Hello everyone
Regarding articles with several initial authors contributing equally, I would need your view. This makes sense in the case of interdisciplinary study, as it is impossible to accurately measure the contributions made by writers in many disciplines. But when both writers are focusing on machine learning, what good is it? What qualifies for equal contribution in this case? Are the two initial writers focusing on both implementation and experimentation, or should the math and concept be seen as equally important?
Does this decrease the success of each one of the writers when it comes for example to hire? Lastly, are you aware of instances when equal contributions have been misused, such as when colleagues have reached a “agreement” to double the publication record without really putting in the work?
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Because of the ridiculous consequences of our field’s PhD awarding process, papers with a first and last author are common, and research teams often switch first authors to ensure that everyone receives their PhD.
I believe that multiple-author equal contributions—as in the business and other academic fields where authors are listed alphabetically, for example—should be the standard in machine learning. Because working as a team produces better results than lone researchers working in their own little area of the lab.
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That’s an academia problem. Industry doesn’t really care
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It seems to me that this whole conversation is pointless since only the first author will be granted “first author privileges,” regardless of whether you provide a statement indicating “equal contribution” or not. To be honest, this is OK; very seldom does a document reflect the genuinely equal contributions of many authors.
What’s your opinion on “equal supervision” last authorships? I have seen this recently, lol.
Why would it be the norm? I have both been in the situation where I would do 90% of the work myself (mainly in academia), and in projects where dozens (close to a hundred) people would touch in different aspects of the work and the paper would somewhat contain a bit of everything.
Even in the latter, the paper is rarely completed if a single person doesn’t take the initiative to organize all data and narrative, do some extra experiments to complete the narrative, and interface the exhaustive interaction between authors and reviewers. I can’t think of a single case I am aware of where there would be truly “equal contribution”, and I have only seen something close to that in papers that come of work done by a group of students for a subject in grad school that is not 100% aligned with their main thesis work,.