joseph lam

Contemplating Originality in Public Health Theories & Frameworks

We are making great progress in our scoping review of frameworks describing health inequalities in observational public health research (protocol). We shared some of our early results with UCL Institute of Child Health Implementation Science Special Interest Group (SIG) last week, and an interesting question came up: what makes a theory or conceptual framework “new”?

It sounds like an obvious question. Most of the time, what we call “new” is really an adaptation — a shift, an extension, a remix of existing framework. We might add or remove an extra domain, a new component, a contextual layer specific to a certain analytical context. For instance, in public health we’ve seen countless expansions of existing frameworks to include social determinants of health (SDoH). These extensions are not necessarily understood as “new models,” but are variations — important and sometimes transformative, yet still anchored in the same conceptual roots. When does adaptation tip into originality? When does a reconfiguration become a new theory rather than a new setting for an old idea? And most importantly, why does it matter?

What tipped my thinking further was this LinkedIn post (Yes! – The new academic Twitter! ) by Dr Erica Thompson, as I quote:

Structural responsibility for model ownership, evaluation/validation and ongoing model maintenance and model risk management in large organisations/systems seems to me to be an increasingly urgent area to address…

Originality becomes important important – as it implies some level of ownership, but mostly ongoing responsibility of model (theoretical) evaluation, maintenance and validation. On the flip side, as an academic community, one could argue that once a piece of information/knowledge/idea is shared, it is then the shared responsibility of all who engages in the space to maintain or refute. Probably not too similar to the replication crisis – where there is a spike of p=.05 effects – I could also expect an iceberg of theories/models/frameworks that fail to achieve their purpose. (but what are their purposes? This very nice paper highlighted 7 of them!)

an AI-generated image using prompt: "Originality of the idea of being original" — an AI-generated image using prompt: “Originality of the idea of being original”

Back to the notion of what makes a model/framework “new” – Perhaps the answer lies not in the number of components added, but in the idea that underlies the model.

Take the SDoH framework from the WHO — a conceptual umbrella so broad that nearly any factor affecting health can be tucked underneath. It’s undeniably powerful, but also absorbent. Compare that to Andersen’s Behavioural Model of Health Services Use, which focuses on access: predisposing, enabling, and need factors shaping health service utilisation. Both speak to inequities, but they come from different conceptual spaces.

Then contrast those with Link and Phelan’s Fundamental Cause Theory — a framework born from a different philosophical stance altogether, one that resists being easily blended into SDoH. It argues that social conditions are not just one set of determinants among many; they are the persistent, structural roots that reproduce health inequalities even when mechanisms change.

In this light, the dominance of SDoH in public health science can have a kind of blender effect — pulling diverse frameworks into its orbit and smoothing over the conceptual distinctions that once made them powerful.

Meanwhile, we see a pendulum effect: theory and empirical research swinging apart. On one end, population health frameworks focus on structures and systems; on the other, individual-level behaviour models persist, often divorced from the macro contexts they operate within. Bringing these worlds together — harmonising the individual and the structural — is both intellectually challenging and practically necessary for meaningful intervention evaluation. However, there is this mismatch of spatial and temporal resolution of the effects that are operating at and across these levels. (hmm feels like a bigger idea is brewing…)

And yet, theory is not only a scaffold for model-building. As others in the discussion pointed out, theory should not be reduced to a checklist or a legitimacy badge. Too often, there’s a quiet academic anxiety: if we say we used the SDoH model, have we ticked the equity box? Implementation scientists know this trap well. Theories can clarify, but they can also constrain. We want them to guide, not to rubber-stamp. A truly new theory, perhaps, is one that opens up new lines of enquiry rather than closes them off.

So maybe “newness” isn’t about novelty for its own sake. It’s about conceptual movement: when the underlying logic shifts, when the philosophical footing changes, when we begin to ask different kinds of questions — not just add more boxes to the framework.

It is Finished.

The PhD rewires you… now I’m rewiring back. The last lesson of the PhD isn’t in the thesis. It’s learning how to stop mistaking endurance for balance.

It is finished. Two months ago today, exactly three years from when I first stumbled into this PhD life, as the clock struck midnight, I had fully drafted my thesis and booked my viva for two months later. Last night, I hit submit.

