Gansheng Tan1 1Washington University in St. Louis, St. Louis, MO, USA (g.tan@wustl.edu)

Being honest

Writing is not my favorite activity. Yet, writing down my ideas has helped me uncover new ones. In case what I’ve written resonates with others or prompts them to reflectcon often results in more generalized philosophy. Over the years, I’ve explored many forms of writing: fiction, academic articles, diaries, and poems. In this post, I share my personal reflection on a question: What is the purpose of writing?

Writing in childhood and adolescence

In childhood, writing is something we’re taught in school. In adolescence, it becomes a tool for coping with confusion and emotional dissonance. Early adulthood is a period when we are little exposed to the world and societal norms. We encounter requirement and expectation that clash with our biological impulses, for example, being told to show etiquette at the dinner table.

During this period of rebellion and reflection, writing is a way to let go some of the grudge, anger, and confusion we have. In this time, we rarely write for approval or understanding. Instead, we tuck these words away, locking them up carefully to protect the more vulnerable parts of our identity.

Academic writing

As we grow older, writing takes on new roles. For artists, it may be a medium for emotional expression. For writers, it becomes a means of reflection, persuasion, or contribution. In academia, where I am in right now, writing is a screening tool, than a paid job. In fact, academic writing is rarely compensated directly. There are two main motivation for researchers to write.

First, in socioecologiucal context, writing bring back recognition, or adds to a record of contribution, which may lead to job opportunities, or future funding. Second, there is autrustic human nature to benefit the race as a whole. This impulse continously motivates us to share our research despite the process of writing often takes more time and effort than the research per se.

Outside academia, writing also serves broader social and epistemological functions. It can be a tool to share insight, persuade others, or contribute to a collective knowledge system. Being read is necessary for achieving any of these purpose.

Writing for being read

At the surface level, writing is usually defined as communication. Communication presupposes a receiver. So it seems natural to say: writing exists to be read. If a piece of writing is never read, not even by its author, what is reason for the existence of such writing? There are several reasons, for example, emotional coping mechanism, an outlet of emotion, a need for express, or reflection, a tool for integrate thoughts. Writing is motor-cognitive embedment, like hand gesturing during speaking. In the framework of cognitive embodiment, writing might facilitate cognitive reasoning. So yes, writing exist without being read, moreover, writing has value before being read. Broadly, any practice has value.

Being judged and viewed is inevitable for academic writing to serve its purpose. For example, the end point of a journal article is to be read. Audience and readership are integrated parts of academic writing. This is dinstinct from writing as a form of art. In the setting where writing is taken as a form of art, writer focus more on what they want to express, for example, criticism, anger, etc. To make the writing understood is less a burden for the writer. And the art often evoked different echoes in reader with different experience. It resonates when a reader has shared a similar experience or can empathize through metaphor and imagery. In contrast, academic writing is designed to inform, instruct, or persuade. As an endeavor in science, academic writing aims to communicate the findings such that people from different walks of life can capture what precise knowledge that the authors want to convey. As a form of communicating knowledge, it prioritizes clarity, logical flow. As a result, the writers now take the task of making reader understand.

How should we write for being read? I will discuss the “how” in the setting of academia. Let’s do an thought experiment: imagine a paper that reports a technique capable of curing cancer. People at risk should be motivated to read and understand it. There is a catch, importance alone does not ensure engagement. Human attention is allocated according to perceived relevance, cognitive effort, and emotional salience. If that cancer-curing paper is written in dense jargon and inaccessible to non-specialists, many people whose lives depend on it may never grasp its meaning. This reasoning makes me realize, my cognitive pathway is not universal. As a researcher, I cannot assume that others digest knwoledge the way I do. If I want my work to matter beyond myself, I should write in a way that invites understanding, that is clear enough to reduce effort, to invite attention, and to sustain curiosity. To write for being read is to transform knowledge from something merely true into something intelligible, therefore contribute to the human knowldge base and promote broader application.

The working conclusion is that the more important the research, the more responsibility the writer has to make it cognitively accessible.

Writing as clarification or manipulation

If we push the idea “we should write to make knowledge intelligible” further, it becomes unsettling: to make something intelligible is also to shape how it is perceived. To shape perception is to persuade. Persuasion as inevitable. Humans are constantly persuaded, through education, media, and communication. Our mind is being remodeled as we sense the world, the incredible ability of human, learning. In this context, every sentence in writing reweights beliefs, and guides interpretation.

There are level of persuation: coercive persuasion or epistemic persuasion to help someone see what is true. My goal of writing aims for the latter. A good eduation strives for the latter too. It defines what counts as evidence, whow to reason, and what do we live for.

If education achived its goal, it means that readers have identical cognitive priors, and identical interpretive frameworks, and writing would require less effort from the writer. I’d love to see a day when writing required no rhetoric implies no ambiguity, no interpretive variation, and no epistemic asymmetry. I realized this may not be biologically or socially possible, at least not at this moment.

Perhaps the deeper question is whether a perfectly objective communicative world is even desirable. From an evolutionary standpoint, cognitive diversity may be adaptive. Variation in interpretation allows disagreement, innovation, and error correction. A world in which every mind mapped writing identically to meaning might be efficient, but also brittle.

