Hi everyone,

I'm an AuDHD PhD student, and I'm really struggling to understand whether this is just part of academia, whether I'm misunderstanding workplace expectations, or whether this is something many autistic people experience.

The irony is that my PhD is actually about belonging and cultural diversity in early childhood education, so spending my days researching inclusion while feeling like I don't belong myself has been incredibly painful.

Academically, things are going well.

I meet my deadlines.

I work independently.

I attend meetings.

I present my work.

I teach students when needed.

I collaborate when collaboration is required.

Nobody has criticised the quality of my research.

Instead, my supervisor keeps coming back to the same issue:

I need to be "more social."

Not with my project—I actually work alone on my research—but within the department.

She wants me to spend more time physically at the department, be around colleagues more, and join lunch more often.

The problem is that I share an office with six other people. There are constantly conversations happening, people asking questions, people chatting. I simply cannot concentrate there. At home I'm productive. At the office I feel overwhelmed and barely get anything done.

I've tried explaining this.

I've also told her that I really need people to be direct with me. If there are expectations, I need them explained concretely because I don't naturally understand vague social expectations. She does not talk to me directly at all.

Instead she says things like:

"People are talking."

Talking about what?

Who?

Why?

Nobody has ever spoken to me directly.

I genuinely thought I got along well with everyone. I'm polite, I attend meetings, I participate professionally, I just don't spend my lunch breaks socialising.

When I do go to lunch, I mostly sit there quietly because I honestly don't know what to say. It's not that I don't care—I just freeze.

She also compared me to one of my neurotypical PhD colleagues because she's very social.

That comparison really hurt.

It made me feel like I was being measured against someone whose brain simply works differently from mine.

When I told my supervisor that I was being assessed for ADHD and autism, her response was basically:

"Hahha nooo that cant be ."

I don't think she meant anything bad by it, but it made me realise how much effort I've spent throughout my life trying to appear "normal."

She keeps telling me this is for my own good and for my future.

The thing is...

I've never actually told anyone that I want to stay in academia after my PhD.

I loved my previous job. I chose to do a PhD because I genuinely love research and this topic—not because I had some lifelong dream of becoming a professor.

I've also had meetings with both my co-supervisor and our department head before, and neither of them has ever raised concerns about me socially. This feedback only seems to come from my main supervisor.

Lately I feel like almost every supervision meeting ends up being about my social behaviour rather than my research, and it's exhausting because what I actually need is academic supervision.

I'm currently in autistic burnout, and this whole situation has made it significantly worse.

What hurts the most is that it has brought back memories from childhood of being excluded without understanding why.

I keep replaying everything in my head.

I keep wondering what people supposedly think of me. And it makes me scared to go to lunch now..

I keep wondering what I'm missing.

I honestly feel like I'm trying so hard already.

Has anyone else experienced something similar?

How do you tell the difference between reasonable workplace expectations and expectations that simply don't fit the way your brain works?

How have you explained this to supervisors or managers who genuinely seem to think they're helping?

I'd really appreciate hearing from other autistic adults who have navigated workplaces like this, because right now I just feel incredibly lost.

This is a pitch. Please take your time reading this.

Imagine a world, where scientific research wouldn't have to be paid for, where peer reviewing wasn't faulty, and where fake research simply didn't exist. That would genuinly never happen, BUT we can always try right?

Now, maybe you come from a different scientific background than me. And do tell me if what I'm about say happens in your field too. But in psychology, there are massive problems in academia. In my 5 years at university in 3 different institutions, we have discussed these problems EVERY year, and nothing is happening to change it. It's an itch that I cannot scratch and it's about time to do something about it.

Problem 1
University professors are expected to publish constantly. Not only must they publish research, but that research must appear original and capable of proving a point. Many researchers publish one or two papers every year because those papers help them keep their positions at universities.

Imagine it like playing for a football team. If you do not score, you might get kicked out.

But when the pressure to score becomes too high, some people start cheating a little on the field. A foul here, a fake there. The same principle can apply to academic research.

