Although we are not quite at the position of releasing yet, Fauxpocalypse has advanced since last I wrote. The manuscript is almost finalised and more hidden obstacles of international tax have been – if not overcome – at least mapped.
In Good Order
With 13 stories in the collection, there are many possible combinations, some of which might be better than others.
Misha Burnett’s Fauxpocalypse! deals exclusively with the detection of Grijalva and events prior to the predicted impact, so is perfect to open the collection.
Dacia Wilkinson’s Full Moon starts nearly a year after the comet did not impact, giving a longer-term view of the social effects of near extinction, so is a natural fit to close the collection.
Leaving 11 stories to sort. So I began to compile a list of possible features:
- Description of the expected impact
I was not sure whether to group stories by location or not, especially as some stories move around. Therefore I chose to leave that for last
Because readers sometimes put a collection down and come back to it rather than reading it cover-to-cover, I started with the idea of putting the stories that explained more about the background to Fauxpocalypse at regular intervals so readers were less likely to need to go back to the start if they put it down for a while.
Next I decided to aim for a mix of moods. As well as avoiding the collection having a depressing section and a cheerful section, this gives the emotional resonance of stories a greater contrast.
As well as avoiding all the tragedies following each other, I did not want all the longest or shortest stories together. Otherwise, some readers might end up feeling rushed or bogged down in one area.
Rather than add another dimension, I decided to work out a potential order at this point rather than also sort by theme as well. So I hit the spreadsheets, and most of the stories neatly fitted into a place in the order. So I started looking at theme and location.
With most of the order decided it was clear where stories with a strong theme of, for example, religion were so I could make sure they were contrasted with more secular motifs.
The locations were already mixed so, in the end, the decision not to group by region was made for me.
Although I ended up not using one of my criteria to actively sort, I still feel it was useful to have. If more of the stories had dealt with very similar topics it would have been useful to see how different countries dealt with, say, rioting.
So, if I assemble another collection I will stay with:
- Identify any stories that strongly fit in a particular position, e.g. refer to events in another story
- Give each story four or five different values
- Pick two or three values and create a rough order which creates contrasts for each of them
- Use the remaining values to work out where stories which fit in more than one place fit best
A Taxing Event
After the effort of sorting all the stories I was less than pleased to discover last Thursday that my claim for gross royalties had been rejected by Amazon because it did not match IRS records. I was further displeased when I remembered it was Thanksgiving, so I could not contact either Amazon or the IRS until today.
The IRS were most helpful once Turkeyfest 2013 was finally over. Their records matched my records, so I had not accidentally made a false declaration. They suggested two possible reasons why Amazon might have thought they did not match:
- The IRS portal takes up to two weeks to make new records public. If Amazon queried the IRS within that time they would get a false report that my EIN did not exist
- My flat has a separate entrance, so the official postal address has a line before the street name and number. As the US standard is to put flat numbers on the line below the street address, and I do not have a different company name from my own, someone might have mistaken the first line of my business address for the name of my company and searched under that.
So, between spasms of ironic moustache twitching, I resubmitted my application to Amazon in the hope the same issue would not arise twice.
Focussing on the positive, if the problem was Amazon being too efficient it bodes well for a quick positive response.