Redefining Impact [or] Metrics to Match Your Mission
What would happen if we changed what it means for journalism to have impact? Traditionally, when we talk about impact journalism, it follows a pattern of articles being written and a law changing or someone stepping down from their role. This idea doesn’t leave a lot of room for the other impact journalism has on communities — like trust, media literacy and access to actionable information. We’re going to discuss how to rethink the impact you’re tracking as a result of your journalism and then the next big step of actually tracking it.
Leavers Survey: Former Journalists of Color on Retention, Public Service, Diversity
This session is where participants can discuss how to retain journalists of color in newsrooms, particularly those at mid-career and up. I'll debut the results from an informal early Spring 2020 survey of former journalists of color in the hopes of: 1) seeding a data-informed discussion space for SRCCON participants; 2) mobilizing participants around the use of data to determine: where do we go from here? and 3) hopefully, carving out space for JOCs (cub journos, especially) to weigh the 'exit interviews' of those who've gone before them.
On top of the language barrier on documentation and UIs, journalism startups that develop products for and from Spanish speaking countries have to face multiple challenges such as tools and SaaS prices that are super prohibitive for people outside the US, the lack of payment methods, lower bancarization rates and less access to tech and connectivity, to name a few examples.
How do we develop profitable media products that fit these contexts and what can we in the intersection of journalism and tech do to help reverse this situation.
Demystifying the Mythologies of Data Visualization
We live in the age of data visualization, but has it always been that way?
Ever since the first Assyrian and Greek stories, humans have passed down their love of storytelling and tradition in the form of myths. These myths are often inspired by true events, but other times they are entirely fictional. Myths can sustain long-standing traditions, prevent people from questioning norms, and ultimately persuade an audience towards a certain belief or action. Much like many aspects of society and culture, the field of data visualization is rich with its own mythologies and problematic histories. Did data visualization help spur Manifest Destiny? What was the objective of maps containing "moral statistics"? What is the truth behind the myth that unbiased data leads to unbiased models?
This session will include a brief history of data visualization and its mythologies, insights from both theoretical and modern texts, and interactive brainstorming activities. We’ll share how we've encountered the myths of data visualization in our own work and learn how to contextualize them for diverse audiences.