Chris Hartgerink

In July, I got notified one of my passwords was available in a dark web data dump, alongside my email. I was able to pinpoint the breached service because I use unique passwords for each account. That service is Pensoft.

Disclosing a Data Breach to Pensoft

In the run up to the European elections, I received a moderation report for a post that contained misleading polling information on the Mastodon server I am responsible for. As a result, AkademieNL now has a new server rule, as formulated above. This blog post dives a bit into the need for this rule and how I came to it. The reported post contained misleading election information.

New AkademieNL rule: No disinformation

I want to recommit to writing, to recommit to actively and publicly think about what is happening. I want to recommit to the idea that thoughts are dynamic and never settled — that thinking in public helps move away from sharing only finalized arguments. Thoughts are produced and reproduced through the conversations we have, be it directly on the phone or indirectly through writing and reading.

The courage to discuss

Leaving Twitter  Today marks the thirty day period of my Twitter deactivation, which means my account is now slated for deletion. Taking this step is reminiscent of when I deleted my Facebook account over a decade ago. It again feels like a bigger thing than it practically is - I haven’t missed my account over the past thirty days, at all. Maybe some of you are thinking about keeping or deleting your Twitter account.

Finally leaving Twitter

I am a member of the Society for Improvement of Psychological Science (SIPS) – have been since 2017. I joined their yearly conferences every other year starting in 2017, but I will not be joining the 2025 conference in Budapest, Hungary. For me, the big selling point of SIPS are the people – the location choice for 2025 (unintentionally) signals that some people are less important.

Why I'm not going to SIPS 2025

If you are not familiar with why calling your organization a family is problematic, here is a very brief recap. While plenty of people have fantastic family environments, family is not a positive experience for everyone.

"Community" is the new "family"

The social media landscape is so different today from when I started participating around 2011. Things change, and that is okay — when the old dies, it becomes the compost for something new. For me, something new sprouted from Twitter's compost beyond just joining Mastodon: I am taking over as the admin for the Mastodon server akademienl.social.

AkademieNL's new admin

I read a lot of news, but I do not like being consumed by it. The balance between what's happening now (news), the short or long past (history), and potential futures (foresight or analysis) is a rough one to keep. This post is about making sure that sources are readily accessible where possible, straight from the news. Part of not becoming consumed by the news and its biases is doing source research and verifying information.

Open sourcing the news

Recently, I left the Upstream editorial team as a result of changing priorities.  I figured it would be a good idea to reflect before I forget.

Upstream reflections

I have been a bit stuck in my head over the past few months. The world's changing so rapidly, it is increasingly hard to come to grips with things big and small. This even though there is a desire to jump to quick conclusions (a typical sign of overconfidence!). As a result of being stuck in my head, I have been absent on here. I am getting back in a habit of writing, although this simple post took me almost a week to write.

Some professional updates

For me, the end of the year is a time for reflecting on the past; summer is a time for reflecting on the future. This summer, I have been thinking about how I spend my labor energy in a rapidly changing world. What is meaningful and a good utilization of my skillset?

Applying as a parliamentary candidate

At university, I was trained to have ideas — to see gaps in between the individual pieces of knowledge, and to seize them as opportunities to move the needle forward. Ideas are a currency, yet executing on those ideas feels undervalued. I am grateful for the years I spent training that kind of creativity. It still brings me joy to have or learn about ideas that make me shift my perspective.

Ideas come cheap

💡  This is a post in a series of Stories From My PhD. For background on this series, read the announcement post. As a researcher you are bound to uphold certain standards of conduct. When I defended my PhD, I was reminded of that rather explicitly with the following statement before being awarded my degree:  This statement was only introduced in the past decade, but I think a reminder like this is a simple and effective idea.

Committing to an Ethics Code

Starting a small company means the buck stops with me on everything, every time. Since founding Liberate Science three years ago, that means I’ve had to pick up a lot of skills.

The joy of compounding skillsets

💡  This is a post in a series of Stories From My PhD. For background on this series, read the announcement post. In 2017, I received a Mozilla Open Science Fellowship, which ended up becoming a career defining opportunity. I was able to expand my horizons beyond the academic statistics work I was doing, and started germinating ideas that, after cultivation, resulted in ResearchEquals. This fellowship, however, almost did not happen.