The only thing left on my PhD agenda now is to lie down like a salted fish and do nothing. (Yes, a nod to Chow’s immortal line: 「做人如果冇夢想，同條鹹魚有乜嘢分別呀？」— “If a person has no dreams, what’s the difference from a salted fish?”). Well, my dream at this point is to nap, so I guess I’ve come full circle.

Amazing art piece we bought in Lisbon – Fish drawn on broken tiles

PhD changes you (arguably – without consent…)

Doing a PhD is a huge undertaking. You think you’re just signing up for a degree, a structured thing with deadlines and milestones. But somewhere along the way it slips under your skin and rewires you. You start to realise it’s not just about producing a thesis — it’s about quietly reshaping how you think, how you spend your time, how you relate to others.

There are the obvious things: long hours, early mornings that bleed into late nights, bending time around deadlines like you’re running your own private Olympics. Dreams about work — not the metaphorical kind, but actual dreams where datasets, arguments, and half-written paragraphs chase you around.

I did try to protect myself. Weekends were sacred — my one immovable boundary. But the weekdays? They became a kind of over-compensation marathon. “If I keep weekends safe, I should pay it back by working even harder midweek.” And so I did. For the last year especially, that rhythm hardened: fewer dinners with friends, more nights staring at a half-eaten meal with my laptop still open, declining church commitments, community projects quietly pushed aside.

And yet, people who know me would probably describe me as a bit of an octopus — always dipping my tentacles into multiple things at once. Even during the PhD, that was my counter-measure: to resist being swallowed whole by the project, or by the endless temptation to improve methodologies on an upward-to-infinity scale. It was my way of clinging to variety, even if just at the edges.

At the end of the day, however, these are futile attempts to move an immovable load of work. All these cost sneaks up on you. No energy left to develop hobbies. No mental space to nurture relationships properly. No margin for anything that didn’t have the word “PhD” stamped on it. Life became PhD-centred, and everything else rotated around it like satellites around a heavy, slightly cranky planet.

Once the dust settled, the obvious question came knocking: is this how I want to live?

The last lesson

The final lesson of the PhD isn’t in the thesis. To me, it’s this: how to unlearn those patterns. How to stop mistaking endurance for balance. I’ve trained myself to push through – (to a point it becomes more enjoyable to just stay) — to add just one more paragraph, one more figure, one more revision. That survival mode worked for the PhD, but it’s a terrible blueprint for life. Productivity becomes its own trap: there’s always another article to read, another method to refine, another dataset to clean. The horizon keeps moving, and so do you, until you realise you’ve forgotten how to stop.

So the work now is almost the opposite: learning the discipline of switching off. Letting “good enough” actually be good enough. Accepting that leaving something unfinished until tomorrow doesn’t mean failure; it means you still get to have a tomorrow. Funnily enough, most of my codes do run much better the next day – once I had a cleared out mind to disentangle what kind of crap I scrambled together the night before.

My attempt to self-correct include:

Leave the office no later than 6:30pm.
Work from home a bit more (countering my tendency to loiter at the desk just because I can).
Say “yes” to new things outside of work. For example: training for a half-marathon. Current progress: minimal. (Help me out, runners of the world).

Onwards

I’ll save the spiel about “thesis format vs publication” for another time. For now, I just want to say I am eternally grateful to my supervisors, family, and friends for putting up with PhD-ing Jo. The PhD has taught me to get better at work. Now I need to continue to get better at life. The bettering doesn’t stop here. Here’s to a fuller, more balanced, more experienced life ahead.

The Elevator Problem

Ever frustrated about waiting for elevators and thinking there must be a better arrangement of default positions to minimise waiting time? Here’s an app I wrote you can try out! I wrote this with UCL Institute of Child Health in mind – so a 5-storey high building. Use the website for best experience.

