Quantified time horizons: a criminal mind?

weeks_ahead_scan_blurred

Figure 1. Blurred scan of my “weeks ahead” page in a log book, with appointments per day for the next six weeks (L being Monday, Lunes in Spanish) .

According to Akerlund et al. (2016), in a recent publication in PNAS (Proceedings of the National Academy of Sciences), the decision to commit a crime depends on how one views time. Most criminals have very short time horizons, where the immediate benefits outweigh the possible costs of punishment. I would argue that most quantified selfers are the opposite, with inordinately long time horizons, both backwards in time and looking forwards.

Most of my recent blogs have dealt with the past, analysing life-logging photos, or other activities over the years. I thought that this time I could concentrate more on the future, analysing how much I prepare for it, based on my agendas.

To begin, I looked at my agendas from this year (2016). I save a page (page 3 in each log book), for a list of appointments over the next 6 weeks (Figure 1). I noticed that the number varied quite a bit, both from week to week and between books. So I made a spreadsheet for every week and for every log book and noted the number of days with at least one appointment. I started to see a pattern where “next week” is pretty full, but the appointments decrease quite rapidly in the following weeks. How much? Well for 2016 so far, on average 45% of the days were filled for the current week (which is not quite fair since many times that week is truncated, since I may start a log book in the middle of the week), 61% of the days had at least one appointment for next week, 42% days filled for “in two weeks”, 31% days filled for in three weeks, 21% for in four weeks, and 8% for in five weeks.

Next I wondered whether the trend was similar in previous years. So I went through the same process for all my notebooks, starting with notebook 5  which began in May 2010 (I didn’t have an agenda my first 4 log books). That data helped produce Figure 2, where we can see the percentage of days filled with at least one appointment in the coming weeks, for every year. In 2012, I had fewer appointments in general, probably since I spent a about six months preparing for an important exam/evaluation. The other years had similar values for the different weeks, and overall the average number of days with appointments was always higher “next week” and decreased quite linearly, more or less as described above for 2016.

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Figure 2. Summary of the percentage of days will with appointments in the coming weeks for all the log books in a given year (the data for the 5 months of 2016 are given in the text).

I also wondered whether I planned ahead more during certain months (Figure 3). You can see a dip in summer (especially July) and peaks in January, April, May and November. I ran the data through an ANOVA (using log book duration as a co-variable) and found significantly fewer appointments in weeks 3, 4 and 5 in July and significantly more appointments in those same weeks in April. So those are now officially my lazy and busy months. Probably there were no significant differences for “in 6 weeks” since there were so few entries.

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What does all this mean? Well, it looks like I have a pretty good idea about what’s going next week and in two weeks, which suggests I’m not too criminally minded. There is another point here too, however. I think that the average person who does not plan ahead is possibly closer to the “criminally shorter” time horizon, since they opt for the short term benefit of not planning and disregard any future benefits. Why spend time and effort planning things when you’d rather think of today? Yes, there is an immediate cost of planning, but it turns out to be low compared to the benefits down the line. But I guess you have to try it to find that out.

 

 

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