by Matt Gibson

Why do scientists commit fraud? If you are active in the scientific community, you are aware of many cases of research misconduct. It happens with significant, internationally recognised research [dias-paper], and it can happen at your university, too [1] [2]. This is a fascinating question partly because of the sensational nature of the drama but also because it can make us think about the social way in which we practise science. In this blog post, I'd like to talk about a neat paper I found by Liam Kofi Bright [on-fraud], which provides a formal model for why scientists might commit fraud.

Take some of these high-profile cases: one that made a lot of noise around my research area was the case of Ranga Dias, who claimed to have discovered a room-temperature semiconductor earlier this year. This had been published in Nature and has since been retracted [dias-paper]. Because room temperature semiconductors would be a revolutionary material with wide-ranging applications from power transmission to digital electronics to medical imaging, it's almost certain that the researcher would be caught when other researchers. Given that the stakes and the probability of discovery are so high, why do it in the first place? 

You might say that the expectation is that they won't get caught, but this is also a puzzling belief suggests either: 

1. they don't see it don't see that outcome (cognitive blindness), 
2. they think that their work won't be scrutinised (deliberate deception), 
3. or that the underlying phenomenon is true, and their data gives the wrong result (noble lie). 

The first explanation is a psychological one, which might be true. Still, it doesn't really explain the why of committing fraud. Much consideration is given to the first deliberate deception scenario: scientific fraudsters are bad apples or con artists who lack morals. However, the truth is likely much messier.

There are many models of human behaviour, but one of the most prominent is the "rational choice theory". Rational choice models, as formalised by game-theoretic games, are rarely fun to play but can explain why people make the choices they do.  Bright's model works within this framework; it is a game-theoretic account of the decision-making process by the scientific community. You might be familiar with well-known game-theoretic models such as the prisoner's dilemma or matching pennies. These are examples of zero-sum, two-player games with perfect information, which are also well-known and well-studied. Bright's model, by contrast, is not zero-sum, with incomplete information and many players.

I'll briefly describe the premise of the model. The model assumes that the scientific community consists of scientists who are interested in theoretical statements that can be true or false (e.g. can a particular method of synthesis yield room temperature stable semiconductors). For simplicity, assume there are two possibilities, one of which Nature picks. Scientists privately conduct unreliable experiments that reveal evidence about the theory. Then, in light of the evidence, the scientists update their beliefs and publish their results; that is, they signal their beliefs about the theory. 
Periodically, the scientists gather at a conference to resolve the theoretical questions bugging them. The position that most scientists agree to become the received wisdom in the field and the scientists who have published in favour of that position are rewarded. Note that the scientific community may decide on a theory that does not agree with the state of affairs picked by Nature (e.g. phlogiston). So far, this is similar to other models of the reputation economy of science (e.g. Kitcher 1993).

Bright introduces a wrinkle to assign scientists different motives: they may be pure credit seekers, pure truth seekers, or mixed credit/truth seekers. Truth seekers only want the scientific community and Nature to be in agreement, pure credit seekers only want to be seen to be on the right side of the community, and mixed credit/truth seekers would like for the scientific community to arrive at the truth but also to be on the right side of the scientific community. Moreover, the scientists also have a set of beliefs about what other scientists will publish. Scientists are motivated to fraud when they are motivated to publish a paper that supports an outcome that is the opposite of what was revealed by their experiments. 

Bright then looks at how changing the motive types would increase or decrease the incentives to commit fraud. Bright also looks at how behaviour assumptions about the cost of fraud and self-confidence would also affect incentives to commit fraud. Putting all this together, he derives several interesting (if pessimistic) results. 

The first result is that turning a credit-seeker into a mixed credit/truth seeker only dissuades people from committing fraud in a setting where they believe their opinion is irrelevant. Further, turning credit seekers into mixed credit/truth seekers can incentivise people to commit fraud in new situations. Pure credit seekers will always be incentivised to commit fraud when they believe their experiments are 100% accurate. Finally, even pure truth seekers can be motivated to commit fraud when they believe their results are incorrect. 