You can customise:

number of elevators
elevator speed
door operation time
distribution of destinations, and call volume for:
morning-peak;
evening-peak; and,
non-peak hours

https://ichelevatorsimulation.streamlit.app?embed=true

With my simulations, the best configuration with default setting + elevator speed = 4.0, door operation time = 0.2 minute per stop:

Morning-Peak: with avg. wait of 0.54 minutes.
1 lift on ground floor
1 lift on 3rd floor

Evening-Peak: with avg. wait of 0.24 minutes.
1 lift on ground floor
1 lift on 4th floor
(Assuming half the calls for elevator per hour than morning peak)

Non-Peak: with avg. wait of 0.14 minutes.
1 lift on 2nd floor
1 lift on 3rd floor
(Assuming even fewer calls per hour)

Of course – I still need to update my assumptions on number of calls, elevator speed, and distribution of journeys. And there are quite a few other things I did not consider in this simulation, such as multiple stops.

I think a model like this reveals insight I don’t directly think of, such as, when elevator speed is fast enough, it does not really matter what configuration of default is set; or, when call load is really high, the small amount of operation time add up exponentially.

Nerdiness and jokes aside, I suppose this would be a good exercise/tool to communicate research findings to the public – but creating these interactive models with immediate feedback – to justify decision-making, resource distribution, and the many different stakeholders & things one need to balance.

It has been a fun little practice!

Evolving Language in Healthcare: Empowering Patients or Consumers?

Language around healthcare provision has been changing over the last few decades, with a stronger emphasis on people’s role and capacity in making their decisions on the care options they wish to receive. This shift is motivated by the intent to balance the power dynamics between healthcare professionals and people who receive care, with the hope that this would reduce risk of harm/iatrogenic events.

Studies such as this examined people’s different preferences (in a mental health service context), and they all come with a reason – even for the less popular term “Survivor”, as the term appears to be describing their struggle to get relevant help in the system. The term “service user” is being increasingly used, within and beyond healthcare, in other domains such as social care or learning disabilities, where the people’s care needs is not necessarily seen as an illness. There is no good recommendation on which term should be used across all circumstances in people-facing materials.

Let’s take a step back: What the language is hoping to achieve, is to safeguard the relationship between healthcare professionals and people who receive care, such that individuals’ health is maximised. Language is relational. The study above highlighted the same thing: communicate and find out for whom which term is best used, and build this carer-cared relationship with respect.

Respect
Photo by Cytonn Photography on Pexels.com

My biggest qualm with the term “service user” is based on exactly this: how the term (potentially) changes the patient-doctor relationship into a consumer-provider relationship. I think the consumer-provider relationship comes with 2 major flawed assumptions:

assumption 1: All problems could be fixed, it is only a matter of price.
This thinking embeds deeply in capitalism that there is always a better solution to the current problem, over-estimating the capabilities of human knowledge on medicine.

assumption 2: All service providers are incapable – there is always someone else who can provide better services – reliance on competition. This is the other end of removing power from healthcare professionals. This removal of respect to professionalism changes people’s attitudes to help-seeking. People now ask for personal recommendations “Which doctor do you know is the best?” – instead of believing in the standards of which the profession is established on. The push to physician associates rides the same tide of the removal of professional standards of medical professionals.

Help-seeking is now dependent on social capital; better service is now linked with cost; the spirit of national healthcare service where health is a basic right is challenged – being healthy becomes a commodity. Inequalities, along with a thriving private healthcare service, will be widened as a result. The lack of a trusting relationship, and move to a transactional relationship between healthcare professionals and people also mean that the end goal of health service provision is no longer focused on individual functioning with alleviated illnesses, but patient satisfaction, which with the false assumption of what level of health is possibly attainable (in certain timeframe), could be impossible to satisfy. This fuels derogatory attitudes towards healthcare professionals, nurses, healthcare assistants, and doctors. No wonder retention rates of hospital staff remains low.

The same phenomenon and patterns are clear in other domains like education, and with the fast development in the capabilities of large language models and artificial intelligence, expertise is becoming less and less valued. Existing potentially trusting relationships between professionals and people need to be reforged and reimagined – and it all has to start with listening and involving people with lived experience in the generation of knowledge and expertise.

Existing **trusting** relationships between professionals and people need to be reimagined
Photo by cottonbro studio on Pexels.com

Culture changes, attitudes changes, patient may be a term running out-of-date, and service user may be no longer in favour. Healthcare provision has to capture, value and reward the building of trusting relationships, and have a longer-term vision in investing in community building. This is bigger than healthcare planning, but on the relationship between the people and their government and policy makers. The people are watching.