The story behind the Mozilla Fellowship

The most common definition of anti-semitism is the racist treatment of Jewish people.

 [1]

Even though when we talk about racism we often talk about white supremacist racism towards Black, Indigenous, and People of Color (BIPOC), racism can be directed to any group.

 [2]

But that also means that if you have been learning about racism since Black Lives Matter, we can use that knowledge to understand anti-semitism better.

Am I an anti-semite?

💡  This is an idea I've toyed around with for a few years, but never wrote down. I would love to hear your feedback! Competitive research processes lead to many perverse incentives - incentives that put the researcher and the research process at odds. For example, because of selective publication pressures researchers primarily end up publishing those research processes that end up in significant or novel results.

The Excellence Paradox: Selecting for excellence is self-defeating

💡  This is a post in a series of Stories From My PhD. For background on this series, read the announcement post. Reading my emails from when I started my PhD, I see that I was full of a different kind of energy. Naive energy, sure, but also unencumbered by how things “were supposed to happen” or the ‘just’ in the “just the way things are.”  I recently discovered an email that I received only two months into my PhD.

When the implicit becomes explicit

💡  These are my remarks for the junior researcher panel at the APE2023 conference. This blog is slightly edited for clarity and expands the quote selection from Aaron Swartz. Aaron Swartz died a decade ago today - to commemorate him I’ll start by reading selected quotes from the Guerilla Open Access Manifesto here today. I would argue to reframe publishing as a question of power — as Aaron talked about it: Information is power.

Remarks for the Berlin Publishing Conference 2023

This week I am a bit at a loss what to write about - I had drafts on the weaponization of meta-research, how to write an R package in 2022 (but the year's almost out), the consequences of owning your digital infrastructure. But none of it really fell into place enough yet.

Dipping my toes into 3D

Startup Therapy series     As write more on this blog, I have come to the realization I thoroughly enjoy coming up with themes to coalesce my writing around. Themes create a certain mass for my activities, reflections, and thoughts to gather around. As a result, things collect in a way they would not without the theme being present. Themes help me write.

New series: "Startup Therapy"

💡  This is a post in a series of Stories From My PhD. For background on this series, read the announcement post. I have been to a few dozen dissertation defenses over the past decade. As a result of attending PhD defenses on a fairly regular basis with the same folk, their procedures got discussed. A lot. This story is about a situation where a university's own arbitrary regulations are arbitrarily not applied.

Arbitrary application of arbitrary rules

Inching towards the Dutch elections, increasing amounts of claims are being made about the (micro)targeting of different campaigns. Here are some: New Social Contract does not do any online ads. The Greens-Labour Party spent €323,000 - more than twice as much as the Democrats 66 (D66), who spent €153,000. The Think (Denk) Party is profiling for Turkish ethnicity. The senior 50PLUS party microtargeted on people who listen to Angerfist.

Political microtargeting

I used to think I was a man’s man and heterosexual — but why? Where I grew up there was little public exposure beyond the traditional gender roles and heteronormative behaviors.

My ongoing gender journey

Yesterday was the first of four listening sessions by the White House's Office of Science and Technology Policy. These are specifically geared towards Early-Career Researchers (ECRs), which I guess I technically would still be had I stayed in academia. I had the opportunity to briefly participate and share some prepared remarks. Sharing those here to document my own thoughts and make them more accessible.

Remarks on barriers to Open Science for ECRs

Over the past decade, the increased attention for questionable research practices (QRPs) and their origins led to the (Dutch) narrative on Recognition &amp; Rewards (R&amp;R). Very bluntly put: Incentives pressure researchers to do things that don't benefit research, so we need to change the academic incentive system.

 [1]

It is a good thing the incentive system is changing.

Undoing questionable academic practices

In October, I shared I started to look for a regular job --- last week, I started as a senior software engineer for data.org until end of 2025. In this role, I will be contributing to digital public goods using data for social impact.

Starting at data.org

I admittedly love it when pet peeves show themselves. That's when I know something is tickling my brain repeatedly and it wants to come out.