On the positive side, however, he can show that pure truth seekers are incentivised to lie in a strict subset of situations of the mixed truth/credit seekers. He also shows if there is a high price for committing fraud, then pure credit seekers will honestly report their experiments when certain conditions are met: they think their beliefs will affect the community consensus, they believe in the true state of Nature, and they think the community will also eventually arrive at the correct theory. Bright has further interesting things to say about the scientific community in that paper. I encourage people to read it because he's a very clear writer and sometimes quite funny ( a rare trait in scholarly writing!). 

This model is attractive because formal analysis suggests counter-intuitive points. A standard theory is that the scientific credit system and the contemporary career pressures, are to blame [3]. While this is undoubtedly true for some cases, the motivation question is worth scrutinising.

 Bright shows that this is not necessarily the case; even people with ideal motives can be incentivised to commit fraud because of "noble lies". To me, this suggests that some problems about fraud are intrinsic to the scientific community because of the community nature of the decision-making. It's worth considering that truth-seeking is not always noble, nor is credit-seeking always villainous.

When this is all formalised as a game-theoretic model and in this context, the relation to the celebrated results on voting theory like Arrows' theorem becomes more apparent. The scientific consensus is a process of plurality voting. In plural voting (like all other forms of voting), it is vulnerable to strategic voting (the Gibbard–Satterthwaite theorem); a voter receives a better payoff if their vote is not a true representative of their true beliefs. Scientists would be better off lying about their beliefs if that would cause the community to arrive at what they honestly think. I think it is also quite interesting to use these game-theoretic/economic models to understand the process of science. Moreover, these hypotheses are testable in a reasonably precise way. From observational evidence, it would be interesting to see how often this happens in practice. 

I'm also left wondering how often "noble lie"-type fraud happens. In particular, I keep thinking about two well-known and controversial experiments: the Stanford prison experiment and the Millikan oil drop experiment. The Millikan oil drop experiment, a canonical experiment to determine the charge of an electron, has been criticised for removing data points from his dataset: he published results based on only 58 out of 175 recorded points. The result is extraordinarily accurate, with 0.5% per cent of the accepted value nearly 100 years later. Yet the case is not clear cut because of the complexity of the experimental setup [goodstein-in-defence]: one person's exploratory data analysis and posthoc analysis can be another person's data dredging and p-hacking.

I hope you'll agree there is much excellent work being done in the history and philosophy of science which is relevant to practising scientists. I think scientific misconduct is interesting for the same reason that a sociologist might be interested in criminal behaviour or an evolutionary biologist might be interested in the Galapagos islands because they represent an extreme. This extreme informs about the practice of science.

By Szymek Drobniak

Conferences can be scary and overwhelming – especially if you’re about to enter the fast-moving world of academia. Even having over 10 years of experience in doing research and participating in some of the largest conferences in my field – I still feel crippling anxiety every time I about to approach somebody at a large meeting. I still get flooded by waves of heat and racing heartbeats every single time I want to rise my hand and ask a question. What if the question will sound silly? What if the presenter won’t get it – or even worse: what if they misunderstand it? My ongoing struggle with crowd anxiety or self-esteem issues only make things worse.
 
However – over time I’ve learned that even severe public speaking anxiety can be overcome, and even the shyest and introvert scientists can learn few tricks that help to navigate the intimidating world of congresses and conferences. Here’s what I’ve learned over the years. Even if my ways won’t work at first – they will hopefully convince you that you’re not alone, and that public meetings anxiety is something pretty natural.
 
1) Instead of throwing yourself into the vortex of people – try to be methodical. Before the conference check who’s attending it. Pick few names that you would like to meet or speak to. Check if they have a talk or poster – that’s the easiest way of meeting people and having a good starter topic.
 
2) Public speaking anxiety can overwhelm you to the point of losing the ability to speak! The easiest way of convincing yourself you’re all good? Say to yourself that during your talk you’re the expert. You know everything (about your topic ) and the audience is here to hear and admire your talk. You’re their guide and guru for the coming few minutes.
 
