A debate on where America was before Trump. Were we really in decline?

[Babale]

@DemonTree

“The interpretation starts from the idea that scientists have to achieve a higher number of citations. I think that is not a good starting point,” she says. “The idea that the goal of mentorship is to maximize the impact of citations later in a protégé’s career is a very shaky target.”

The study was fine, it was only the interpretation they made of the results that was dubious. But people made unfair criticisms of the methodology anyway out of a desire to discredit it. That’s not the right way to do science.

Here are the methodology criticisms from your link:

Scientists have heavily criticized the study on methodological grounds as well as on the authors’ interpretations and policy recommendations. Methodologically, “the study conflates authorship with mentorship,” explains Regina Baucom, who studies plant genetics at the University of Michigan.

“Lots of coauthors do zero mentoring,” Brian Uzzi, who researches factors that affect women’s success in science and business at the Kellogg School of Management at Northwestern University, writes in an email.

The study’s use of algorithms to identify gender based on names is also problematic because it can lead to mistakes, Baucom and others have pointed out.

What is “unfair” about these criticisms?

Eta: and the source of the criticism is a study that used different methodology and had different findings:

ABOVE: © ISTOCK.COM, MORSA IMAGES

Update (December 21): The authors retracted the paper today after three experts reviewed the study post-publication and agreed with criticisms about the use of coauthorship as a proxy for mentorship. “Although we believe that all the key findings of the paper with regards to co-authorship between junior and senior researchers are still valid, given the issues identified by reviewers about the validation of key measures, we have concluded that the most appropriate course of action is to retract the Article,” the authors write in the retraction notice, adding that they regret the pain the paper caused among members of the scientific community.

Astudy published in Nature Communications November 17 has caused an eruption of outrage among scientists. The study of 3 million mentor-protégé pairs in STEM found that women trainees who coauthored papers with senior women scientists received fewer citations after they became principal investigators than did women trainees who coauthored with senior men. That gendered pattern is consistent with previous research documenting citation biases in science. But what caused a firehose of criticism was the conclusion of the paper, in which the authors suggest that the solution to this disparity is that women should avoid female mentors, thus perpetuating an existing bias.

“Instead of coming to the conclusion that their data shows the system is biased, they come to the conclusion that women shouldn’t be mentors, which is blaming individuals as opposed to blaming a broken system. That’s why I think it’s so harmful,” says Rebecca Barnes, a geoscientist at Colorado College and co-PI of a National Science Foundation grant that supports a mentoring program for women in her field. Barnes and her colleagues published a 2020 study showing that exposure to women role models increases the likelihood that women trainees will be retained in geosciences.

For the Nature Communications study, researchers analyzed a dataset of 215 million scientists and 222 million papers. They used a computer program to infer the gender of scientists based on their names and designated them as junior or senior scientists (junior scientists were defined as scientists in the first seven years since their first academic publication; senior scientists were beyond that). Mentorship was defined by authorship patterns: when a junior scientist coauthored a paper with a senior scientist, the senior scientist was considered a mentor. In this way, the researchers identified 3 million unique mentor-protégé pairs spanning more than a century.

The idea that the goal of mentorship is to maximize the impact of citations later in a protégé’s career is a very shaky target.

—Roberta Sinatra, IT University of Copenhagen

To probe whether these authorship patterns were a good measure of mentorship, the researchers also sent a survey to 2,000 scientists in the dataset, 167 of whom responded, that confirmed these authorship patterns involved some form of mentorship.

The researchers then measured the standing of mentors by their average number of citations per year before their first publication with the protégé. Highly cited mentors were called “big shot” mentors by the paper’s authors. The researchers also calculated the degree to which the mentor was integrated within networks of scientific collaborations (that is, how much of a “hub” each mentor is in a collaboration network). The mentorship outcome was measured as the number of citations of the protégé’s publications published beyond the first seven years of their career and without their mentor as a coauthor.

The study’s authors found that “big shot” mentors (and “hub” mentors to a lesser degree) were associated with a greater number of citations of their protégés post-independence. The researchers also found that for all trainees, “having more female mentors is associated with a decrease in the mentorship outcome, and this decrease can reach as high as 35%,” they write in their report.

Next, the researchers examined how the mentorship relationship benefited the mentors. “The results suggest that, by mentoring female instead of male protégés, the female mentors compromise their gain from mentorship, and suffer on average a loss of 18% in citations on their mentored papers,” the researchers write. Male mentors did not see an effect on their citations related to the gender of their protégés.

Scientists have heavily criticized the study on methodological grounds as well as on the authors’ interpretations and policy recommendations. Methodologically, “the study conflates authorship with mentorship,” explains Regina Baucom, who studies plant genetics at the University of Michigan.

“Lots of coauthors do zero mentoring,” Brian Uzzi, who researches factors that affect women’s success in science and business at the Kellogg School of Management at Northwestern University, writes in an email.

Uzzi and colleagues published a paper in PNAS earlier this year about mentorship and protégé success that found no differences in the success of women scientists who had male versus female mentors. In that study, the researchers used data on mentors and protégés from the ProQuest PhD Dissertation & Thesis databank, an official record of advisor-student relationships taken from doctoral theses. They measured several aspects of protégé success, including winning a scientific prize, election to the National Academy of Sciences, and a high citation impact score. “Our paper contradicts their paper’s finding and recommendations that women scientists do better when mentored by men when a woman’s actual and known mentors are identified,” Uzzi writes in an email to The Scientist .

This is the Peer Review process and is EXACTLY how science should be done.

