The first round of the SpinTunes #3 song writing competition is over. Lo and behold, I made it to the next round! So needless to say I’m happy with the results. But equally important, the reviewers provided a lot of feedback. One is often inclined to retort when faced with criticism. Musicians even tend to reject praise if they feel misunderstood. I’m no exception. But this time around I actually agree with everything the judges wrote about my entry. (I Love the Dead – remember?) There wasn’t even the initial urge to provide my point of view, shed light on my original intentions. I will now go into the details, before I turn to a quick statistical analysis of the ratings in the last section of this post.
The incubation period for this song was rather long. At first, I was considering writing about the death metal band Death. It would have meant stretching the challenge and alienating anyone unfamiliar with the history of death metal (read: pretty much everyone). The only reminiscence of heavy metal in my actual entry is the adaptation of Megadeth’s “Killing Is My Business and Business Is Good”. I toyed with the idea of celebrating the death of a person who has lived fully and left nothing but happy marks on the lives others. Translating this idea into an actual song was a complete failure, though. I also considered writing about mortality statistics. There’s people who estimate the space needed for future graveyards and health insurances and so on. I’m somewhat familiar with the statistics behind that. But it would have taken weeks to turn this into a cohesive songs. So I returned to the notion of the happy grave digger. (Yes, Grave Digger is the name of a German metal band.) The working title was “Grave Digger’s Delight”. The music started with the chorus while I was playing an older idea I hadn’t used so far. Basically, I threw away the old idea except for the initial G-chord and the final change to D. I did add the intro melody, more on that soon. The verses are the good, old vi-IV-I-V, but with a ii thrown in for good measure. That’s not too original, but I was already running out of time. The lyrics started out with a word cloud of related terms. Plots With a View was a big inspiration when it came to the sincerity behind the mortician’s word. Here’s a person who’s dedicated to his job! I had wanted to include a couple of fancy funeral descriptions. But the music called for more concise lyrics. All that’s left from that idea is the line “I can give you silence – I can give you thunder”, which I kept to rhyme with “six feet under”. That one is indeed very plain, but I felt that the huge number of competitors called for a straight song that brings its message across during the first listen, preferably during the first 20 seconds. I think I succeeded in this respect. (This also a major reason why I changed the title to “I Love the Dead” – keeping it straight and plain.) The 2 minute minimum length gave me headaches. This made me keep, even repeat, the intro melody. I was tempted to use a fade out. But I always see this as a lack of ideas. So I used the working title for the ending. Given a few more days I might have come up with a more adequate closure. Even as I was filming the video, I felt the need to shorten the ending. I tried to spice up the arrangement with a bridge (post-chorus?) of varying length. I wasn’t completely sure about it during the recording process, but now I’m glad that the deadline forced me to keep it as it is. At one point I had a (programmed) drum track and some piano throughout the songs. To me it sounded as if they were littering the song rather than filling in lower frequencies. So I dropped them and just used a couple of nylon-stringed guitars (one hard right, one hard left), a steel-stringed guitar (center), a couple of shakers, lead vocals plus double-tracked vocals and harmony vocals in the chorus (slightly panned) and, of course, the last tambourine.
TL;DR – I appreciate the feedback and I resolve to start working on my next entry sooner.
Russ requests statistics. I happily obliged and performed a quick factor analysis using the ratings. What this method basically does is to create a multi-dimensional space in which the ratings are represented. There is one dimension for each judge, yielding a 9-dimensional space in the present case. If everybody judged the songs in a similar way, you would expect “good” songs to have rather high ratings on all dimensions the “bad” songs to receive low ratings. A line is fitted into this space to model this relationship. If all data point (i.e., songs) are close to that line in that space, the ratings are supposed to be uni-dimensionally. In other words, there appears to be one underlying scale of song quality that is reflected in the ratings. This would be at odds with the common assertion that judgments are purely subjective and differ from rater to rater. (It would also suggest that computing the sum score is somewhat justified and not just creating numeric artifacts void of meaning.)
Using Stata 10 to perform a factor analysis with a principal-component solution, I get the following factors:
. factor blue-popvote, pcf
(obs=37)
Factor analysis/correlation Number of obs = 37
Method: principal-component factors Retained factors = 2
Rotation: (unrotated) Number of params = 17
--------------------------------------------------------------------------
Factor | Eigenvalue Difference Proportion Cumulative
---------+----------------------------------------------------------------
Factor1 | 4.44494 3.29466 0.4939 0.4939
Factor2 | 1.15028 0.33597 0.1278 0.6217
Factor3 | 0.81431 0.08112 0.0905 0.7122
Factor4 | 0.73319 0.19850 0.0815 0.7936
Factor5 | 0.53468 0.05959 0.0594 0.8530
Factor6 | 0.47510 0.11760 0.0528 0.9058
Factor7 | 0.35750 0.05932 0.0397 0.9456
Factor8 | 0.29818 0.10635 0.0331 0.9787
Factor9 | 0.19183 . 0.0213 1.0000
--------------------------------------------------------------------------
LR test: independent vs. saturated: chi2(36) = 137.45 Prob>chi2 = 0.0000
Wait, what? Let’s just focus on one criteria for exploring the factor solution: Eigenvalues larger than 1. Here are two such factors, which suggests that the rating data represents two (independent) dimensions. (For those familiar with the method: I tried a few rotated solutions, but they yield similar results.) Now the first factor explains almost half of the variance at hand whereas the second factor has a much smaller Eigenvalue and subsequently explains only 1/8 of the variance in the data.
Let’s take a look at the so called factor loading to see how the two factor relate to the raters. Stata says:
Factor loadings (pattern matrix) and unique variances
---------------------------------------------
Variable | Factor1 Factor2 | Uniqueness
---------+--------------------+--------------
blue | 0.6128 -0.0039 | 0.6244
mike | 0.7690 -0.1880 | 0.3733
mitchell | 0.7188 0.1032 | 0.4727
glenn | 0.7428 -0.0309 | 0.4474
randy | 0.8830 0.0089 | 0.2202
kevin | 0.7768 0.1219 | 0.3817
david | 0.6764 0.3650 | 0.4092
ben | -0.0672 0.9439 | 0.1045
popvote | 0.7512 -0.2534 | 0.3714
---------------------------------------------
Without going into statistical details, let’s say that the loading indicate who strongly each rater is related with each factor. For example, Blue’s ratings have less to do with the overall factor than Mike’s ratings. Both rater’s show rather high loadings, though. Given the high loading of all raters (except one) indicate a high level of general agreement. The only exception is Ben, whose ratings have little to do with the first factor. (You could argue that he even gave reverse ratings, but the loading is quite small.) Instead, his ratings play a big role in the second factor (which is by definition statistically independent from the first one). There is some agreement with the remaining variance of David’s ratings and a negative relationship with the popular vote (if you use the somewhat common notion to interpret loadings that are larger than 0.2). So there appears to be some dissent regarding the ranking. But on the other hand, the “dominant” first factor suggests that the ratings reflect the same construct to a large degree. Whether that’s song writing skills, mastering of the challenge, or simply sympathy, is different question.
PS: I must admit that I haven’t listened to all entries, yet. It’s a lot of music and I’m struggling with a few technical connection glitches. Anyway, I liked what Jason Morris and Alex Carpenter did, although their music wasn’t that happy. Another entry that necessarily caught my attention was Wake at the Sunnyside by the one and only Gödz Pöödlz. Not only did they choose the same topic I used, they also came up with a beautiful pop song and plenty of original lyrical ideas. Good work!