3) Not being able to answer questions after your talk may make you feel bad or afraid of how others judge your performance. But not knowing the answer to a question – or, in fact, not understanding the question! – is totally normal. If it happens just naturally move to the next one. Make sure the person asking the question is not left in the void: invite them for a chat after the talk, or casually suggest meeting over lunch or dinner to elaborate more. You will appear professional – and potentially get another opportunity to meet someone interested in your research.
 
4) Have a conference buddy – e.g., a colleague from your lab that attends the same conference, or a friend from another university you know is also at the meeting. Having someone to talk too during breaks will make you feel more comfortable and help you relax. Don’t be afraid to ask your friends for help with any sort of anxiety you may feel. Quite often just speaking about anxiety is a great way to weaken its effects on your life.
 
5) Try not to steer away from round tables and panel discussions – even if you stay quiet most of the time, they are great moments to see more experienced scientists in action. You may learn many under-the-hood secrets of your field, get to know the thought leaders in the discipline, and often forge new collaborations.
 
8) Always rehearse your talks – either on your own, or in front of your lab-mates. There’s nothing more stressful than a badly rehearsed talk that goes overtime and makes chairpeople to cut your microphone off. But – rehearsing does not mean “memorising”. Avoid learning the “screenplay” of your talk by heart – memorise the main points and try to story-tell around them. It will sound much more natural – and there’s less likelihood you’ll get stuck having forgotten a line or two. Somewhere around the 2/3 of your talk – try to have an emergency connection to your final slides – just in case you do run overtime and are forced to wrap up before reaching the end of your presentation.
 
7) If you’re organising a conference – see if you can make it a bit more friendly for neurodivergent persons. Few recommendations you might consider include:

• having a quiet corner far from the buzz of the biggest crowd;
• organising a public speaking workshop or mentoring session – i.e., an event that would gently bring likeminded people together and help to break ice more easily;
• organising poster sessions in ways that loosen any excessive crowding – e.g., by having multiple sessions that target alternating poster numbers;
• inviting willing keynote speakers to have an open lunch sometimes during the conference (organised in a way that allows people to easily join or leave without attracting too much attention) – such events are a great way of giving less bold people a chance to meet the big names and start conversations that can than more easily continue during the conference.

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We bumped into quite a bunch of people and hung out extensively with the PhD students and post-docs from Bob Wong’s lab. Their work zeroes in on a range of things, particularly the effects of pollutants and pharmaceuticals on various critters' behaviors. With our research intersecting in some places, we found ourselves engrossed in some engaging conversations. An intriguing encounter came our way when we met a researcher from South Australia who's deep into studying the impact of PFAS on dolphins. She’s on the hunt to uncover whether there's any link between those unusual mortality events recorded in that part of the continent and their run-ins with these pollutants. Intriguing, right? 

​​Recently, I was awarded the E&ERC Outstanding Postgraduate Researcher award, which commemorates exceptional achievements from PhD students at the Evolution & Ecology Research Centre (E&ERC). 
 
While overwhelmed with pride and gratitude, I believe it was also time for me to reflect on the circumstances and privileges that paved the path to this accomplishment. It is rather common to bask in the glow of success, yet rarely do we show our weaknesses, and the bumpy journeys that often lead to these accomplishments. I invite you to interpret my reflections in your own way, while acknowledging that every path is different and that the role of luck and privilege vary greatly between individuals.
 
Let's start from the beginning. I was born a mentally and physically abled white male in the vicinity of Lyon, France. My mother was a first-generation immigrant from Russia, and my father was born in Algeria and later grew up in France. Shortly after my birth, my parents decided to relocate to Pointe-Noire in Congo, an environment that would soon be marred by the Republic of the Congo civil war. My sister was brought to the world in the midst of a civil war, etching a profound influence on our upbringing. After four years in Congo, my parents, fearful of escalating conflicts, moved us back to France.
 
