Ayesha decided to present gender as a binary “male” or “female” for ease of analysis, but acknowledges in the methodology this characterisation of gender is simplistic. To assign a gender to each of the authors was a difficult process. Ayesha used the pronouns in the author’s official “about” webpages where possible. However, when this was not possible, she determined their gender from images, by emailing the authors to ask, and with the API genderize.io – although she recognises that this method does not guarantee accuracy.
The Carbon Brief digital team translated the results of the analysis into both spatial and graphical visualisations for optimal effect. They used the Highcharts JS library to produce three interactive charts showing the national, continental and gender distribution of authors. To present the data spatially, they computed Natural Earth boundary data in QGIS to build a choropleth map of the physical distribution of authors by country. They then exported this as an SVG, cleared and annotated in Adobe Illustrator. The visual components of the story were used to promote the analysis on Carbon Brief’s social media channels, including its 100,000 followers on Twitter.
What was the hardest part of this project?
The piece is in-part a response to the “Reuters Hot list”, which highlights the 1,000 “most influential” climate scientists – largely based on their publication record and social media presence. Scientists from the global south and women are vastly under-represented in the list, but the piece does not discuss the reasons for the imbalance. The Carbon Brief piece is framed around unpacking the reasons for the trends. The piece does not aim to diminish the achievements of scientists highlighted in the Reuters Hot List, but rather to highlight the systemic biases in academia that make it easier for some academics to succeed than others.
The hardest part of the project was choosing which papers to analyse. Ayesha initially planned to use Altmetric rankings, which rank a paper’s “influence” through mentions in media and social media engagement. However, she eventually decided that using solely citations is a cleaner metric, which would provide more of a focus for the piece. To identify climate science papers, she first considered a tool developed by a colleague, which filters papers using keywords. However, it quickly became apparent that too many climate science papers would be excluded from the final list using this method. She ultimately decided to go through the google scholar citation rankings of relevant journals and manually select the climate science papers because, although this method was time consuming, it had the lowest margin for error.
What can others learn from this project?
This piece highlights that even “obvious” findings can be used to build an interesting data journalism story. The finding that women and countries in the global south are under-represented in the authorship of highly cited research is unsurprising to many, but forms a solid backbone for a discussion around the systemic issues in academia.
The interviews conducted for this piece demonstrate that even when the drivers behind your data seem obvious, it is important to talk to people with different backgrounds to capture a range of opinions and lived experiences. Contrary to our expectations before beginning this project, every individual interviewed for this piece emphasised different issues – often raising points that we had not considered before, and brushing aside points that other experts highlighted as crucial.
Getting a well-rounded view of the issue was a significant time commitment, and publishing the data analysis alone would have taken a fraction of the time. However, the insights gained from these interviews were invaluable additions to the piece, providing crucial context behind the data.