Week 2 is much less eventful comparing to week 1. It is likely a more truthful depiction of a typical week in the coming 3 years.
Measure and Routine Practices
Why we do what we do the way we do it?
Several constellations lined up to trigger this train of thought. I recently finished listening to Desperate Remedies: Psychiatry’s Turbulent Quest to Cure Mental Illness by British Sociologist Andrew Scull, whilst starting James Vincent’s first book, Beyond Measure: The Hidden History of Measurement. A challenge faced by psychiatrists in the 1970s as they put together DSM III was not a new one. It is a problem of establishing a reliable measure. As the French tried to establish the metre, the Chinese Emperors defining the tunes, and the Egyptians keeping time – to be reliable in what they measure. A proper measurement often relied on a naturally occurring (hence valid) phenomenon to establish it’s reliability, which is relatively easy to do for some of the things, etc. how sundials and waterclocks were used to track time. Mother nature became their guarantor. For other constructs, like friendship, happiness, rights and responsibility, we are less capable to do so, or at least haven’t found a way to reliably doing so yet. How we measure things tell us a lot about our understanding (or the lack) of the phenomenon.

The same applies to the research in health equity. What is being recorded and how they were recorded matters. And these directly influence what is available in our routine administrative data. For example, indicating the poor uptake of psychological therapy in an ethnically diverse catchment area do not simply mean that there is a strong stigma, but perhaps more entrenched distrust in the system, lack of support for people to access services etc. Moreover, alternative support provided by community members, cultural practices and are merely not recorded, and discounted from routine records. From this snap shot understanding of the “evidence” for poor therapy uptake, what could be a proper policy in response? It is impossible to tell just by data, and this is because of how we decided to frame and measure access.
It begs the question, who decides what to measure and how? Under this veil of evidence-based policy making, which people groups are routinely under-represented? I reflected on some of these question in my blog earlier this week (Reflecting on Ethnicity in Research – Challenging the Default). These are the questions I will keep in mind and keep interrogating myself as I carry on with my PhD research.
Learning Python
Starting to experience once again the joy and frustration of learning a new program. Successfully installed relevant packages – celebrates! Failed to reliably call my virtual environment – felt defeated… I have been forking people’s repos on Github but struggling to understand the process… Would appreciate any tips on picking up Python!
Week 2. Solid 6.5/10.