Like many scientists, my fascination for nature was innate. However, personal events distanced me from this passion until early in my adulthood. I moved cities every few years, preventing me from building lasting social connections. My father's work also took him away for months, sometimes years, culminating in a drawn-out, emotionally draining divorce. This turbulent period forced me to prioritise my mental health over all else – my quest for understanding biology took a back seat. The divorce also placed a financial burden on my mother, making daily sustenance a recurring struggle. This financial insecurity also separated my mother from her other son in Congo - a rift that, two decades later, remains.
 
Undeniably, my upbringing was fraught with economic and emotional trials. However, this telling isn't a bid for comparison. Each of us encounters significant difficulties, some silently destructive despite their lack of obvious tragedy. I'm not insinuating that my journey was harsher than most - quite the contrary. Frankly, I was deeply lucky, and privileged. My upbringing in a secure country with a great health and educational system was a luxury denied to many. University was not a conscious and motivated choice, but more a refuge from indecision. I gravitated towards Biology simply because it resonated with me, and as university education was virtually free, it seemed like the logical choice. I chose this path by default.
 
While my affection for biology now is unwavering, this was not an immediate realisation. My initial two years of university did not captivate me as much as I had hoped. My interest was selectively inclined towards courses concerning ecology and evolution, and the image of myself as a scientist was a blurry vision at best. I also did not think I was good enough to become a scientist. Yet, I stayed because I lacked other options. Luckily, accumulating tuition debt was absent in my journey. If I did, I certainly wouldn't have chosen a university path, and for this, I bear gratitude to the French public university system. Eventually, I fell in love with biology, and it is hard for me to imagine how I could possibly break this bond. I crossed paths with exceptional academics who sowed the seeds of belief that I too, can make a significant contribution to the world. The consistent guidance and encouragement from these remarkable scientists were truly transformative, and for that, I am eternally grateful.
 
You might wonder, how does someone who just stumbled upon his interest in science end up pursuing a PhD? The answer is simple: luck and privilege. Yes, I was dedicated, hardworking, and increasingly captivated by my field, but so are many others. I was not working harder or smarter, nor was I more talented. Most of my opportunities came from being at the right place at the right time, meeting the right people.
 
Towards the end of my undergraduate degree, I faced a daunting uncertainty about my future. My understanding of research was obscure as I was a first-generation scientist, and a PhD seemed an insurmountable challenge. Yet I was pushed to explore this option. The turning point came when I was offered an internship with Marlene Goubault, an associate professor at the University of Tours. This experience sparked a passion for research, and fully re-ignited my genuine interest in Biology.
 
Upon this realisation, I recognised that a master’s degree and a PhD were my next steps. I pursued a master’s program at the same University, and I genuinely loved every second of it. This degree led me back to working alongside Marlene and her PhD student, Anthony Mathiron. During this time, I met a visiting professor from the University of Alabama, who happened to be Anthony's PhD co-supervisor, Ryan Earley. After a few beers at a pub and some good laughs, Ryan invited me to work with him. I was thrilled, but there was a hick. How could I possibly afford moving to the other side of the world for 6 months, with no income? Luck and privilege were again on my side. A bank agreed to lend me a loan, and Ryan pressured his university to pay me a small, yet life-changing, compensation. The stars aligned, and I was ready for more research.

This certainly wasn't easy, however. My English proficiency was not great, and I had to run a research project, supervise undergraduate students, write, and build a social life in a new language. Yet I was privileged enough to have lived in a country where English is taught from a young age. I cannot imagine having to face these challenges with little to no understanding of English - it was already hard enough. Despite the challenges, Ryan’s continual support was my beacon of light. Thank you, Ryan.
 
After this internship, I had no doubts I wanted to do a PhD. I was lucky to stumble upon an advertisement for a PhD program in the I-DEEL lab with Shinichi Nakagawa. To be honest, I was not too familiar with meta-analyses, nor was I too familiar with Shinichi's work. However, I was armed with curiosity and eagerness to learn. I applied, although I had little confidence in the outcome. To my surprise, Shinichi shortlisted me, I believe, thanks to recommendations from my previous supervisors. In parallel, I also tried for an RTP scholarship at the University of Sydney, only to soon realise I had little chances because my university wasn’t ranked highly enough. I was encouraged to apply regardless, but doubts clouded my hopes and determination. I never thought of university rankings until then, and this realisation made me doubt my chances of success for the UNSW scholarship. I felt trapped because of the university I had chosen, something now beyond my control. All I could do is wait and hope for the best.  
 
