This year, the Marsden Fund had 1152 Expressions of Interest... and 1032 of those weren't funded this year.
Assuming 3 researchers per unfunded application working 100 hours as a Step 1 Lecturer, that's $11,140k wasted.
If, instead, I assume the pre-fund work for each application is done by three researchers at a rate of $300 per hour, that's $92,880k wasted... more than the award money allocated!
Regardless of how you look at it, consider that those researchers *still* need to get their research funded from another source in order to continue as a researcher.
An award success rate of 10.4% means researchers will need to spend ~10 times that amount in order to get funded.
Even at the Step 1 Lecturer salary, when accounting for multiple applications, once again the wasted pre-research comes out as higher than the award money allocated... by over $24,000k.
We really need to stop this.
Pre-research is a waste of money.
Suppose, instead, that every researcher who applied were provided with an equal proportion of the $82,345k award money.
That's ~$21k per researcher, for an input effort of 100 hours.
Instead, 394 of the "best" get $209k each for a similar effort.
I'll guess at 20h work at L1 lecturer salary for 1032 applications, and 100h work at $200/h for 108 applications:
$2,450k round 1
$7,130k round 2
The alternative calculation comes in a little under what it is for 100h work for all researchers at L1 salary, but is similarly over the award money when success rate is accounted for.
[$9,580k wasted on pre-funded work for both rounds combined, about $2.8k per researcher]
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I've been looking at all these plots about vaccine effectiveness and hospitalisation, and thinking they're missing the exposure side of things... so I made another plot.
This plot shows how the vaccine reduces both hospitalisations *and* disease.
I've assumed here that the number of exposed unvaccinated people is the same as the number of unvaccinated people with COVID. I could bump that exposure number up a bit, but it wouldn't change the overall visualisation because the proportions of vaccinated people wouldn't change.
There's another niggle in that vaccination & cases are a dynamic event. MOH doesn't have vaccination status in their case demographic CSV file, so I use 2 wks ago as a fudge.
That shouldn't be too much of a problem anyway, because recent numbers dominate for exponential growth.
In short, they're great. My main comments are around needing more emphasis on participant control - making that implicit principle explicit.
"Researchers are expected to learn as well as gather data in research, to collaborate and to give back to the community (eg, through koha and sharing ideas)." [S 5.7] - a good principle to have; I think a minimal sharing protocol needs to be specified in ethics applications.