2015 Nebula Prediction: Indicators #6-#8

These indicators try to wrestle with the idea of critical and reader reception by charting how the Nebula nominees do on year-end lists. While these indicators are evolving as I put together my “Best of Lists”, these are some of our best measures of critical and reader response, which directly correlate to who wins the awards.

Right now, I’m using a variety of lists: the Locus Recommended Reading List (which has included the winner 13 out of the past 14 years, with The Quantum Rose being the lone exception), the Goodreads Best of the Year Vote (more populist, but they’ve at least listed the winner in the Top 20 4 years since they’ve been fully running, so that’s at least promising), and then a very lightly weighted version of my SFF Critics Meta-List. With a few years more data, I’ll split this into a “Hugo” list and a “Nebula” list, and we should have some neatly correlated data. Until then, one nice thing about my model is that it allows me to decrease the weights of Indicators I’m testing out. The Meta-List will probably only account for 2-3% of the total formula, with the Goodreads list at around 5% and the Locus at around 9%. I can’t calculate the weights until I go through all the indicators.

Indicator #6: Places on the Locus Recommended Reading List (92.86%)
Indicator #7: Places in the Goodreads Best of the Year Vote (100.00%)
Indicator #8: Places in the Top 10 on the Chaos Horizon SFF Critics Meta-List (100.00%)

Table 4: Critical/Reader Reception for 2015 Nebula Nominees
Table 4 Reception

There are separate Fantasy and SF Goodreads lists, hence the SF and F indicators. These are fairly bulky lists (the Locus is at least 40+, the Goodreads the same, etc.), so it isn’t too hard to place on one of them. If you don’t, that’s a real indicator that your book isn’t popular enough (or popular enough in the right places) to win a mainstream award. So these indicators more punish books that don’t make the lists than help those that do, if that makes any sense.

Results are as expected: Gannon and McDevitt suffer in these measures a great deal. Their books did not garner the same kind of broad critical/popular acclaim that other authors did. Cixin Liu missing the Goodreads vote might be surprising, but The Three-Body Problem came out very late in the year (November), and didn’t have time to pick up steam for a December vote. This is something to keep you eye on: did Liu come out too late in the year to pick up momentum for the Nebulas? If The Three-Body Problem ends up losing, I might add a “When did this come out?” Indicator for the 2016 Nebula model. Alternatively, these lists may have mismeasured Liu because of its late arrival, and then these lists would need to be weighted more lightly.

The good thing about the formula is that the more data we have, the more we can correct things. Either way Chaos wins!

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