Unexpectedly, I was awarded the scholarship at UNSW, which filled me with happiness, excitement, and above all, gratitude. Shinichi gifted his energy and skills to put the odds in my favour. He devoted hours to ensure my application was competitive. I was also lucky my previous research experience with Marlene and Anthony resulted in two co-authorships. It's not lost on me that numerous individuals dedicate an often-higher level of effort in other labs without receiving the same recognition. I was at the right place, and surrounded by the right people, and I recognise that many did not have this chance. Thank you, Marlene, Anthony, for being so inclusive. Thank you, Shinichi, for your help in the application and for believing in me. 
 
There I was, ready to embark on my PhD journey in Sydney, yet financial constraints surfaced again. I had to buy a ticket to Australia, cover visa fees, and pay for an overseas student help cover upfront. I did not have this money. Though, I was lucky enough to be financially supported by my father to follow this journey.
 
My luck stretches further. My supervisors, Shinichi and Szymek, proved to be extraordinary individuals, far removed from the horror stories of negligent or abusive mentors. Thank you both for your dedication and empathy. Another turn of good fortune was being granted a generous scholarship, which allowed me to focus solely on my research without having to juggle additional jobs. With this funding, I could organise workshops, attend professional courses, and go to conferences without applying for extra funding. I could also do most of my work remotely, which was a huge privilege when covid hit. Therefore, it is no surprise that I had more time to focus on my research and be productive. Frankly, I believe such an exclusive scholarship should not exist - all PhD students deserve these privileges. We all deserve a living wage.
 
Reflecting on my journey, the evident narrative is not of an individual striving against odds, but rather a story of privileges and supportive networks. The cascading series of fortunate circumstances stemming from my French upbringing, the right connections, and sheer luck, guided my trajectory. If anything deviated along this path, I would not be here telling this story. 
 
Comparing my journey to my Congolese half-brother, Roderick, illuminates these privileges in action. Despite working harder than I ever did, Roderick never achieved financial stability due to his background and lack of opportunities. None of my experiences compare or outweigh the struggles others with less privileged backgrounds face. Roderick is one of the most dedicated people I know and is sacrificing nearly everything to live from his passion, animation. If he had decided to follow an academic path, I am convinced he wouldn't have made it - even if he worked orders of magnitude harder than any other students. Perhaps I should ask, how many Congolese academics do you know? Do you think there aren't many because of a lack of abilities, or a lack of privileges and opportunities? 
 
Perhaps the take home message here is to recognize privilege. Academic expectations must be recalibrated to account for individual circumstances rather than a sole focus on university rankings, prestige, and research output. True achievements are only understood when viewed through the lens of privilege. I hope for a future where equal opportunities are extended to all, irrespective of their background. For this change to happen, we require a collective change in perspective, a genuine understanding of the myriad of challenges individuals face. I firmly believe in equity over equality, a sentiment I hope we can achieve in Academia and beyond.

Generative AI technologies like OpenAI's ChatGPT and Google's Bard have taken the world by storm since the end of 2022. These tools have transformed the way we approach many tasks, from your weekly shopping trip to drafting academic manuscripts. Generative AI has the potential to democratize knowledge for budding scientists by bridging knowledge gaps and enhancing language translation. 
​
As science explores this new frontier, it is evident that generative AI is revolutionizing not only scientific manuscript writing but also the way we think of authorship and integrity of scientific research. Along with the endless implementations of these powerful tools, the use of Generative AI in science poses novel ethical and practical challenges. For instance, how do scientists with dealing with sensitive data use AI? How can science prevent the potential misuse of AI to generate misleading information or potentially data fabrication?

