[quote skeptile]@Reedwarbler Your point has been made by the legendary Prof John Ionnadis, in his June paper forecasters.org/blog/2020/06/14/forecasting-for-covid-19-has-failed/
'Let’s be clear: even if millions of deaths did not happen this season, they may happen in the next wave, next season, or with some new virus in the future. A doomsday forecast may come handy to protect civilization, when and if calamity hits. However, even then, we have little evidence that aggressive measures which focus only on few dimensions of impact actually reduce death toll and do more good than harm. We need models which incorporate multicriteria objective functions. Isolating infectious impact, from all other health, economy and social impacts is dangerously narrow-minded. More importantly, with epidemics becoming easier to detect, opportunities for declaring global emergencies will escalate. Erroneous models can become powerful, recurrent disruptors of life on this planet. Civilization is threatened from epidemic incidentalomas.'[/quote]
Scary stuff. I hope that when the dust settles and the wider consequences become more clear, that all this is scrutinised and lessons genuinely are learned.
I think we do have a culture problem especially in the public sector of an inefficient relience of data for data's sake. It was a big driver in me leaving teaching. Those hours manipulating and analysing data into spreadsheets rarely ever told me things that I didn't instinctively know about my pupils, and were hours of time that I could never get back for my own children as they sat in childcare and I had to catch up on the actual core teaching admin at stupid o'clock in the evening or morning while my children slept.
There does need to be accountability in systems, but over the last 20 years and especially the past 10, we've gone too far. It's not just education, it cripples the NHS and just about every other sector.
Just because you can put it in a database, it doesn't mean that you're actually doing any good, and it all becomes less acountable as you can blame the "mutant algorithm" and "follow the science" and claim the lovely impartial nature of numbers and never get to the root of whose crap idea it was anyway!
Certainly for teaching, the cheapest way to improve retention of staff is to ditch much of the data and let people do their core job.