The Value of a Child

“The Dog Who Went To Space” by Mila Punwar

I was honoured to have witnessed the unveiling of the inaugural ‘Children’s Plinth’ winning ceramic artwork ‘The Dog Who Went To Space’ at St Martin-in-the-fields last week. The artwork is part of the Mayor of London’s ‘Fourth Plinth Schools Award’ to put creative children centre stage as they paid homage to the Trafalgar Square’s historic Fourth Plinths.

Historically, women and children are often undercounted, deemed invisible, and their achievements not fully celebrated (see recent uproars on the Nobel Prize in Medicine). There are more statues of animals than statues of named women in London. Children are often discussed in a lens of potentials, what they can become, the next generation, and the future. But they are seldom appreciated as beings with intrinsic value, as valid and living contributors to knowledge generation, or valued members of society.

Who’s voice is heard? Who’s opinions are valued? Who is answering and making judgements to these questions? I observe a dominance of (a false sense of) a need for demonstrating entitlement. One has to earn their spot to be in the “room where it happens”. Under a façade of meritocracy, this need to show “added value” structures societal resource allocation and social policies. For example, the same line of reasoning underline the debates on minimum age for voting, eligibility for state pensions, mean-tested welfare system, and provision of health service. The same old Greeco-Roman attitude of citizenship persists: One has to contribute to society in a certain way for one to be recognised as a rightful citizen, a valued being. Initiatives on expanding participation, public and patient involvement, and Equality, Diversity and Inclusion all serve to challenge this old view, and expand: Young people’s merits is their being. You are valued for their being. (extend/substitute young people with any protected characteristics, gender, sexual orientation etc.)

The same old Greeco-Roman attitude of citizenship persists
Photo by Hisham Zayadneh on Pexels.com

Academics and policymakers learn the keywords quickly – to give a voice to young people, and listen; but many young people still doesn’t feel that they have a voice, and their voices unheard. I want to highlight an amazing work led by Dr Lauren Herlitz and a group of young people who produced a podcast episode on their thoughts and experiencing interacting with primary care services. Lauren put the young people’s voices at the forefront, in a direct, raw form that does not filter out their anger and fear in their voices (listen to the podcast). These voices are now transformed into a different voice – as an academic paper, backed by the academic class. In my view, the academic class has the role and responsibility to amplify and project these voices: we are rooted in scientific methods, evidence and rigor, but has to transform and be (always) unsatisfied with the impact of our collective contributions.

The burden is now with us as adults, activists, researcher academic and policymakers. The public is engaged when relationships are built, when actions are seen, when voices are heard, when history and culture is respected. Investment in long-term planning of public engagement is crucial to inclusive and better research and policy-making practices.

I am deeply inspired by Mila Punwar and her ceramics artwork. Listen to Mila talk about her creations. Laika, the dog, was the first living creature to orbit the Earth. Laika died a few days into her mission, partly due to the process, but the crew never prepared for more than 7 days of food. Laika was bound to be sacrificed. Young people’s voices are here to be projected upwards, to the outerspace if need be. Their voices cannot die like Laika.

Who do we value?

Conference Thoughts & Reflections

It’s been a whopping 2.5 weeks of conferences, presentations, exploration and learning in September for me. Kicking off at the Royal Statistical Society International Conference (RSS) in early September (2 presentations), to a week at Institute of Health Metrics and Evaluation (IHME, University of Washington, Seattle) (2 invited lectures), followed by a week-long conferences and workshops at the International Population Data Linkage Network Conference (IPDLN) at Chicago (1 poster, 2 presentations). Lots of “firsts” this month, and this is a blog to organise my thoughts and experiences!

RSS – 4-5th September

Presenting at RSS, article will be out in November 2024 Edition of Significance!

