When was the last time you watched a news video and saw a bit of yourself in the person or community being covered? The probability of seeing yourself represented depends heavily on where you live or the community you identify with. This means some of us see much less of ourselves in the news stories being covered.
Video stories covered by newsrooms and content creators rely on the footage they have access to. And the easiest footage to get access to is open licensed footage online. Open licensed footage means videos published online under a license that allows reuse by others for their content. Creative Commons (CC) freely offers six different licenses and two public domain tools, allowing content creators to choose the terms by which they share content. Content creators keep their copyright, but can choose if others reuse their works, and if so, on what terms. For example: CC0, which is the the most permitting license under the Creative Commons umbrella. You can find out more about it here.
We are actively working on projects to reduce the gap in CC footage available online. And this survey will help guide our efforts in the direction that's most useful to working journalists and creators of nonfiction video. So, if you or your friend work in this space and have have 5-10 minutes to spare, please consider filling this survey or email us your thoughts/feedback by
clicking here.
The valuable information from this survey will guide our collaborative project on making journalism and storytelling more diverse and inclusive around the world. We really appreciate you taking the time to engage with this work.
And if you want to know a little more about us, we are
In Old News. We are a small company working on supporting a diverse journalism ecosystem. We do this by training journalists and also by sharing resources in the form of stories and free online courses. You can check out our work at inoldnews.com
Privacy Policy: We care about your privacy and will not publish any of your personal information without your consent. We will only use the analysed data without any individual identifiers for our reports and projects.