Reader-Engineered Writing

Here comes the debates. We can present results and knowedge in a way that only few people or only the writer can understand. That’s a personaly choice. However in today’s life pace, a paper that is difficult to follow, either because of jargon, poor organization, or lack of contextualization, discourages reader from continuing reading and understanding it. This limits its reach and impact. More precisely, such writing can not make little contribution to general knowledge, which violate the autristic purpose of academic reading. A paper that is hard to read for the reader often fail the second objective as well, to get recognition. Peer-review is a unpaid labor. most likely, Your peers will not spend time to understand your work and background before reading your paper, not to mention peer-review do not pay your peer.

Thus, a foundational epistemological principle of academic writing is that it should be readable. This shift introduces a responsibility: to make our message accessible, relevant, and engaging. Finding a right way to communicate knowledge clearly is of course time and effort consuming. Given our limited time, how can we write in an efficient way that convey our knowledge that benefit as many readers as possible? That is why I would like to share a framework for reader-engineereed writing

framework for writing in academic setting

So far, the arguments presented support that considering readership is an important epistemology for academic writing to serve its purpose. A framework built upon natural reasoning process of human cognition can guide academic. Humans want to know why, how, what, and so what. Therefore, a useful structure for the results section—follows the sequence: Motivation → Methods → Results → Interpretation. We begin by asking why the work was done (goal and motivation), then describe how it was done (methods), followed by what was found (results), and finally what it means (interpretation).

Academic writing is not merely a summary of finding. It is an integral part of active research. From my own experience, I will outline how to write to effective communicate knowledge and contribute to research. Research usually starts by writing proposal where goals, background, and methods are pre-defined. This pre-definition serves an epistemic function. It guards against bias and unjustified post hoc claims. Next, the study is conducted according to the protocol, the primary outcome is analyzed using pre-specified methods, sensitivity analyses generate new hypotheses, and writing conveys the gained knowledge.

Once results from planned analysis and necessary controls are available, we should have a sense of the big picture. I advocate drafting the abstract and introduction at this time, before in-depth analysis and sensitivity analyses. This anchors the work in its intellectual context. Results are then organized, with figures used to support and clarify the written narrative. The discussion evolves in parallel with the results: as data are analyzed, insights emerge, patterns are interpreted, and limitations and implications are addressed. Finally, I will describe the methods with two guiding questions:

1. What motivated each analysis?
2. If I were new to this study, what background would I need to replicate the work? Depending on scope, this may be supplemented with detailed tables and appendices. I believe this approach is both efficient and epistemologically sound. Below, I consider three debates that arise within this framework.

Debate 1: Interim Analysis lead to Insight or Bias

One ongoing debate in research design concerns interim analysis. Should we analyze data during the study to optimize resource use and gain early insight, Or should we avoid this to prevent bias and false discoveries?

In conventional paradigms, interim analysis is discouraged because it may lead to “double dipping”, inflating the chance of false positives. However, in domains where data are rare and the cost for experiment is tremendous, such as intracranial recordings in human patients, there is a growing recognition that interim insights may be ethically and practically justified. In this setting, patients volunteer time and accept risk. With limited funding and high logistic cost is limited, it would be a lose if a decade-long study on ten patients yield no conclusion because the paradigm was flawed from the beginning.

Personally, I would highlight the importance of sanity checks at the begining of the study, which hopefully identified potential design flaw. I can see the values of interim analysis in hypothesis generation, but not in hypothesis testing. I would decide abort the study based on the interim analysis, for example, safety concern in a clinical trial. I would design subsequent study based on the interim analysis while following the predefined protocol if no flaw is identified. In addition, carefully documenting the interim results, any changes in hypotheisis, methods allow us gain real-time insight while preserving transparency.

Debate 2: Introduction First, or Last?

One recurring dilemma is whether we should write the introduction before or after analyzing results. Many researchers prefer to start with results and then shape a introduction that frame them more clearly. This approach is practical because most journals favor papers that read compelling, that is, give the impression that the work is advancing the field. Notably, most readers may not be deeply familiar with the field. By shaping the introduction around the results, the paper could stands stronger chance of passing the review process. However, this way may obscure the broader context, risking a missed opportunity to foreground the most important knowledge gap. I recommend the opposite. In my opinion, transparently presenting the big picture in the introduction and refine results to address important knowledge gaps as best as possible does not make a paper less compelling. Research is always constrained by practical and physical realities, so no study can fully resolve every open question. Yet by clearly situating the work within the larger scientific landscape, a paper helps the audience grasp understand the current progress in science, and connects the findings back to the central issues in a frank and authentic way. Such honesty not only respects the reader but also builds trust and emotional resonance with the authors’ motivations, making the contribution feel more meaningful, even if it is necessarily partial.