My first ever RSS conference and I wish I had learned about it sooner! The conference is a great mix of statistical theory, methods and applied research, and an international representation with >700 attendees from academia, media, and people from government statistics. A flurry of exceptional talks and keynotes started with Tim Harford, reaffirming that it is key to reject the notion that “Stats can tell you anything” because it becomes synonymous to “Stats can tell you nothing” – undermining the confidence of the public (and sometimes our own!) towards statistics. Pivotal to my theoretical thinking & development is Erica Thompson’s talk and book “Escape from Model Land”, encapsulating the need for modellers to make use of their expert knowledge in their interpretation of statistical models, and take accountability, instead of pretending there is strong objectivity in research. My talk as the winner of the RSS Early Career Writing Competition was well received, with several follow-up chats and emails. It’s another imposter syndrome moment – who am I to give a talk to these brilliant and renowned statisticians!? People I met at the conference were kind and open to conversations, and I felt very welcomed from start to finish. Statisticians are a special group of people!

IHME – Seattle, University of Washington

“Stay open to new data and be prepared to keep freshening up your knowledge”
Hans Rosling, IHME

First few steps into the building and was greeted with Hans Rosling’s quote “Stay open to new data and be prepared to keep freshening up your knowledge.” Another humbling experience giving a 1-hour seminar, titled: The Road to Racial Health Equity Starts with Data Equity, Transparency and Clarity, with a strong 80+ audience online, and 10 in the room. Again I fell into my typical long-winded mode and couldn’t finish all of my slides, but it is re-assuring knowing that what I have been working on in the last 2 years can be meaningful and impactful to how researchers approaches racial and ethnic health inequalities. The dynamics at IHME is always upbeat with biweekly goal settings and meetings. As a PhD student, my research is sometimes a bit isolated from the rest of the group. It is quite nice to re-immerse in a team-based research process for a bit! I was ecstatic to visit the paediatric residents on the Health Equity Track at Seattle Children Hospital, had great conversations about quantitative and qualitative approaches to improving health equity. Also inspired my initiative to share our stories!

Conversation with Paediatrics Residents on the Health Equity Track, Seattle Children Hospital

IPDLN 2024, Chicago

Chicago – it’s been over a decade since I last visited and it is ever-stunning. IPDLN Edinburgh was my first conference as part of my PhD, I was 3 months in, and was properly amazed by the breadth and depth of topics discussed then. I hoped I could one day have an opinion, have something valuable to add to this community – and I did! With new friends I met at IHME, I was invited to help out at a pre-conference workshop, presented a poster with international collaborators (and meeting some for the first time in person!), and gave 2 different presentations. I am so glad to have met people across UK, US, AUS, NZ and beyond, working in inter-related areas on record linkage. Incredible workshop on data visualisation by Rowena from Wales, and again featuring Hans Rosling on his BBC visualisation on life expectancy! His legacy is felt deeply in this trip, and every time we hear from colleagues working with Swedish data! I look forward to keep being a part of this evolving community!

L to R: Peter Christen, Rainer Schnell, Joseph Lam;
Presenting work led by Sumayya Ziyad who cannot make it to Chicago this time.

Having Fun

I have yet to talk about the entertainment and cultural exchange bit 🙂 Seattle and Chicago has treated me well, from Space Needle to the Bean, from underground walk to architectural boat trip, from jazz club to blues bar, from Burke Museum to Second City, from Seahawks to the Cubs! This will be undoubtedly a fond memory when I finish my PhD – final stretch, now back to work!

The fault in our names – Share your story

I had the opportunity to visit the Burke Museum of Natural History and Culture at Seattle, Washington. I was greeted by a pair of (portraited) open arms of Chief Si’ahl, the most famous dxʷdəwʔabš chief, whose name was anglicised to – as we now know – Seattle.

Picture of the description text for Chief Si’ahl’s portrait.

I can’t help but think about how Chief Si’ahl’s name would most likely be represented in many different ways in a modern data system. For example, Si’ahl already is a compromised ASC-II representation of his name in his original Lushootseed writing, where non-alphabetical characters are simply not accepted. Even in the anglicised form, his name may be recorded quite differently at different places, namely “Sealth” or “Seattle”. This meant that linkage based on his name would be more difficult than others.

Burke Museum gave me another example of situations when people’s naming systems differ from the Western Forename-Surname structure, they are sometimes forced to conform. Chief Jonathan “Whonnock” (anglicised)’s name is structured as such.

You would be mistaken to think these questionable treatments of names is a thing of the past! I was updating my UCL profile recently, and UCL gave this lovely advice – no names containing punctuation, diacritics, special or non-Latin characters, or names that are too long.