(Not-)for-profit in research

💡  These are prepared remarks for the Choice Hackathon on March 18th, 2023. Find the recording on YouTube. When we think of gender gaps in academia or society more broadly, we may think of very specific issues. But gender gaps are mere symptoms, with a common cause: The patriarchy. This is a system where maleness ultimately dominates, at the cost of everyone.

Gender gaps as symptoms of patriarchy

I used to introduce myself as a recovering academic in the years 2018-2022. Only now in 2023, am I comfortable saying I am a recovered academic. Having recovered, I am in a comfortable place to start sharing some personal stories that have not seen the light of day before in written form.

"Stories from my PhD" series

In my decade working on the openness of research I touched upon content accessibility only a few times, in part because it was and is a less discussed topic in my circles. But that does not make it less important.

Open Inaccessibility

![](https://images.unsplash.com/photo-1583339522870-0d9f28cef33f?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=MnwxMTc3M3wwfDF8c2VhcmNofDR8fHB1cnBsZXxlbnwwfHx8fDE2NzM2MTA0MDA&ixlib=rb-4.0.3&q=80&w=2000)

I used to introduce myself as a recovering academic in the years
2018-2022. Only now in 2023, am I comfortable saying I am a recovered
academic. Having recovered, I am in a comfortable place to start sharing
some personal stories that have not seen the light of day before in
written form.

Writing stories is a way for me to remember and to reflect on some of
the events that shaped me. It will become my external memory archive as
I wade through my personal archives of recordings, emails, and internal
memories. I do not yet know the lineup of these posts.

It will not be hard to figure out who is who in these stories,
especially if you are familiar with the actors despite my
pseudonymization. But that is not the point --- in addition to my
external memory I hope these stories may help others who are living
similar stories feel seen. I love the idea of [trauma-informed
design](https://digitalfutures.space/deepdive/trauma-informed-design/?ref=chjh.nl),
where we use our trauma to inform how we imagine better futures. Maybe
revisiting some of the things I needed to recover from so intensely
proves informative to myself.

I recognize I am a male presenting white person, first-generation
student. I pass as the default even when I may not be at times in
minimal ways. In no way do I write these stories to elevate them as the
worst things in the world. If anything, I hope they may inspire others
to feel the courage to share their stories, no matter how old they are.

Symbolically, I will open this series of posts with my dissertation\'s
prologue (minus the chapter summary), to set the stage once more.

------------------------------------------------------------------------

The history and practice of science is convoluted^[\[1\]](#fn1)^, but
when I was a student it was taught to me in a relatively uncomplicated
manner. Among the things I remember from my high school science classes
are how to convert a metric distance into Astronomical Units (AUs) and
that there was something called the research cycle. Those classes
presented things such as the AU and the empirical cycle as unambiguous
truths. In hindsight, it is difficult to imagine these constructed ideas
as historically unambiguous. For example, I was taught the AU as simple
arithmetic while that calculation implies accepting a historically
complex process full of debate on how an AU should be
defined^[\[2\]](#fn2)^. As such, that calculation was path-dependent,
similar to how the history and practice of science in general is also
path-dependent ^[\[3\]](#fn3)[\[4\]](#fn4)^.

Scientific textbooks understandably present a distillation of the
scientific process. Not everyone needs the (full) history of discussions
after broad consensus has already been reached. This is a useful
heuristic for progress but also minimizes (maybe even belittles) the
importance of the process^[\[3:1\]](#fn3)^. As such, textbook science
(vademecum science)^[\[5\]](#fn5)^, with which science teaching starts,
provides high certainty, little detail, and provides the breeding ground
for a view of science as producing certain knowledge. Through this kind
of teaching, storybook images of scientists and science might arise,
often as the actors and process of discovering absolute truths rather
than of uncertain and iterative production of coherent and consistent
knowledge. Such storybook images likely result in the impression that
scientists versus non-scientists are more objective, rational,
skeptical, rigorous, and ethical, even after taking into account
educational level ^[\[6\]](#fn6)^.