The rapid emergence of generative AI has sparked debate within the scientific community, as to how and if we should use these tools in academia. This issue has left many scientific journals in a quandary about how to regulate the use of generative AI in their publications. Whilst at this uncertain time it is difficult to predict the correct approach as to how to regulate the use of Generative AI. Some Journals have implemented policies requiring authors to disclose their use of generative AI and to take responsibility for the accuracy of the content they generate. For instance, Water Research has stated “Where authors use generative artificial intelligence (AI) and AI-assisted technologies in the writing process, authors should only use these technologies to improve readability and language”. And they have asked authors to provide a declaration of generative AI in scientific writing with all articles who have used it, for example:
 
Declaration of Generative AI and AI-assisted technologies in the writing process
During the preparation of this work, the authors used GPT 4.0 and GPT 3.5 created by OpenAI, and Bard by Google to enhance clarity, readability, and flow of writing. After using the tools, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.
 
Moving forward, it is important that science navigates this transitional time with caution, fostering fruitful discussions across multiple disciplines. In these discussions, we must weigh the remarkable potential of generative AI in science against its possible risks to scientific integrity. Although, it is too early to say how science will ultimately regulate the use of AI, it is clear that transparent reporting is a useful way for balancing innovation and ethics. As scientists it is a collective responsibility to tame the beast of generative AI, and our actions now will define the future of AI in the scientific method.
 
And here is my declaration:

Declaration of Generative AI and AI-assisted technologies in the writing process
During the writing of this blog, the author used GPT 4.0 by OpenAI to enhance the readability and flow of the writing. The author reviewed and edited the content as needed and takes full responsibility for the content of this work.​

We earlier wrote this post to show how we can use SSH key to connect GitHub with RStudio. This post was quite popular, but I think I give up teaching how to use SSH to connect to GitHub now, as I had too much trouble with it, especially teaching the course I coordinate (Big Data in BEES). For example, to directly access GitHub via RStudio on a Mac computer, we need to have Git installed; this means one needs to also install the XCode which is a big piece of software, and not everyone’s computer has space left for it.
 
Now, I know,it is so much easier to connect to GitHub with GitHub Desktop – no SSH key required.
 
Thus, my new workflow is:

1. Create a GitHub repo on the GitHub webpage (my profile page).
2. Clone the repo my computer using GitHub Desktop to create a local folder (note that you need to log in GitHub Desktop using your GitHub username and password).
3. Open a RStudio project using this local folder.
4. Then, you can just use RStudio normally but commit, push, and pull using GitHub Desktop.

 
In RStudio, it was not so easy to resolve problems, for example when a committed file was too big to push. In GitHub Desktop it is more intuitive to resolve. Also, it is easy to open the GitHub repo page via GitHub Desktop.
 
Now, I teach the above workflow at my class too and it seems students could start using GitHub and RStudio together quite smoothly via GitHub Desktop!
 
Here is a good YouTube video more on Git, GitHub and GitHub Desktop (note this video dooes not use RStudio but it is still useful to watch).

​ by Pietro Pollo
​

Following the last I-DEEL blog post (by Samantha), I’d like to continue the conversation about biases we see in academia (and elsewhere). I am glad to see this issue getting attention, especially because discrimination hits too close to home. I am even happier that I am part of a lab that is particularly open to this conversation, discussing what we can do through equity, diversity, and inclusion initiatives. Fostering an environment in which everyone feels comfortable is, after all, vital. However, is it enough to ensure our workplace is a safe place for all, if not all can get here?

Academia is full of people studying or working in a country they were not born or raised in. Australia is similar, as around half of its citizens’ parents were born elsewhere, making it a place filled with distinct cultures. However, the diversity in academia and in Australia ends up being superficial: the more powerful a position is (socially and professionally), the more likely it is to be filled by people of a certain phenotype and background (e.g. cis heterosexual white men from rich countries). This is a pattern seen everywhere, including in the country where I’m from (Brazil). This, in my opinion, ends up being the true root of the problem. Is there anything we can do about it?

