Week 2: Getting Real

Week 2 is a philosophical one. More reflection on how this world operates.

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.

Photo by Moose Photos on Pexels.com

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.

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Reflecting on Ethnicity in Research – Challenging The Default

Reflecting on how Ethnicity is researched in academia, challenging “defaults practices”

Listen to the blog here

From the latest release of admin-based ethnicity statistics (ONS), it was shown that, across several administrative data source, there are a significant proportion of people having reported to belong to more than 1 ethnic group.

Similar evidence of changing ethnic identification was demonstrated in Understanding Society @usociety youth survey in young people aged between 10-15.

Ethnicity is a dynamic historic-cultural construct, and for most people from ethnic minorities groups, it changes overtime. In research/policy-based evidence making, ethnic groups are often lumped together (#BAME…), assumed to be constant, and you can only pick 1. It bears the question, how come the default practice in research is to treat ethnicity as time-invariant?

You might notice that – Changing ethnic identity is very uncommon among people reported to belong to White British groups.

And rightfully so! At the time when the population is predominantly white British (or that people from other groups are mostly slaves or seen as objects), research is predominantly initiated by white British, it is reasonable that ways of research are agreed for and within white British.

I am not saying it is a bad thing to have a consistent ethnic identification! But this lived-experience of an invariable ethnicity by white British groups has dominated the knowledge generation process and structure. And this assumption, rightfully based on white British experience was then assumed to be an universal experience.

It became The Default.

I did not recognise the issues with The Default.

I thought it was a consensus, as it was widely replicated and taught to next generations of researchers. I still do the same in my own research: treating ethnicity as lump sum categories, do not change over time.

And perhaps this IS the manifestation of systemic #oppression/#racism. Paraphrasing Dr. Celestin Okoroji: @CellyRanks shared at @kcsamh #PartneringforChange event yesterday (21/6), we need to recognise the hegemonic knowledge and evidence generation mechanisms in this society, and challenge them. (See my thread to capture part of the talk here)

It became The Default.
(Photo by Pedro Figueras on Pexels.com)

The next question is: “how” – what can we do, if we think we should challenge the default – or at least suggest an alternative of how “reality” is conceived.
I have 2 thoughts – (please share yours with me too!)
1) Community-Centric Research
2) Improving Methods

(1) Community-Centric Research means to put local communities – people – at the heart of research. It is about valuing relationship building, and demonstrate impact valued by local people. It is one form of Public Patient* Involvement I suppose, but more. This should be embedded in how funding is planned and commissioned.

(2) Improving Methods
This is one goal of my PhD project (with @Klharron & @rob_aldridge), to improve research equity, to face the biases in “default practices”, more specifically in the practice of data linkage, interpretation and public health policy decision making.

This is new to me – and I am empowered to see so many pioneers on this path. Change can only come from a collective effort. Do share your thoughts and idea with me here or via email!

希望是本無所謂有,無所謂無的。 這正如地上的路;其實地上本沒有路,走的人多了,也便成了路。

魯迅先生 – 故鄉

There is no such thing as Hope, it’s just like the path. There was no path. The path is manifested when thousands of people walk through.

Mr Lu Xun – Hometown
Photo by Julia Volk on Pexels.com

(end)

Originally tweeted by Joseph Lam (@Jo_Lam_) on 22nd June 2022 as a Twitter Thread. Minor edits and expanded on points without character limits.

Week 1: The Beginning

First week of PhD, thoughts on Remote Start. Software Nightmare. and Academic Career Progression

“Welcome to UCL” – 10 online induction courses (no kidding!) but I doubt I’d remembered a lot from them. Possible true that it is to leave a gist, an impression of what the college values: fire safety, implicit bias, data security… All is well! Changing jobs are never simple, and doing this in a remote-working era makes it … a bit weird? But I presume it is something for all of us to get used to.

The plus side of everything going online is that, I get to attend A SWARM of online talks, seminars and groups. It does feel a bit overwhelming to start – my schedule is quickly populated with scheduled meetings and invitations, there are always this prominent speaker coming, that core training one cannot miss – can’t help but wonder – will I ever attain this wisdom to determine which talks are the truly good ones I should listen? Would be a thing to reflect perhaps a few weeks down the line..!

A Virtual Office (Unsplash)
Office. Photo by Laura Davidson on Unsplash

Software Nightmare

The excitement of starting at a new post was quickly overtaken by the frustration of – you guessed it – installing the relevant applications and softwares on my laptop! Numerous emails, calls and remote access sessions but still not able to get all I need. There must be more flexible ways for colleges to adapt to this fast-changing landscape of software development! Take Python as an example, the only version that is easily installable via college software centre is version 3.6.4, which failed to satisfy a lot of the dependencies of many recently developed softwares. Guess it is always this tug of war between data system safety & integrity vs freedom & flexibility…! Hope they all get sorted next week!

Imagining an Inclusive Academia

UCL provides a clear guidance on career progression – the Academic Career Framework (see below) – with a comprehensive list of things one is expected to achieve at UCL Grade 7 and above. This is something I have never heard of! It provides a substantive structure into what is needed to progress at UCL, in other words, things that are (currently) valued by the college.

4 Components of the Academic Career Framework (UCL)

It is said that contributions to all 4 categories is necessary to measure one’s achievement. I appreciate the attempt to provide clarity on progression, and I can see a wider potential of these frameworks to revolutionise academics’ roles in society – As Dr. Nadia Islam rightly put, a community-focused collaborative role needs to be more heavily emphasised in academic research. This would be a part of a change I would like to see, and contribute to in academia in near future!

I think this pretty much wraps up week 1 – excited to continue to embark on this journey, and hope that you will be adjourning with me 🙂