Scientific research articles tend to provide more details and less
certainty than scientific textbooks, but still present storified
findings that simplify a complicated process into a single, linear
narrative^[\[7\]](#fn7)^. Compared to scientific textbooks, which
present a narrative across many studies, scientific articles provide a
narrative across relatively few studies. Hence, scientific articles
should be relatively better than scientific textbooks for understanding
the validity of findings because they get more space to nuance, provide
more details, and contextualize research findings. Nonetheless, the
linear narrative of the scientific article distills and distorts a
complicated non-linear research process and thereby provides little
space to encapsulate the full nuance, detail, and context of findings.
Moreover, storification of research results requires flexibility, where
its manifestation in the flexibility of analyses may be one of the main
culprits of false positive findings (i.e., incorrectly claiming an
effect)^[\[8\]](#fn8)^ and detracts from accurate reporting. The lack of
detail and (excessive) storification go hand in hand with the
misrepresentation of event chronology to present a more comprehensible
narrative to the reader and researcher. For example, breaks from a main
narrative (i.e., nonconfirming results) may be excluded from the
reporting. Such misrepresentation becomes particularly problematic if
the validity of the presented findings rests on the actual and complete
order of events \-\-- as it does in the prevalent epistemological model
based on the empirical research cycle ^[\[9\]](#fn9)^. Moreover, the
storification within scholarly articles can create highly discordant
stories across scholarly articles, leading to conflicting narratives and
confusion in research fields or news reports and, ultimately, less
coherent understanding of science by both general- and specialized
audiences.

When I started as a psychology student in 2009, I implicitly perceived
science and scientists in the storybook way. I was the first in my
immediate family to go to university, so I had no previous informal
education about what \'true\' scientists or \'true\' science looked like
\-\-- I was only influenced by the depictions in the media and popular
culture. In other words, I thought scientists were objective,
disinterested, skeptical, rigorous, ethical (and predominantly men). The
textbook- and article based education I received at the university did
not disconfirm or recalibrate this storybook image and, in hindsight,
might have served to reinforce it. For example, textbooks provided a
decontextualized history that presented the path of discovery as linear,
\'the truth\' as unequivocal, multiple choice exams which could only
receive correct or wrong answers, and certified stories in the form of
peer reviewed publications. Granted, the empirical scientist was
warranted the storybook qualities exactly *because* the empirical
research cycle provided a way to overcome human biases and provided
grounds for the widespread belief that search for \'the truth\' was more
important than individual gain.

As I progressed throughout my science education, it became clear to me
how naive the storybook image of science and the scientist was through a
series of events that undercut the very epistemological model that
granted these qualities. As a result of these events, I had what I
somewhat dramatically called two \'personal crises of epistemological
faith in science\' (or put plainly: wake up calls). These crises
strongly correlated with several major events within the psychology
research community and raised doubts about the value of the research I
was studying and conducting. Both these crises made me consider leaving
scientific research and I am sure I was not alone in experiencing this
sentiment.

My first, local crisis of epistemological faith was when the psychology
professor who got me interested in research publicly confessed to having
fabricated data throughout his academic career ^[\[10\]](#fn10)^. Having
been inspired to go down the path of scholarly research by this very
professor and having worked as a research assistant for him, I doubted
myself and my abilities. I asked myself whether I was critical enough to
conduct and notice valid research. After all, I had not had even an inch
of suspicion while working with him. Moreover, I wondered what to make
of my interest in research, given that the person who got me inspired
appeared to be such a bad example to model myself after. This event also
unveiled to me the politics of science and how validity, rigor, and
\'truth\' finding was not a given ^[\[11\]](#fn11)^. Regardless, the
self-reported prevalence of fraudulent behaviors among scientists (viz.
2%)^[\[12\]](#fn12)^ was sufficiently low to not undermine the
epistemological effort of the scientific collective (although it could
still severely distort it). Ultimately, I considered it unlikely that
the majority of researchers would be fraudsters like this professor and
simply realized that research could fail at various stages (e.g., data
sharing, peer review). As a result, I became more skeptical of the
certified stories in peer reviewed journals and in my own and other\'s
research. I ultimately shifted my focus towards studying statistics to
improve research.