This may be innocent and non-consequential for file names – but you won’t say for people’s names. What truly hurts about “being called names” is about being called names that one does not identify. We live in a culture that claim to respect diversity, but has yet to truly reflect on their practices, in terms of data system design. In terms of data linkage, where names are often used to help identify if multiple records belong to the same person, we have long-established inequalities by racial-ethnic groups – where people from White British groups are most well linked, represented, and included in research. I have written about the technical side of this argument in my own academic work – hopefully out soon (waiting for Arxiv…)!

The Fault in our Names – share your stories.

We need to tell our stories to drive change. I have started a page here to invite your submission to collective tell our story – how our names are misrepresented in data systems, and it’s direct impact on our lives. I hope this will create an archive of our stories, and bring them to light.

One day, our names, all names, will be treated with respect.

That’s Just Common Sense… Or is it?

Esther McVey, A.K.A Rushi Sunak’s “Common Sense” Minister, declared “war against backdoor politicisation” by suggesting a ban of “divisive” rainbow coloured lanyards among civil servants (which caught most of media attention), and a ban on all jobs dedicated to equality, diversity and inclusion (EDI). This probed my curiosity in what “common sense” really meant.

Here’s a quick summary from reading the Wikipedia page (perhaps GPTs would do a better job here but let’s keep this authentic!). Earlier (~BCE 350ish) Aristotelian definition of “Common Sense” focused on the five senses, how there must be a common way in which people (and creatures) perceive the world, tell apart constructs across modalities, for example “sweetness” from “white”. This understanding of “Common Sense” was mostly translated and updated after Enlightenment, in the late 18th Century, to mean a set of collective and conventional moral consciousness, sense or sentiment that doesn’t need reasoning (with Kant standing against the feeling bits). This philosophical line of representing “Common Sense” as an “universal moral law” has been adopted in Catholic and Christian apologetics, such as CS Lewis’ influential book “Mere Christianity”. Across the Pacific Ocean, ancient (~BCE 300ish) philosopher Mencius wrote (English translation) about a similar concept, that humanness is defined by their innate feelings of commiseration, shame, modesty and complaisance. These philosophies shaped our modern understanding of “Common Sense”: (1) very optimistic view of the human condition, (2) universality of this moral judgement that does not require reasoning or reflection, and (3) “Common Sense” is used to define humanness.

Here are a few quick arguments to the “Commonness” in “Common Sense”. *Assessment of the human condition is not relevant to this discussion so I will just say I do not hold the same optimistic view of human nature as Mencius. A low hanging counterargument to (2) is the shift of what’s deemed to be morally acceptable over time, context, society structure and locations. Killing animals for fun was “universally” accepted, until it’s not. Slavery was “universally” accepted, until it’s not. Given (3) is true, with (2) being relative to space and time, accordingly, what defines humanness (3) becomes relative. The key question, hence lies at who decides what is Commonly Good, and when it is no longer Commonly Good.

How did Esther McVey know rainbow coloured lanyards are “divisive” and are against “Common Sense”? By definition, there is no need of reasoning for Esther to explain her decision. On a personal level, I acknowledge (accept, but maybe not at endorse level) other modes of “knowing” that does not strictly rely on reasoning. For example, faiths, beliefs, trust, relationships, values can not always be meaningfully explained or metricised and quantified into degrees of reasoning. People are rightfully living by their beliefs, without the need of justifying how they have conceived their beliefs, with or without reasoning. I mean, I still can’t fully understand why people voted for Trump, but I am satisfied to not demand their votes to be reasoned before them be deemed valid, and I can co-exist with them in a democratic society. However, in the public sphere, this way of knowing without reasoning removes the transparency and justifiability of decision-making. Relying solely on this way of knowing re-mystifies politics back to the era of empire-theocracy. The politicians (decision-makers) are left with the opportunity to misuse their power of exceptionality. Reason is required for this reason. Fortunately, in a democratic system, there are still mechanisms to challenge this power – We’ll see when it happens (when’s general election?).