Writing the abstract and introduction first forces us to re-Review the literature (parallel work emerges during the execution of the project), identify advance during the years when study is conducted, indentify gaps this research can solve, and reorganize results in a way that follows the advance of knowledge in this field,and most importantly, update analyses with most reasonable methodologies and conduct control experiement and statistical control needed to draw conclusions, given newly identified confounds

This approach and mindset not only anchors the analysis but also ensures that conclusions are grounded in existing knowledge. In fact, this approach fit my philosophy of science: to solve unknowns, not by narrating what we’ve happened to find. However I have to admit, a better narration is important to communicate the knowledge to the reader. And the good new is that they do not conflict with each other. A well-articulated story helps readers engage with the work, but it should not come at the cost of obscuring the larger context or the unresolved gaps in the field. Second, although it take times to implement the most appropriate methods and sometimes we can encouter the scenario where the hypothesis defined in the proposal has been somewhat verified, writing the introduction and refining results thereafter might be less efficient than finding a suitable narrative. But in my experience, this often yield higher-impact papers and a smoother peer review experience.

Debate 3: Figures First, or Text First?

Having figures ready early is a common and useful practice when writing journal articles. For many readers, visual content captures attention more readily than text, and figures often provide a coherent storyline on their own. Visually inclined thinkers, in particular, may grasp the main idea more quickly through figures. I do not oppose having the figures themselves represent the full story—ideally, they should stand alone and cohesively convey the main message. That said, I personally prefer to begin with text. As an analytically oriented reader, my understanding from a paper starts with the quantified results and the logic laid out in the text. Figures then serve as a complement representation I turn to when I want to clarify or look for evidence.

Writing the results in text first also helps me determine which aspects of the data are most important to illustrate and what kind of visual representation will best illustrate the knowledge. In this way, figures support the claims and help comprehension through spatial representation. Both approaches are epistemically sound, but my own practice is to write text first.

Conclusion

Writing is time-consuming and rarely rewarded immediately in academia. Yet it is an important component in research, for its ise for reflection, connection, and contribution.

This essay reflects on the purpose of writing, and share a structured and transparent workflow that prompt our writing to fullfil its purpose efficiently: make readers understand.

update

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III. Thought 2:

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IV. Neuroscience of Convincing

Humans rarely update beliefs from raw data alone.

Belief change requires: 1. Coherence with prior knowledge 2. Emotional regulation (avoid threat response) 3. Narrative framing 4. Trust in the source

If writing ignores these, even true findings fail to propagate.

So persuasion is not manipulation.

It is cognitive scaffolding.

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V. The Cancer Example — Two Scenarios

Scenario A:

A paper describes a cure in dense, inaccessible language.

Patients: • Don’t understand it. • Don’t know whether it applies to them. • Don’t know what to do.

Result: Impact is minimal.

Scenario B:

The same discovery is clearly contextualized: • Why it matters • Who it helps • What risks exist • What steps follow

Now understanding converts into action.

So the issue is not: “Should people be motivated?”

The issue is: “How do we convert importance into comprehension?”

Writing is that conversion mechanism.

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VI. But There Is a Real Tension

Your discomfort is pointing to something subtle:

If writing is persuasion, is clarity partly strategic?

Yes.

But the ethical line is here: • Persuasion to clarify truth vs. • Persuasion to distort perception

Science writing persuades toward: • Accurate inference • Appropriate confidence • Collective coordination

It should not persuade toward exaggeration.

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VII. Deeper Philosophical Framing

You can think of writing as operating on three axes:

1. Epistemic Function

To refine truth internally. (Writing generates thought.)

1. Communicative Function

To transmit structured knowledge.

1. Coordinative Function

To align collective action around shared understanding.

Your essay strongly covers (1) and (2). Your new thoughts introduce (3).

Academic writing is not just making others understand — it is enabling coordinated cognition at scale.

That is why readability matters.

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VIII. Why “Reader-Engineered Writing” Is Not Submission

It may feel like: “If I engineer for the reader, I am compromising purity.”

But cognitively:

Understanding is co-constructed.

Meaning is not injected. It is built in the reader’s brain.

If the writer ignores the architecture of human cognition, the message cannot instantiate properly.

So reader-engineering is not dilution. It is biological realism.

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IX. The Real Question You’re Asking

You’re really asking:

If truth is strong enough, shouldn’t it stand on its own?

But truth without transmission is inert.

A cure locked in unreadable text cures no one.

Knowledge has impact only when embedded into other brains.

Writing is the embedding process.

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X. A Possible Synthesis

You can integrate your two thoughts like this: 1. Research importance creates moral weight. 2. Human cognition requires persuasion for activation. 3. Therefore, writing must both: • Respect truth • Respect human cognitive constraints

Writing is not lowering the bar for readers. It is lowering friction for truth.

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XI. Final Reflection (Neuroscientist-Philosopher Position)

From a brain perspective: • Humans are energy-efficient. • Attention is scarce. • Meaning must be scaffolded.

From a philosophical perspective: • Knowledge unshared is incomplete. • Truth requires intersubjective validation. • Society runs on structured persuasion.

So writing in academia is not merely reporting findings. It is an act of ethical translation.

The more important the work, the greater the responsibility to make it understandable.

Not because readers are lazy.

But because cognition is finite.

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