'Churn Becomes the More Effective Strategy'?

There's been some problem with Blogger last week, and it seems to have lost the post I did on whether to deluge funders with applications when success rates plummet. Luckily, I kept a draft, and have pasted it below. Apologies if you've seen this already.
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An interesting piece by former Times Higher journalist Zoe Corbyn writing in Nature. She reports on a mathematical analysis that suggests that, when success rates for grant applications fall below 15%, applicants should just deluge the funders rather than try to hone their proposals. It's quantity that counts.

You can imagine the funders reacting with horror to this suggestion. All their recent policy diktats have been aimed at discouraging just this kind of behaviour. 'Demand management', to give it its newspeak label, is the policy du jour with the Research Councils, who are seeking to stem the flow of applications and thereby bolster plummeting success rates.

However, the research seems to suggest that more is better. The analysis was undertaken by Paul Roebber, an atmospheric scientist at the University of Wisconsin-Milwaukee, together with meteorologist David Schultz from the University of Manchester. It used 'game theory' to model the funding success of two hypothetical groups of 500 scientists whose proposals had the same range in quality but who had different strategies for submitting applications.

And this, I think, is the weakness of the analysis. It's all a bit too...theoretical. Whilst they tried to factor in the idosyncracies of the reviewers (identified as 'correct', 'selfish' or 'harried'), they don't seem to factor in the patchwork of issues, politics, funder priorities and personalities that affect the peer review panels. One factor that doesn't seem to have been included is the irritation of the panelists at seeing repeat submissions - even if the funder allows for resubmissions. Whilst interesting, I think we need to see beyond the theoretical mathematics and develop a more nuanced understanding of what works - and what doesn't - when success rates crash.