My first question in viewing the network of who chose which pieces is: How does the five most-selected list in our section compare to the other section of this course? I predict Beethoven’s Fifth Symphony, our section’s most picked item, is also high on their list. It appears 11 out of 18 people included it in our section, although I anticipated at least 75% of the class would have chosen Beethoven’s Fifth.

I also notice no one in our section chose “Kinds of Flowers.” This is the only item excluded from the original list. Otherwise the least selected item is the men’s house song; Helen-Marie is the only person choosing it.

Observing that my list includes five of the ten most-selected items in the class, I wonder what the class average of items in the ten most-selected list is. I would also be interested in seeing a graphic of the proportions of geographic representations in our selections. Regarding the modular graphics depicting clusters of similar triads I would also like to see a relationship of dissimilarities between triads.

My modular community includes Inhee Kim and Lesley Hemsworth. Inhee and I share five selections:

• “Tchakrulo”
• “Melancholy Blues” by Louis Armstrong and his Hot Seven
• Bach’s Well-Tempered Clavier
• Beethoven’s Fifth Symphony
• the Peruvian wedding song

Lesley and I also share five:

• “Tchakrulo”
• “Melancholy Blues” by Louis Armstrong and his Hot Seven
• “Izlel je Delyo Hagdutin” performed by Valya Balkanska
• the Peruvian wedding song
• “Flowing Streams” performed by Kuan P’ing-hu

Lesley and Inhee share four:

• Bach’s Brandenburg Concerto
• “Tchakrulo”
• “Melancholy Blues” by Louis Armstrong and his Hot Seven
• the Peruvian wedding song

Our module shares three:
• “Tchakrulo”
• “Melancholy Blues” by Louis Armstrong and his Hot Seven
• the Peruvian wedding song

I would be interested to know what the average number of shared selections is in each triad as well as the average number of shared songs between each diode in the course. I would also be interested to know the highest and lowest numbers of shared selections between all diodes and all possible triads in our section.

I find my module fascinating and illustrative because whereas my method for selection—diversity of culture, historical significance, geography, composers, artists, composition, and instrumentation—was in concert with Lesley’s curation rubric, it was very different from Inhee’s classical-driven list. As Lesley writes, “my personal curated list also tried to capture voices from a variety of time periods and a variety of cultures” and “to use tracks that had recordings of both female and male voices.” And as Inhee writes, “Many of the songs are very European focused, there’s very little diversity in the pieces.”

70% of Inhee’s list is classical; Inhee and I overlap on two of these items and Inhee and Lesley overlap on one of the classical selections. However all three of us overlap in full on the remaining 30% of non-classical music in Inhee’s list. Lesley and I both sought to create a diverse list. She and I ended up with an equal balance of overlapping and non-overlapping content. And despite our different approaches the amount of overlap between Inhee and I is proportionally the same as the amount of overlap between Lesley and I: 50%.

This single example is insufficient to form a functional working theory. However, because of this experience I wonder if this outcome is an unlikely exception or if diversity as an operational selection methodology statistically may be less significant than it seems.