@mcaleerp I guess you can also give feedback to colleagues to improve on assessments! Course assessment groups are a great place to do that
@mcaleerp I enjoy marking certain assessments, hate marking others.
It mostly depends on the assessment, there's a lot of badly designed ones around unfortunately.
Big thanks to all who contributed to these initial guidelines, including the helpful reviewers and editors!
@gringene ooohhh I remember dismembering an old toy to get the motor out. Lots of fun! I was using it with Meccano rather than Lego though.
I also remember that at the time it sounded like the most interesting thing to do what's connecting the motor to the mains. I am sure your kids will be wiser, that didn't end well for the motor, although I had a nice pyrotechnics show in my room
@nancylwayne @Frederik_Borgesius I think the main problem is not that there are people cheating. It's that universities don't do anything about them, and it's not just when they are 'big' scientists (well, they enabled them to become directors or what not)
Having seen a couple of cases of this, my impression is that the policy of many universities is to cover their assess and not do anything about 'problematic' employees, whether they falsify data, or harass others. It doesn't make sense, because I'd rather work for a uni that said 'we made a mistake hiring X, we will not support this person or their science anymore'. But apparently that's bad PR. 😭
‘According to the Retraction Watch database, the 200 authors with the most retractions account for over a quarter of all 19,000 retractions. Many of the most prolific fraudsters are senior scientists at big universities or hospitals.’
https://web.archive.org/web/20230222193709/https://www.economist.com/science-and-technology/2023/02/22/there-is-a-worrying-amount-of-fraud-in-medical-research
#fraud #science #academia
Check out our new commentary piece in @NatureEcoEvo - Better incentives are needed to reward academic software development rdcu.be/c6uMN software is critical for synthesizing & modeling big data in ecology and evolution … but current incentive structures are lacking
Ok, so there is much discussion about the alt text on pictures. My mom is legally blind. As she has gotten older her sight is almost gone. She LIVES on the computer and to say she gets excited when special attention is paid for the blind is a great understatement. Please use alt text and describe the pictures you post. Describe it as if you had your eyes closed and the only link to the outside world is what a kind soul took an extra 5 minutes to type. Come on, do it, make someone’s day.#AltText
How are different scientific fields related, from a bibliometric point of view? Who writes longer papers? Uses more references? More recent references? In which fields does author position matter? Data for 20 years, all of Web of Science here:
https://doi.org/10.1162/qss_a_00246
Underlying, de-identified data can be found here: https://doi.org/10.5281/zenodo.7573523
Okay, it's been a while since I last did this, and I haven't done it on mastodon yet, so I'm going to take a deep dive into p-values for another automated GWAS. Specifically, this one, relating to "Eosinophil percentage":
https://twitter.com/SbotGwa/status/1622218396661071874
I'm interested in this particular set of results because the p-values are impossibly large, with dozens of impossibly-large p-value peaks throughout the genome.
Also, the heritability of 0.22 is within the realm of possibility for finding true links.
@ct_bergstrom Not sure what's this rant about. Nobody ever said decoder models are perfect or will have an actual understanding of the world. (Ok, maybe except for that one Google guy) OpenAI released a beta product which is incredibly helpful if used correctly but people like you just focus on its mistakes. It's like hating on cars because they can't take the stairs.
@ct_bergstrom The LLM isn't bullshitting, because it's just a machine. It has no intentionality and no mind.
The engineers and execs at tech companies who are leveraging LLMs: they are bullshitting. It's an act of malice and should be treated as such.
@ct_bergstrom Disagree. They're designed to mimic what a human would write. If they end up bullshitting it's because the models aren't good enough, not because that's what they're designed to do.
Have you got data and not sure where to deposit? Look at the helpful table by @CiminiLab for image archives.
#imageAnalysis #microscopy #openScience
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RT @CiminiLab
@Romain_BioImage I recently generated this table, if it helps! I think the BioimageArchive would be good for images
https://twitter.com/CiminiLab/status/1616508224571641856
@giladfeldman Do you know #pubpeer ? https://pubpeer.com/
It's not quite what you are talking about but I think it goes in the right direction. There is also a handy Chrome plugin to link to comments on PubPeer on pages that cite papers.
@giladfeldman I think we should, indeed. I find that reading reviews (in those journals that share them) often gives you a different view on the article.
Senior lecturer at ZJE and Edinburgh university.
I teach #imageanalysis & #dataanalysis with #RStats & #python. I study #heterogeneity in #pituitary (and other) cells.