At first look, based on the last names of the few nodes (System Innovation, 2015) surrounding me such as Jiang, Chan, and Luk, I recognize these names to be Chinese last names. This allows me to assume that identity is one reason we chose our songs, as we can relate to it (New London Group, 1996). At closer look to see what song nodes form an edge to our names (System Innovation, 2015), Flowing Streams were a song choice we had in common. This song, in my eyes, have instruments and music flow that connect with the Chinese identity, drawing connections to New London Group’s (1996) idea that people find the language of music or sound more powerful when we can relate to it in experience or culture. However, just looking at last names to assume identity may not be accurate in today’s time. Family structures have changed to include adoption, foster families, remarriage, etc. People may keep their last names, but not necessarily “identify” with that culture or identity.
Interesting to note, is that Flowing Streams was a high pick song for many curators, with 16 of us choosing that song, demonstrating a 16 degree of connectivity (System Innovations, 2015). At first, this made me think that many of us were educators and we understand the need for bias free, cultural responsive diversity in education (Capacity Building Series, 2013). Of the many songs, only one was from a Chinese background. However, looking closer, I could not see diversity as a continued trend as there was less commonality in choosing songs like Crane’s Nest and Jaat Kahan Ho in which were the only Japanese and Indian songs. Thus, this assumption may seem biased based on my own experience and interpretation.
Looking deeper and stretching my node more, the four people closest to me were Graeme, Jackson, Whitney and Angela. Particularly Angela and I had similar pattern in algorithms (O’Neil, 2017) for those around us, causing me to believe that Angela and I are the factors that caused Jackson, Graeme and Whitney to be closer to us.
Jackson and I had 4 songs in common (Crane’s Nest, Flowing Streams, Senegal, The Fairie Ground). Whitney and I had 5 songs in common (Crane’s Nest, Flowing Streams, Jaat Kahan Ho, Senegal, First Movement). Angela and I had 6 songs in common (Senegal, String Quartet NO. 13, Jaat Kahan Ho, Flowing Streams, Night Chant, Gavotte en Rondeaux). Graeme and I had 6 songs in common (Crane’s Nest, String Quartet No. 13, Jaat Kahan Ho, Flowing Streams, The Fairie Ground, Senegal).
4, 5, 6.
Whitney and Angela had 4 songs in common (Senegal, Jaat Kahan Ho, Flowing Streams, Tchakrulo). Jackson and Angela had 5 songs in common (Pygmy Girls’ Initiation Song , Senegal, Kinds of Flowers, Rite of Spring, Flowing Streams). Graeme and Angela had 6 songs in common (Pygmy Girls’ Initiation Song, Senegal, String Quartet No. 13, Jaat Kahan Ho, Flowing Streams, Tchakrulo).
4, 5, 6.
This similarity in algorithm pattern of 4, 5, and 6 similarities in song choices, makes me feel that those are the patterns found for our surrounding area of nodes. Trying to find more connections between curator nodes and similarities in song choices, I found that 4 was a common number. Whitney and Jackson had 4 songs in common, Jackson and Graeme had 4 songs in common, Whitney and Angela had 4 songs in common, Jackson and I had 4 songs in common as well. This similarity in pattern (O’Neil, 2017) can also demonstrate the interconnectivity or algorithm that connects these four curator nodes (System Innovations, 2015) to be placed in the same vicinity.
However, based on this observation, I may be missing data or my assumed algorithm could be bias, as noted by O’Neil (2017). For example, looking only closely to those around me and the similarities around me, I might be missing if the same type of pattern can be observed for others in different areas of the nodes. I’m also only focused on the similarities, missing what was different between us in which is also valuable data to observe. Looking at number of similar choice may be bias, as the reason behind the choices are not accounted for. What if the reasons were significantly different? Where one is choosing based on identity, another based on unfamiliarity to the song type or based on how different it is to one’s identity? This does not paint a full picture of the full data of each curator and their reasoning behind their choice and these missing variables, in which can result in a false positive of relationships.
References:
Capacity Building Series. (2013). Culturally responsive pedagogy: Towards equity and inclusivity in Ontario schools. Retrieved from http://www.edu.gov.on.ca/eng/literacynumeracy/inspire/research/cbs_responsivepedagogy.pdf
O’Neil, C. (2017, July 16). How can we stop algorithms telling lies? The Observer. Retrieved from https://www.theguardian.com/technology/2017/jul/16/how-can-we-stop-algorithms-telling-lies
System Innovation. (2015, April 18). Graph theory overview [YouTube Video]. Retrieved from https://www.youtube.com/watch?v=82zlRaRUsaY&t=261s
System Innovation. (2015, April 19). Network connections [YouTube Video]. Retrieved from https://youtu.be/2iViaEAytxw
The New London Group. (1996). A pedagogy of multiliteracies: Designing social futures. (Links to an external site.) Harvard Educational Review 66(1), 60-92.