July 31, 2020

Reflect: Summer Week 9 and 10

Reflect: Summer Week 9 and 10

Hey there! Welcome to another reflection piece, which is part of a series of short articles I write to keep myself accountable in Summer 2020. Every one to two weeks, I share about the stuff I’ve done, several interesting ideas I’ve come across, and a personal reflection on what I’d like to do better in the coming weeks.

Stuff I did

I’ve probably just had the best two weeks of summer. I attended the IPSA-NUS Networks Analysis course conducted by Prof Adam Henry from the University of Arizona. This course was about two things: the how’s and why’s of networks analysis. I loved that there was a good balance of both: the theories behind why we study networks; and how we go about analysing them.

Every live zoom lecture has its own accompanying R lab (kinda like a practical) where I got to put theory to practice. I found these pre-recorded labs immensely helpful because Prof Henry walks us through his analytical workflow. He goes over the logic behind each line of code, taking the time to explain the parameters of the functions used and more. His verbal explanations made learning the R packages used a lot faster. He also anticipated questions- which was great because I found myself assured that my doubts will get answered along the way. During the lab sessions, I also got to work with real-life network datasets. He addressed any questions that arise the next day in class.

I’m glad I opted to complete the course for credit (even though it does not satisfy any of my graduation requirements). The required exams and research design report were so tough :’) but so useful in helping me consolidate my learning. In case you’re interested, here is a brief overview of the concepts we covered during the course.

  • The fundamentals of graph theory
  • Full network descriptives i.e network density, centrality, transitivity, clique analysis and segregation.
  • Quadratic Assignment Procedure (the t-test equivalent for network graphs)
  • Exponential random graph models (the logistic regression equivalent for network graphs)

Prof Henry has been doing research on networks since forever. In addition to teaching this course at NUS every summer, he also teaches at conferences and conducts regular workshops on the topic. His vast extent of knowledge is well complemented by his ability to break down complex ideas into digestible chunks that in no way undermines their complexity (not many profs are capable of such a feat). The hRU, his own R package for conducting networks analysis, will be added to the CRAN repository sometime within the coming year. That aside, Prof Henry is patient and has a pretty amusing sense of humour (he channels statistician/dad-jokes vibes, if that makes sense). Most importantly, he is willing to go out of his way to clarify any doubts his students might have. What a blessing to have been his student. A definite 11/10 for a prof!

Stuff I learned

What is intersectional analysis and how does it related to mitigating health inequities during a pandemic? We are aware that crises often track along the fault lines of society- hitting hardest the most vulnerable of communities.

Researchers  at Global Health 50/50 suggested an approach rooted in intersectional analysis “to question the assumed neutrality of policymaking” to target health inequities that have been made stark with the the pandemic.

Intersectionality, in the simplest of terms, it demands for us to resist the natural tendency to identify someone as a particular sex, a specific race, class, sexual orientation, religious affiliation, age, nationality, disability or other statuses. This is because these statuses intersect and combine in complex ways that influence a person’s lived experiences, and hence advantages and disadvantages a person has. Intersectionality demands for us to view others in totality, as complex intersections of their characteristics, or otherwise put, as ‘everything at once’.

Intersectional analysis rejects one-dimensional approaches to examining forms of oppression. Instead, it considers how characteristics such as gender, race, class, ability, and sexuality interconnect to form complex axes of discrimination and privilege. These identities impact an individual’s risk of ill health and access to appropriate treatment, and it is critical that global health policy is responsive to this.
Mireille Evagora-Campbell, Global Health 50/50

By studying how people from different socioeconomic backgrounds are affected by the pandemic, this approach can help us critically examine the ways in which oppression has been systemically been legitimised through existing health policies. That way, we can start dismantling the problematic structures before working our way towards a more inclusive system that accounts for the needs of all segments of the population.

Figuring, by Maria Popova (probably my favourite read this summer)

This book. Otherworldly. A wonderment. A gift to humanity. A book about the beauty of our universe revealed to us by the most masterful of scientists and artists. How science: astronomy, mathematics, chemistry, biology, and art: literature, poetry, brushstrokes, were never separate in the first place. A delightful read that is enthralling, calming, empowering all at once.

A good read for quieting existential thoughts before bedtime, because I realise how insignificant little troubles are in the grand scheme of things. Popova probably made it easier to do so- after all, how could you not feel inspired by the very essence of life when you’re reading about astronomists charting the skies, poets capturing the magic of love and companionship, scientist-artists whose works driven by the deepest parts of their souls and who defy all odds to seek the truth. I’d borrowed this book from the library but quickly bought a copy for myself.

By gods, this profound book has taught me that by sheer will, humans can move the earth. Maria Mitchell’s intellectual curiosity inspires me. Margaret Fuller’s strength moves me. Most of all, Popova’s words bewitch me. As a longtime fan of Popova’s Brain Pickings, I can’t believe it took me so long to pick up a copy of Figuring. And devour it slowly I will <3

What I can do better in Week 11 and 12

  • Work on a cheat sheet for Prof Henry’s hRU package. This will help the team with analysis once data collection is completed.
  • Rest and recharge for school. PleAsE.

That’s all for this fortnight. It’s been a hectic two weeks, after all. Thank you for reading <3

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