Women in media: What we know so far
Hearing that women in mainstream media are portrayed stereotypically, probably doesn’t surprise you. But we, as a humanity, should stop dismissing important societal issues by saying – It’s normal, there’s nothing we can do about it.
Sure, we all know about it, but when you see the actual data supporting this premise, you might as well stop and wonder how serious of a problem it is.
So, here are the most important stats about women in media gathered in a global monitoring project, “Who Makes the News?” that takes place every five years. The cited report was published in 2021, with 116 participating countries and over 30,000 analyzed stories.
- In TV news, women were subjects or sources in only 13% of the sample.
- Only 1% of analyzed major news stories were marked as “gender and related”, including violence against women and girls.
- In all news, there’s only 3% of women aged 65-79, compared to 15% of males of the same age.
- In traditional media, women report 4 out of 10 stories.
- Among experts in media, 24% of them are women. However, they’re most commonly experts in the following fields:
- Personal experience providers;
- Popular opinion givers.
The latter shows us that women are still heavily underrepresented as experts in hard science or politics.
If we keep moving at this pace, when will things change?
The researchers shared their point of view:
All things remaining equal, it will take at least a further 67 years to close the average gender equality gap in traditional news media.
– GMMP, 2021
Let it settle.
New AI research on women in political debates
Researchers from the Rochester Institute of Technology, led by Ashique KhudaBukhsh, Assistant Professor of Computing and Information Sciences, conducted a large-scale analysis of interruptions in political discussions on cable news.
Namely, the authors have spent around three years analyzing over 625,000 dialogs from cable news networks (CNN, Fox News, MSNBC) that took place between January 2001 and July 2021.
Side-to-side comparison of female vs. male representation in the analyzed sample looked like this:
|Average number of words per chance to speak
In other words, although female speakers tend to interrupt more frequently than their male counterparts, they are also more considerate when interrupting. Furthermore, it may be interpreted as their way of fighting for a chance to gain more space in the media, considering they get fewer opportunities to speak in political discussions.
Although gender equality in this environment wasn’t their primary motive for research, the lead author underlines how important these findings are:
Analyzing interruptions at this scale provides meaningful insights into subtle conversational dynamics and how they vary across race, gender, occupation and political orientation.
– Ashique KhudaBukhsh
Why is introducing AI into academic research important?
Now, you may wonder how is AI research in this field relevant and what its advantages are.
First of all, as shown in this example, AI is able to produce large-scale analysis based on data available from decades ago, and provide you with valuable insights in a relatively short amount of time.
This step of the process is inevitably more efficient in comparison to human-deducted analysis. Moreover, it ensures more time for researchers to interpret the data.
Not only that but, if given precise inputs, AI analysis will be 100% reliable. In other words, it eliminates the possibility of human error.
If we take this approach to a global scale, and equip researchers from different parts of the world with the same tools and methods, AI will guarantee coherent and accurate data from each participating country, giving more credibility to the findings themselves.
And we saved the best for last.
The AI method developed by the Rochester Institute of Technology enables real-time analysis of talk shows, interviews, and political debates. This level of efficiency would be impossible to be done by humans in a continuous manner.
This technology is not only fascinating but profoundly useful as well. For example, during elections, the public could have real-time information about serial interrupters and therefore give a chance to balance out the media space and ensure civil discourse.
What we see in practice is a post-election analysis of media coverage, when the damage is already done and we can do nothing about it. By introducing AI, we could have accurate, timely information about political debates, based on actual data and not subjective feelings or perfidious propaganda.
On that note, this may be more necessary than ever, considering that the rate of unfriendly or intrusive interruptions has been gradually increasing, as shown in the cited analysis.