A second, more encompassing epistemological crisis arose when I took a
class that indicated that scientists undermine the empirical research
cycle at a large scale. These behaviors were sometimes intentional,
sometimes unintentional, but often the result of misconceptions and ill
procedures in order to play the game of getting
published^[\[13\]](#fn13)^. More specifically, this epistemological
crisis originated from learning about how loose application of
statistical procedures could produce statistically significant results
from pretty much anything^[\[14\]](#fn14)^. Additionally, these
behaviors result in biased publication of results^[\[15\]](#fn15)^
through the invisible (and often unaccountable) hand of peer
review^[\[16\]](#fn16)^ that in itself suffers from various
misconceptions. This combination potentially leads to a vicious cycle of
overestimated (and sometimes false positive) effects, leading to
underpowered research that is selectively published, leading to
overestimated effects and underpowered research, and so on until that
cycle gets disrupted. These issues are not necessarily new and have been
discussed for over 40 years in some way or form^[\[17\]](#fn17)^. Given
this longstanding vicious cycle, it seemed unlikely the issues in
empirical research would resolve themselves \-\-- they seemed more
likely to be further exacerbated if left unattended. Progress on these
issues would not be trivial or self-evident, given that previous
awareness subsided and attempts to improve the situation did not stick
in the long run. It also indicated to me that the reforms needed had to
be substantial, because the improvements made over the last decades
remained insufficient (although the historical context is highly
relevant)^[\[18\]](#fn18)^. Because of the failed attempts in the past
and the awareness of these issues throughout the last six years or so,
my epistemological worries are ongoing and oscillate between pessimism
and optimism for improvement.

Nonetheless, these two epistemological crises caused me to become
increasingly engaged with various initiatives and research domains to
actively contribute towards improving science. This was not only my
personal way of coping with these crises and more specific incidents, it
also felt like an exciting space to contribute to. In late 2012, I was
introduced to the concept of Open Science for my first big research
project. It seemed evident to me that Open Science was a great way to
improve the verifiability of research^[\[19\]](#fn19)^. The Open Science
Framework had launched only recently ^[\[20\]](#fn20)^, which is where I
started to document my work openly. I found it scary, difficult, and did
not know where to start simply because I had never been taught to do
science this way nor did anyone really know how. It led me to experiment
with these new tools and processes to find out the practicalities of
actually making my own work open, and I have continued to do so ever
since. It made me work in a more reproducible, open manner, and also led
me to become engaged in what are often called the Open Access and Open
Science movements. Both these movements aim to make knowledge available
to all in various ways, going beyond dumping excessive amounts of
information but also making it comprehensible by providing clear
documentation to for example data. Not only are the communities behind
these movements supportive in educating each other in open practices,
they also activated me to help others see the value of Open Science and
how to implement it ^[\[21\]](#fn21)^. Through this, activism within the
realm of science became part of my daily scientific practice.

Actively improving science through doing research became the main
motivation for me to pursue a PhD project. Initially, we set out to
focus purely on statistical detection of data fabrication (linking back
to my first epistemological crisis). The proposed methods to detect data
fabrication had not been tested widely nor validated and there was a
clear opportunity for a valuable contribution. Rather quickly, our
attention widened towards a broader set of issues, resulting in a broad
perspective on issues in science by looking at not only data
fabrication, but also at questionable research practices, statistical
results and the reporting thereof, complemented by thinking about
incentivizing rigorous practices.

------------------------------------------------------------------------

::: {.section}
1.  Wootton, David. 2015. The Invention of Science: A New History of the
    Scientific Revolution. Toronto, Canada: Allen Lane.
    ISBN:9781846142109. [↩︎](#fnref1)

2.  [doi:10.1017/s1743921305001365](https://doi.org/10.1017/s1743921305001365?ref=chjh.nl)
    [↩︎](#fnref2)

3.  Latour, Bruno, and Steve Woolgard. 1986. Laboratory Life: The
    Construction of Scientific Facts. Princeton, NJ: Princeton
    University Press. ISBN:0692094187. [↩︎](#fnref3) [↩︎](#fnref3:1)

4.  Gelman, Andrew, and Eric Loken. 2013. "The Garden of Forking Paths:
    Why Multiple Comparisons Can Be a Problem, Even When There Is No
    'Fishing Expedition' or 'P-Hacking' and the Research Hypothesis Was
    Posited Ahead of Time."
    [https://wayback.archive.org/web/20180712075516/http://www.stat.columbia.edu/\~gelman/research/unpublished/p_hacking.pdf](https://wayback.archive.org/web/20180712075516/http://www.stat.columbia.edu/~gelman/research/unpublished/p_hacking.pdf?ref=chjh.nl).
    [↩︎](#fnref4)