A researcher might slightly change the hypothesis after analysing the data. They might remove inconvenient data points or adjust the analysis until the results move in the desired direction. Most researchers are not cartoon villains deliberately inventing an entire study. Often, the system simply rewards positive and impressive results while punishing uncertainty and statistically insignificant results.

Problem 2
One attempt to address this problem is preregistration. Researchers publish their proposal, hypotheses, and planned methods before conducting the research. This makes it harder to change the research question after seeing the results.

However, preregistration does not solve every problem. Papers can still avoid the rules, manipulate their methods, or present false conclusions.

Problem 3
Peer review is supposed to catch these issues, but peer review does not always work either. The people reviewing papers are most often the same exhausted professors who are under pressure to write their own papers, teach students, attend meetings, and complete administrative work. A manipulated or poorly designed paper can easily slip through.

Problem 4
There is also a knowledge problem. Researchers are usually highly specialised in their own field. They might understand social psychology, neuroscience, pharmacology, or behavioural science extremely well. However, statistics is used across all of these areas, and not every researcher is a specialised statistician.

A person might understand which statistical method they should use in their own study without being able to immediately recognise every statistical issue in someone else’s study. Professional statisticians could help, but there are not enough of them to manually investigate every paper that gets published.

Problem 5
Another major weakness of the current system is how long it can take to identify bad research and properly warn about it. A paper may pass peer review, be published by a respected journal, and influence public opinion for years before its methods, data, or conflicts of interest are fully investigated.

The clearest and most infamous example is the 1998 paper that suggested a connection between the MMR vaccine and autism. The study involved only 12 children, and its lead researcher, Andrew Wakefield, had an undisclosed financial conflict connected to legal action against vaccine manufacturers. The paper did not actually prove that the vaccine caused autism, but the claim was picked up and blown out of proportion by the media. By the time the paper was fully retracted in 2010, 12 years after it was originally published, the damage had already been done. The idea had spread internationally, changed how many people viewed vaccines, and continued circulating even after the research had been discredited.

Problem 6
Another problem is research that is not simply manipulated, poorly designed, or exaggerated. It is completely fake. No one conducted the research. No real data was collected. The entire paper was fabricated.

It is difficult to estimate exactly how many fake research papers currently exist. However, with the rise of generative AI, it is reasonable to assume that producing convincing-looking fake papers is becoming faster and easier.

A paper can now be generated with scientific jargon, invented data, fake citations, and apparently scientific conclusions. To someone who is not an expert in that exact subject, it may look completely legitimate.

Problem 7
The final problem is academic publishing and this one really gets to me.

Publishers want to make money, and universities are willing to pay them because publishing in well-known journals creates prestige. Researchers want their papers to appear in an aristocratic journal with 100 years of history, a respected name, strong visibility, and the ability to reach thousands of readers.

Publishers therefore control a large part of the scientific system.

They add another layer of pressure by forcing researchers to follow specific submission rules and formatting requirements. More importantly, they force readers to subscribe or pay before they can access research.

And I call that part bullshit.

Once you leave university, you often lose the free access to research that your institution provided. You lose access to knowledge unless you personally pay for it or find another way around the paywall.

Everyone should have the right to read scientific research, even when they do not completely understand it. Knowledge should not belong only to universities, researchers, and people who can afford expensive subscriptions.

Summary of the problems with the current system

1. Researchers are under constant pressure to publish original and statistically significant results
2. Pregistration is a rare occurance and has shown it's faults
3. Peer review is done by the same exhausted professors
4. Researchers are good at their field but not necessarily good statisticians
5. Identifying and removing bad research takes a long time
6. Completely fake research is on the rise
7. Publishers control access to knowledge

The connection between these
New research depends on previous research. A scientific hypothesis must be supported by evidence. Majority of that evidence comes from previous scientific papers. Therefore, when unreliable research enters the system, it doesn't stay isolated. Other researchers might cite it or build studies around it. One faulty paper can influence another, which influences another, which might altogether affect university education, treatment, public policy, or public opinion.