There are several foreseeable practical impact on public servants following Esther McVey’s announcement. This instrumentalised view of civil servants as a horde of machines with assumed neutrality might be preparing for large-scale AI takeover. Jokes aside, this un-reasoned power to put restrictions on people – humans – to express themselves will soon be shooting the already weak civil services in their own foot. There are two kinds of expressions that are being restricted – visible and invisible sense of identities (Back to Aristotelian!). Visible ones are like the example, carrying rainbow lanyards, but could be extended to, say, wearing a hijab, looking too Asian, does not drink, revealing ankles etc… When the expression of personal identity conflicts with what’s deemed to be “divisive” or “Common Sense”, it will always be the individuals’ humanness that are disrespected. Heck, “Esther” too is a name originated in Jewish/Christian traditions, should we move to use numbers to call civil servants during their duty hours (hello again, 1984)? Esther McVey’s attempt to promote inclusion in civil servant workforce serves as a recipe to undermine the exact thing she is trying to improve.

There are wider implications on identities that are invisible. Networks to support people from different religion or country of origin are now suppressed. Role models, peer support that were previously more accessible are now hidden. There is no easy way to identify other people who are similarly minded, who are happy to support, for mentorship, informal chats or discussions. This assumed “neutrality” then, again perpetuates a biased resource allocation system towards people with high capabilities (in terms of social capital etc….), and not potential. The already clunky “machine” Esther hoped to fix will keep on failing her expectations.

Would universities and higher education institutes follow suit? UKRI has made precedent in October 2023 by banning Research England EDI Expert Advisory Group (with independent investigation found no evidence of any breach). Will these bans extend to university staff who are technically publicly funded? I had a rainbow lanyard when I was at King’s College London, would they take those away too?

End with a whip of good news – in the latest news today, the lanyard ban does not appear in the actual guidelines. But it was never just about the rainbow lanyards. More is coming, and next time it might concern you, when your sense of individual and humanness is no longer respected, remember, it’s just “Common Sense”.

Temptation of Treating Science as Sovereignty

Science as Sovereignty, and the problem of this.

As Nietzsche shared his observation that “God is dead”, as we enter the (post)secular world, we seemingly departed from the need of revelation from supreme beings to ascertain the truth. However, Schmitt believed that political sovereignty remains (re)enchanted within the same theological framework, that modern national sovereignty is a reflection, or a derivative of Theo-sovereignty. In Chan’s book, he attempts to disenchant the Theo-political relationships in this atheistic age.

I cannot help but project the arguments & discussions in the book to my line of work: in health research and policy making, that Science is disguised to fill the gap of Theo-Sovereignty.

“Follow the science” – Not sure if anyone kept a count of how many times Boris Johnson and his crew repeated this phrase during the pandemic. They certainly walk their talk in at least 2 dimensions: party gate, and in policy making – slow & weak masking recommendations. Nevertheless, “follow the science” stirred up a lot of emotions and debates within the country – arm-chair epidemiologists, experts with polar opposite recommendations, fake news… Amongst the fury of opinions, the government framed science as the rightful king, filling the gap of Theo-sovereignty, as a voice of a justified and absolute authority.

A character of sovereignty is that it is above the law, that the sovereignty shapes the law, and the law serves the sovereignty. Social distancing, no home visits, masking… In this way “science” very well fits this description, determining “What” a society should do. Anything that strays away from “Science” deserves mockery and rejection, if not punishment and persecution.

All sounds good, only if science is as straight forward as a binary yes or no. In my view, science is an art of embracing and interrogating certainty. “It depends.” Science by nature cannot act as a sovereign power to rule a society. Hence what we observed in the UK (and many other places), is instead a colluded form of scientific sovereignty, a nationalism-biased evidence-picked aristocracy. This camouflage of nationalism in science is most evident in global (health) research. In the following paragraph, I wish to demonstrate how current approaches in defining “Who” should do research is colluded with nationalism (national sovereignty).

There is an increasingly popular narrative in academia that global research should be led by people from their corresponding country. Not to be mistaken, I am fully supportive of the said initiatives, providing funding and opportunities for scholarship to develop in the global south. I’ve gone out of my way to support researchers from overseas to learn research methods, statistical software, and job interview preparations.

