🍎your Scholarly Digest 20th March, 2025

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Image Credits: Courtesy National Gallery of Art, Washington

Hi Scholar,

We’ve got a fairly long Letter this week. To quote French philosopher and mathematician, Blaise Pascal:

NEWS ANALYSIS

Penny for Your Thoughts, Reviewer 2?
- The Tatler

Technically this isn’t “news” in the traditional sense because the website in question - ResearchHub - has been around since about 2020. But it did come to our attention through a X/Twitter post that went live 2 days ago:

ResearchHub is a platform that promises to pay peer reviewers for their time by issuing them with ResearchCoins (a cryptocurrency token) and regularly updates a list of “grants” to incentivise review of preprints or manuscripts offering about 500 ResearchCoins per review. It’s not clear from the website why these articles specifically have been assigned grants. 

It’s unfortunately true that publishers do make enormous profits while researchers who do the work get nothing from them; ResearchHub is essentially positioning itself as a redistribution mechanism where researchers get to share in the profit. If you perused the Sunday Read this week on “Researching Like a Dog” then you may see a reason to question the fundamental assumption that ResearchHub’s mission rests on: that publishing scientific knowledge should generate enormous profit.

If we all agree that it should, then what ResearchHub is doing makes perfect sense.

If we suppose that the profit-driven nature of scientific publishing is actually a problem, then it’s possible ResearchHub will only result in publishing practices that are, at best, what we have right now, and at worst, even less concerned with integrity.

If you’re interested in doing some more reading on the intersection between cryptocurrency and scientific research, this piece is a good place to start. 

BRAIN FOOD

The Science of Envy

In this essay, Professor Richard Nelson explores what makes physics unique as a discipline. He questions why some research fields, in their attempts to emulate physics through quantification and mathematical analysis, often struggle to achieve the same precision and clarity in understanding their subjects.

Different fields of inquiry require different modes of investigation. While this may seem obvious, there has been a persistent tendency across disciplines to look to physics as the gold standard of science: the model that all fields should aspire to emulate. This stems from physics’ ability to formulate precise, law-like relationships that allow for mathematical analysis and highly accurate predictions. The pursuit of similarly precise, predictable answers has led disciplines ranging from biology to economics to education to adopt physics-like methods, often prioritizing mathematical modeling and quantification.

However, this approach is problematic because many of these disciplines deal with complex, variable, and evolving phenomena where strict predictability is difficult, if not impossible. We may understand the causes of diseases or the mechanisms behind climate change, but our ability to predict specific outcomes with precision remains limited. Unlike physics, which studies tightly constrained systems where universal mathematical laws can be applied, many sciences work with “fuzzy” or context-dependent phenomena where such law-like relationships simply do not exist.

This does not mean these sciences are any less rigorous or valuable. Rather, different disciplines require different forms of representation: qualitative data, narrative explanations, pictorial models, and descriptive analysis all play essential roles. For instance, Charles Darwin’s theory of evolution is largely conveyed through verbal and pictorial representation rather than mathematical formulas.

The objective of all research, therefore, is not necessarily to discover universal laws as physics does; expecting this from all sciences sets them up for failure.

Even the way research programs themselves are assessed has increasingly mirrored the physics model, emphasizing quantification and predictive accuracy over other valid forms of knowledge. Our reliance on the impact factor as a measurement of article quality is another example of the over-reliance on quantified metrics in modern research. This approach requires reconsideration. Both researchers and policymakers must recognize that different sciences operate under different epistemic constraints and adjust their expectations accordingly. Not all scientific inquiry can, or should, be evaluated through the lens of physics.

RESOURCE

How Should One Read?
- The Critic

Virginia Woolf’s essay ‘How Should One Read a Book?’* starts with a declaration: that it is an interrogation, not a definitive answer. She writes that while an answer on the ‘right’ way to read might be possible, it’s likely misguided, as what works for one reader might not for another. Accordingly, the only advice one can give another about reading is:

It is only after recognizing the importance of ‘independence’ in reading that the individual might indulge in taking onboard ideas and suggestions for how they could read. And it is in this vein that Woolf offers a few thoughts on how one might read:

1. Reception first: focus on what the text is offering in the beginning, instead of expecting that it meets our demands. Do not come with preconceptions when you read as it prevents you from ‘getting the fullest possible value from what you read’. It is best ‘if you open your mind as widely as possible’. This will allow you to see the text from the author’s perspective: what the author is trying to communicate and present.

2. Read different texts in different ways with different aims.

3. Direct understanding of what the author is saying is only half the process of reading: it must be completed by judging and comparing texts. Reading, therefore, requires both receiving impressions and critiquing them. In this process of actively and critically interpreting a text: ‘we are no longer friends of the writer’, as we are in the beginning, ‘but his judges.’

4. The second part of the reading process is one which involves slow digestion. “Wait for the dust of reading to settle; for the conflict and the questioning to die down.” To form our own analyses of a text as a whole we need to create some distance between it and us. This is because we do not always grasp the full weight of a text while reading it; understanding often arrives later, unexpectedly: “Then suddenly without our willing it…. the text will return, but differently.”

5. ‘Learning through feeling’ rather than only relying on external interpretations and established readings. Approach texts with curiosity and an openness to discovering its meanings given your specific context.

The process of reading is an intellectual and imaginative act, not a mechanical process of absorbing information. It is both an act of surrender (to the text) and an act of independence (in forming one’s judgement). How we read is ultimately a question of thought, perception, and imagination.

*While her essay is titled, ‘How Should One Read Book’, there is no reason why her thoughts cannot be applied to the reading of any text which is not just a book.

If you’ve stumbled across a resource that’s been super helpful to you as a scholar, reply to this email and send it to us so we can share it with 3000+ scholars. We don’t believe in gatekeeping around here. 

OPPORTUNITIES

Funded PhDs, Postdocs and Academic Job Openings

• PhD, Postdoctoral, and Academic Positions @ Masaryk University, Czech Republic: click here

• PhD and Postdoctoral Positions @ Karolinska Institute, Sweden: click here for PhD Positions; click here for Postdoctoral Positions 

• PhD Positions @ Coventry University, United Kingdom: click here

• Research and Scientific Positions @ Leibniz University: click here

KEEPING IT REAL

You’re a better writer than AI (yes, You)

Video essays on YouTube tend to be nothing more than written essays simply read aloud to you. What we have here, however, is a work of art which uses video as a rich medium to build, maintain and illustrate the main point of their argument: 

As a piece of work in itself, it’s worth your time for 2 reasons:

1. It is a compelling, well-constructed critique of the phenomena of AI writing. Whether you are positively or negatively disposed to AI-as-writer it’ll make you think. 

2. It’s a great example of how to not only introduce an argument, but to incrementally build it throughout a piece of work.  

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