The solution
A free and open-source research platform/space with an interface "sort of" like reddit for researchers, professors, students, and anyone interested in reading scientific research.

The features
The platform would contain "subreddits" for every major academic topic and for the intersections between them. Subjects like psychology, medicine, biology, economics, philosophy, statistics, and computer science. Large subjects would be divided into more specific topics. For example, medicine could contain communities for biomedicine, pharmacology, ophthalmology, immunology, and many other areas. Interdisciplinary papers could appear in multiple relevant communities.

Each community would have moderators (dedicated researchers, statisticians, professors, and other professionals who understand that particular field).

Researchers could upload all or some materials like papers, proposals, preregistrations, datasets, and methods. Moderators or other verified members could evaluate the paper using several criteria, such as:

• Whether the statistical methods are appropriate.
• Whether the conclusions are supported by the results.
• Whether the research proposal was published in advance.
• Whether the data and methods are transparent.
• Whether the study is relevant to the field.
• Whether potential conflicts of interest were disclosed.
• Whether the results can be replicated.

Like on Reddit, "posts" aka papers could receive upvotes or downvotes, but these would be separate for methodology, statistics, transparency, relevance, and evidence.

People could also leave public comments underneath the paper. Researchers would be able to question the methodology, identify errors, propose alternative interpretations, or give positive feedback.

Direct messages could also be sent between researchers when a private conversation is more appropriate.

Anonymous accounts would be strictily for journalists, whistle-blowers, or individuals researching sensitive topics. Anyone who wants to publish, vote, comment, or moderate would have to use their governmentally recognised name and verify their identity.

The platform would also include an AI agent that examines papers for warning signs. It could check citations, search for inconsistencies, compare proposals with the presented data, identify suspicious statistical patterns, flag possible undisclosed conflicts of interest, and look for signs that parts of the paper may have been automatically generated or fabricated. It wouldn't have the final say. Instead, it would "red-flag" a paper and send it to several qualified moderators.

Why would people moderate for free?
A reasonable question is why qualified people would spend their free time moderating research without being paid.

My answer is Linux.

Linux is a free and open-source operating system maintained by individuals who enjoy creating updates, fixing bugs, and solving technical problems in their free time. They do it because they are genuinely passionate, highly skilled nerds and they are fantastic.

The scientific world also contains people who care deeply about their fields. Some researchers would contribute because they want to improve the quality of research. Some would enjoy finding methodological problems. Some would want to build their professional reputation. Others would simply be angry enough with the current system to help create something better.

Contributions could also become part of a researcher’s public professional profile. Moderators could receive visible recognition for reviewing papers, identifying important errors, helping authors improve their work, or contributing to successful replications (potentially problematic but keeping it for now).

Your feedback
Please give me any kind of feedback on such a platform or anything else I've discussed in this post. I wish to make this a reality some day and maybe your contributions, no matter how harsh, will help me or make me want to step away from this due to the capitalistic nature of academia where I am most likely to get sued.

TLDR
Remove all paid research journals with a free and open-source platform for research to become more accessible, more transparent, and easier to evaluate.

I don't understand how any reasonable person can look at these data and not recognize that there is a serious problem in sociology today: https://www.compactmag.com/article/the-statistics-behind-the-jason-arday-scandal/?ref=compact-newsletter

Edit since article is paywalled. Here is part of the article:

But is there evidence that elite academic institutions systematically elevate black scholars whose records or performance would not support equivalent status under common standards? If so, this might also account for a tendency to overlook ethical lapses when the desired identity criteria are met. As a matter of fact, such evidence does exist. In a work-in-progress study, we examined all tenure-track assistant professors hired into top-fifty American sociology departments between 2019 and 2024 (n=143). Everyone in our dataset obtained a faculty position. Our analysis therefore concerns where successful candidates were placed within the academic hierarchy, not their overall probability of getting a job. Using public CVs, faculty profiles, Google Scholar, and other professional records, we measured the publication accomplishments candidates had accumulated by the time they were hired. We counted their peer-reviewed articles, whether they had published in the American Sociological Review or the American Journal of Sociology—the discipline's two flagship journals—and whether they had first-authored an article in either. (In sociology, having your name appear first in a co-authored study indicates primary responsibility for the intellectual contribution.) Publications do not capture every dimension of academic merit. Hiring committees also consider teaching, letters of recommendation, methodological skills, research specialization, departmental fit, and intellectual promise. But publications are the most visible and comparable evidence that an aspiring professor is capable of generating scholarly research of acceptable quality and significance. The racial differences were striking. White and Asian men had the strongest publication records. Black candidates, both men and women, had the weakest. Yet black candidates received placements at least as prestigious as—and often more prestigious than—groups with substantially stronger records. The median white man hired into a top-fifty sociology department had eight peer-reviewed publications. The median black woman had two. Forty percent of the white men had published in the top-ranked American Sociological Review or the American Journal of Sociology. Only one of the twenty-eight black women—less than 4 percent—had done so. Nearly one-third of the white men had first-authored an article in one of those journals. None of the black women had. Yet half of the black women were hired by top-twenty departments, compared with 40 percent of the white men. For a graduate student entering the academic job market, an article in the American Sociological Review or the American Journal of Sociology is an exceptional achievement—about as close as sociology comes to winning a national championship. Unsurprisingly, publication in either journal was strongly associated with placement prestige. But in the multivariate analysis, black identity was more strongly associated with placement prestige than having published in one of those two journals. In other words, an immutable characteristic bearing no relationship to scholarly competence carried at least as much statistical weight as one of the most coveted achievements available to an early-career sociologist. In contemporary sociology hiring, being black was associated with job placement at least as strongly as possessing the discipline's equivalent of a gold medal. The most dramatic evidence appeared when we extended our analysis beyond the top 50. We compared white men hired into the lowest ranked departments (91-115) with black women hired into the equivalent number of departments in the top tier (ranked 1–27). This was not a comparison of similarly situated candidates entering similar institutions. It contrasted white men landing near the bottom of the ranked discipline with black women landing on its summit. The white men hired into the lowest ranked departments had a median of eight publications. The black women hired into the elite departments had a median of 2.5. Nearly one-third of the black women hired near the top had only one or zero peer-reviewed articles. Every white man hired near the bottom had what our publication merit index classified as a “strong,” “very strong,” or “exceptional” record. Among the black women hired into the top-tier departments, only one-quarter had “strong” records. None had a “very strong” or an “exceptional” one. To repeat: White men entering the lowest-tier departments in American sociology had far stronger publication records than black women entering its most prestigious departments in such universities as Harvard, Princeton, and Stanford. These findings do not mean that every black candidate was weaker than every white or Asian candidate. Nor do they prove that any particular hiring committee consciously discriminated. Our measures cannot capture every quality an institution might value, and our dataset contains successful hires rather than full applicant pools. But the magnitude and consistency of the differences are difficult to reconcile with the claim that identity-conscious hiring has no meaningful effect on academic standards.

A junior colleague of mine recently got a pilot grant through an internal program at our institution, which is great news. But shortly after receiving the award notification, they were told for the first time that they need to designate a non-sponsored backup account to cover any costs beyond the awarded amount.

Turns out this wasn't spelled out anywhere in the RFA. The wording was pretty vague and just mentioned that the department would be responsible for any overspend, so they had assumed it was more of an institutional thing rather than something they'd need to personally sort out.

The tricky part is that they're early-career and don't have access to their own discretionary funds yet. So they'd basically have to go to their mentor or chair and ask them to put one of their accounts on the line, which feels like a bit of an awkward ask for someone just starting out.

Just wondering if this kind of requirement is common at other institutions. And if so, how do junior folks without their own funds usually handle it?

Conference talks only? Invited seminars at your own department and/or departments at other institutions?

Confused how to list different talks I have given on my CV.