5.  Fleck, Ludwig. 1984. Genesis and Development of a Scientific Fact.
    Chicago, IL: University of Chicago Press. ISBN:9780226253251.
    [↩︎](#fnref5)

6.  [doi:10.1080/08989621.2016.1268922](https://doi.org/10.1080/08989621.2016.1268922?ref=chjh.nl)
    [↩︎](#fnref6)

7.  [doi:10.1017/cbo9780511807862.002](https://doi.org/10.1017/cbo9780511807862.002?ref=chjh.nl)
    [↩︎](#fnref7)

8.  [doi:10.1371/journal.pmed.0020124](https://doi.org/10.1371/journal.pmed.0020124?ref=chjh.nl)
    [↩︎](#fnref8)

9.  De Groot, A.D. 1994. Methodologie: Grondslagen van Onderzoek En
    Denken in de Gedragswetenschappen \[Methodology: Foundations of
    Research and Thinking in the Behavioral Sciences\]. Assen, the
    Netherlands: Van Gorcum. ISBN:9789023228912. [↩︎](#fnref9)

10. Stapel, Diederik A. 2012. Ontsporing. Amsterdam, the Netherlands:
    Prometheus. ISBN:9789044623123. [↩︎](#fnref10)

11. See for example Broad, William, and Nicholas Wade. 1983. Betrayers
    of the Truth. New York, NY: Simon; Schuster. ISBN:9780671447694.
    [↩︎](#fnref11)

12. [doi:10.1371/journal.pone.0005738](https://doi.org/10.1371/journal.pone.0005738?ref=chjh.nl)
    [↩︎](#fnref12)

13. [doi:10.1177/1745691612459060](https://doi.org/10.1177/1745691612459060?ref=chjh.nl)
    [↩︎](#fnref13)

14. E.g.,
    [doi:10.1177/0956797611417632](https://doi.org/10.1177/0956797611417632?ref=chjh.nl)
    [↩︎](#fnref14)

15. [doi:10.1007/bf01173636](https://doi.org/10.1007/bf01173636?ref=chjh.nl)
    [↩︎](#fnref15)

16. Harnad, Stevan. 2000. \"The Invisible Hand of Peer Review.\" Exploit
    Interactive.
    [http://cogprints.org/1646/](http://cogprints.org/1646/?ref=chjh.nl).
    [↩︎](#fnref16)

17. [doi:10.1037/0033-2909.105.2.309](https://doi.org/10.1037/0033-2909.105.2.309?ref=chjh.nl);[doi:10.1037/h0045186](https://doi.org/10.1037/h0045186?ref=chjh.nl);[doi:10.1037/0033-2909.86.3.638](https://doi.org/10.1037/0033-2909.86.3.638?ref=chjh.nl);[doi:10.2466/03.11.pms.112.2.331-348](https://doi.org/10.2466/03.11.pms.112.2.331-348?ref=chjh.nl);[doi:10.1207/s15327957pspr0203_4](https://doi.org/10.1207/s15327957pspr0203_4?ref=chjh.nl);[doi:10.1056/nejm199310143291613](https://doi.org/10.1056/nejm199310143291613?ref=chjh.nl)
    [↩︎](#fnref17)

18. See
    [doi:10.1177/1745691615609918](https://doi.org/10.1177/1745691615609918?ref=chjh.nl)
    [↩︎](#fnref18)

19. See also
    [doi:10.15200/winn.144232.26366](https://doi.org/10.15200/winn.144232.26366?ref=chjh.nl)
    [↩︎](#fnref19)

20. [doi:10.31237/osf.io/t23za](https://doi.org/10.31237/osf.io/t23za?ref=chjh.nl)
    [↩︎](#fnref20)

21. My first steps taken in
    [doi:10.6084/m9.figshare.928315.v2](https://doi.org/10.6084/m9.figshare.928315.v2?ref=chjh.nl)
    [↩︎](#fnref21)
:::