However, this narrative is often reduced into a means of reattribution or reimbursement of the western colonial past. This emphasises on appearance and country of origin takes away from the researchers’ abilities, but more importantly, feeds into the increasingly prominent nationalist agenda: “it is their history, let them research it”, “it is their people, let them help them”, in short, “it is none of our business.” By no surprise, as the UK economy showed signs of slowing, the overseas aid (which is used to support a lot of global research) was immediately cut. This new “scientific” post-Theo-sovereignty is not gentle nor kind, but self-preserving, self-promoting and self-indulging.

Science does not happen in a vacuum. But it if does, we would easily reach the conclusion that researchers from the local countries are more likely to understand the context better, which makes research, communication, implementation and much more easier. The preferential development of scholars from the global south to solve local problems makes sense. These initiatives need not to be framed as promoting diversity, which could be twisted into a form of exclusivity, but simply as a better approach to produce better science.

Why hasn’t in the past global south scholarship taken a larger role in academic research and policy making? Why hasn’t they be considered suitable candidates? Our measurement of capability is always framed by a limited few. Did you graduate from Oxbridge? Did your parents work in academia? Did you publish from x y z journals? It is the university application season soon, have a look at the plethora of university league tables floundering themselves to their potential (mainly overseas) customers, aren’t we all playing by this game a greater authority designed, as they saw that this was good?

We are enchanted by the belief of certainty “Science” provides. This is no fault of the scientific approaches, but the collusion of other worldly powers (e.g., nationalism) that biases how progress is achieved and measured.

This is usually the place I offer a solution, some insight or revelation. But I really don’t have one. As a Christian, I believe in God’s provisions big and small. Researcher is a role equally as impactful to improving people’s lives as any. If God forbids, I shall do as much as I can as a researcher. My life and mission is bigger than this role. And I hope you find yours too.

This blog collects my early reflection from reading Dr Chan Ka Fu’s new book on political theology. I’m still very early on in this book, so I might have misrepresented Dr Chan, if so I apologise!

Open (Data) Science – Data Management is Key

Till the end of the day, it is rare for any finding to be considered completely irrefutable or beyond scrutiny.

Psychology degrees do give you superpowers. No, you can’t read minds, but you can shut your eyes and perform t-tests on SPSS. There is a point in time where I can rely on muscle memory alone to get the p-values popping up my screen. I can see how for simple analysis point and click solutions can be much preferable.

It wasn’t until my final year project that I started to really recognise the importance of transparent and replicable codes and research processes. I had to co-collect data along with my peers, we each collect half of the data. The data collection process is by no means easy: a collage of cognitive tests, long structured interviews etc. keeping the participants (mainly other undergraduate students) engaged and put effort was always a challenge.

All is well until I discovered my data collection partner was popping in random numbers in the dataset. “What is she doing?!” Shocked I was seeing this, but even more shocked when it turned out that she forgot to record age and gender in the interviews. Not having gender is less relevant, but age is a key variable we have to take into account for the distribution of IQ differs by age. I was quite disappointed as this meant that the data was compromised, and I couldn’t bring myself to really trust what the data could tell me – if basic demographics are made up, how credible can other information be?

I was annoyed, just like this cat.
Photo by Anna Shvets on Pexels.com

I think of this experience often as I read research papers that does not describe their data collection and analysis plan very well. In academia, more people are willing to share the codes they used for analysis. I believe the next step is to extend the transparency to data cleaning and management processes. When describing the process of data curation, it is easy to focus on describing the psychometric properties of the questions. However, I believe there are a lot of wisdom research groups can benefit from sharing their responses to more general questions like: How is the database managed? Were there any challenges to data management, how were they resolved? Studies and initaitives like PROSPER (PROfeSsionnal develoPmEnt for Research methodologists), helps consult and formulate future developments plans for research methodologists. I am happy to see how things are developing, and for methodologists to finally gain the limelight a bit more in research!

Till the end of the day, it is rare for any finding to be considered completely irrefutable or beyond scrutiny. The best we can do as researcher, in my opinion, is for future researchers to acknowledge as they read our findings, and say: “They were bound by the knowledge of their time, that was the most rigorous way they could have done it!”.

A key development goal from my PhD is the ability to develop codes and wrangling with data across Stata, R and Python. I am still learning the way to work across platforms that would make the most sense! Do share with me if you have any tips 🙂