People moan about falling standards in the media but there never seems to be any evidence of a time in the past where there was a higher quality. Either these people are referring to points in history where elites have controlled the agenda and access to audiences or to an unexamined nostalgia for the content they enjoyed at some formative moment in their past.
If the FT decides to drop its paywall we might have a really interesting competitor in the serious news space.
Finally read a Fast Company interview with Chris Wiggins, not the greatest interview in the world. Journalists are clearly still awed by STEM professors. The piece confuses data-driven editorial and data journalism which are two different things in my mind.
It also washes around the general lamentation about ignorance of statistics (learn to code! learn stats! understand the scientific method!) which feels like one of the dilemmas you have when you hire academics into commerce.
It feels like the current quest for the predictive indicators of news stories are like a new El Dorado, filled with strange characters with excessive hopes. It's unclear to me what anyone hopes to do when they do find El Dorado. Create the ultimate story by hitting all the points in the indicators? Change a story so it will do better?
The obvious thing is to find the aspects that will cause a story to suffer unduly and fix them but that's not a good story for techno-utopian blogs (or even interesting).
Wiggins also fails to articulate what the point of a data scientist in media is. Other areas use data science to drive their business cycle more efficiently. The putative driver what makes a good long-term relationship with the reader is hardly unique to data science and none of the rest of the interview to me expands on what the intersect of the discipline and the question might be.