First, research centres, universities, and PIs hold substantial power as they are responsible for hiring and recruiting new professors, researchers, and postgraduate students. Instead of relying on “objective” metrics (e.g. number of papers, journal impact factor, university rankings) to award those that have “done more/better”, they could consider candidates’ diverse backgrounds (in a meaningful and positive way). The metrics currently used to assess performance are not only problematic on their own (do they really reflect advances in science?), but they are also related to one’s phenotype and background for multiple reasons. Being born in a non-English-speaking country already represents a major constraint to people’s productivity, as they first need to dominate the language before being able to read the literature and write their research manuscripts. Thus, creating new ways to assess academics’ journeys that minimises bias is essential to build a diversity community.

Junior scientists are not exempt from responsibility either. Biases can occur when networking or reviewing manuscripts, even if unconscious. For instance, Fox et al. (2023) performed randomised trials in which they compared single- and double-blind reviews (i.e. reviewers did or didn’t have access to author information, respectively) in the journal Functional Ecology, showing that authors from developed countries received better review scores in single-blind reviews than in double-blind reviews. In other words, authors from rich countries were favoured by reviewers when their information was disclosed. Fox et al. (2023) also showed that editors, who can always see the authors’ information, sent manuscripts from developed countries’ authors for review much more often than manuscripts from others. These results were not because of language differences, as authors from both English-speaking and non-English-speaking developed countries were equally favoured. This means that even individuals with less power can perpetuate — or break — cycles of biased decisions.

Promoting diversity is a difficult task: there is no magical solution for the bias we see in academia. However, it is imperative to improve the current situation. I do not believe it should be a contest about who deserves more pity, but I also do not think we should ignore the barriers imposed on minorities and the clear advantages given to already privileged groups. It might seem unfair to deviate from a “pure meritocratic system” to seek alternatives, but meritocracy is an illusion when society is so unequal. If all of us could have the same opportunities that a rich, white British man like Charles Darwin had, perhaps more of us could advance science as much as he did.
 
References:
Fox, C.W., Meyer, J. & Aimé, E. (2023). Double-blind peer review affects reviewer ratings and editor decisions at an ecology journal. Functional Ecology, 1–14.
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This Women’s History Month, a friend asked me to contribute an audio recording about being a woman for a podcast. Anastasia Shavrova runs the podcast Conversations with Chordates (aka Convos with Chordates). Chordates is one of many science podcasts that I recommend to people looking for a new podcast, but Chordates has a much more relaxed and chatty style and sometimes delves into topics that are more tangentially related to science.

I’m incredibly honoured to contribute to this podcast alongside many amazing women. Please check out the episode Convos with Women.

Women’s history is incredibly interesting and integral to the growth of countries and society as a whole. However, like many minorities, much of women’s history has been left out from general historical education. I-DEEL is committed to open and transparent science though transparency shouldn’t be limited to science. I wanted to use my audio recording to highlight some of these moments in history to bring them back into the narrative. Please check out a blog post on my website that goes into this history in more detail.

This Women’s History Month, please take a moment to think about the transparency of women’s influence on the development of the world. In particular, consider the records (or lack thereof) of women’s involvement in science both historically and currently. Many women were not recognized as they should have for their involvement in scientific developments. See this list of the untold stories of women in STEM and the Netflix documentary Picture a Scientist.

I-DEEL has recently updated our policies around Equity, Diversity, and Inclusion initiatives to better our support for each other within the lab, as it’s incredibly difficult to separate one’s identities from their work. We encourage others to do similarly. Acknowledging differences marks the first step to equality (such as Scripps Institute publishing an internal review on gender disparities in lab space).

Happy Women’s History Month, and thank you to all the women who’ve advanced science to what it is today.
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I didn't quite grasp that this was an issue until a specific Wednesday during my PhD. Several hours into a lab meeting, I had to leave “early” to go to my varsity wrestling practice. I delayed going for as long as I could, but finally at 5 pm, already late, I had to go otherwise I would miss practice entirely. A lab-mate turned to me and very loudly said to the room how inappropriate it was that I was not prioritizing my graduate studies over all else. I still left the meeting, but their remark highlighted a sentiment[1] we don’t discourage often enough…