[DemonTree]

Did you even read my post?

Roberta Sinatra, a scholar at the IT University of Copenhagen, uses big data to study publication, citation, mentorship, and success in science. She says that the methods used in the study, although flawed, are fairly standard in this field. The lack of gender information is a limitation of the dataset, but the algorithms are about 80 percent accurate, and questions about gender bias couldn’t begin to be addressed without this approach, she says.

“Overall, it’s a very thorough and comprehensive analysis,” Sinatra says, adding that she felt some of the methodological criticisms were unfair because the approaches are fairly standard in the field known as the science of science.

And criticisms like these have no place in science:

That’s why I think it’s so harmful.

She adds that in this moment in particular, when the pandemic has amplified the structural and societal obstacles that women in science are facing, publishing this paper was a mistake.

Science is about finding out what is true, full stop.

As for the second paper, it wasn’t a study but an argument against affirmative action. It should be possible to publish that argument and lay out the evidence without risking one’s job, even if ultimately it proves not to be persuasive.

[survinga]

@octopus

There is a huge difference between polices that price folks out of the labor force and then pay folks to be idle and policies that assist with the cost of living.

With the former you have jobs go overseas or filled with illegal labor. You have folks who can’t legally get a job they qualify for but isn’t worth the legally mandated wage. You have folks who instead of being busy doing something productive and learning skills and, just as importantly, values, that would increase their economic worth sit around all day causing mischief.

But minimum wage laws have been studied and they don’t impact unemployment in the areas where they occur. Your arguments are assigning blame to minimum wage laws that’s not happening in real practice.

Research Shows Minimum Wage Increases Do Not Cause Job Loss | Business For a...

Furthermore, manufacturing jobs were never minimum wage. Many of them were union jobs or jobs that pay much higher than minimum with benefits. Those are the jobs in many cases that went overseas…or more than anything else, they were replaced by automation.

I’m in favor of policies that help maufacturing and help employment. But I don’t think getting rid of minimum wages will do either.

[Max_S]

As far as outputs, I was thinking apps like SnapChat or instagram. There’s so many pictures and videos of people making art, cooking, playing music, &etc. Most young people I know make something that they can post to social media, at the very least amateur photography. 20 years ago this would be called “scrapbooking” and it would involve blackrooms, scissors, and glue. Now almost everyone does it all the time.

And inputs would involve pretty much anything streamed, all the pictures watched, games played, books read. It’s all there at your fingertips and people are spending more and more time consuming electronic media.

It’s sort of the next step in globalization, which has always meant more cultural inputs and outputs.

~Max

[GIGObuster]

@DemonTree

As for the second paper, it wasn’t a study but an argument against affirmative action. It should be possible to publish that argument and lay out the evidence without risking one’s job, even if ultimately it proves not to be persuasive.

Sorry, it failed on both counts (as a persuasive argument and an item that in reality had no good evidence) and what follows is to be expected, one loses one’s job after showing incompetence at that level.

Of course this is incomplete for one important bit, can you do us a favor and explain who gave you that sorry talking point? I do want to know who gave you a link to that item with a spin that looked to be coming from a bigoted blog. I do want to know to whom one should complain in the proper way.

[Irishman]

@HMS_Irruncible

Nope. Re-read for comprehension.

You posted

@HMS_Irruncible

I can identify with this sentiment - let’s just lift up the people who are feeling left behind. But from everything I read, they were mostly content with their status until Obama’s election shocked them into realizing that black people might be moving up the social ladder ahead of them, leaving them on the bottom.

I just don’t know how to do an economic outreach to people whose main concern is staying out of last place but not investing any competitive effort to do so.

So
(A) you are talking about white people being shocked at black people moving ahead of them on the social ladder.
(B) you said they do not invest any competitive effort into their own main goal.

So that is (A) white people (B) being lazy. No?

[HMS_Irruncible]

@Irishman

So
(A) you are talking about white people being shocked at black people moving ahead of them on the social ladder.
(B) you said they do not invest any competitive effort into their own main goal.

So that is (A) white people (B) being lazy. No?

Nope. They may be perfectly willing to work. What they aren’t willing to do is change. They think the jobs that they’re accustomed to (say, coal mining) ought to be perfectly good-paying jobs forever. That’s not realistic. They need to adjust to the times, but instead they blame everyone else for the position they’re in.

And I’m not talking about white people as a category here. Not all white people are racially aggrieved Trump voters who expect to keep their obsolete coal-mining jobs forever. But those are the ones I’m talking about.

You’ll probably keep flogging this as “white people lazy” and I can’t stop you, but you have your answer.

[Crane]

Max,

I see your point.

Some of the discussion here has involved a value judgement of good and bad information. Isn’t that the scientific method? You publish and your peers jump all over your data, your methods and your conclusions.

So, in the context of the OP, what is the quality of the inputs and outputs on the internet. It seems to be a normal distribution centered around simple reports. The center is more like a photo album than a scrap book. But at the extremes - there it’s like a technical notebook. Magnus effect, magnetic toroids, down wind faster than the wind, pulse jets, 200 mph model steam boats, and ghosts - arcane areas of investigation that get published.

So, is the net effect of the internet that the mass of the population is absorbing better information? Are we smarter? Or has the internet allowed us to split into two populations: one of social zombies swapping photos of kids and pets and the other technology geeks fondling the fringes of science?

[DemonTree]

@Crane

So, is the net effect of the internet that the mass of the population is absorbing better information? Are we smarter? Or has the internet allowed us to split into two populations: one of social zombies swapping photos of kids and pets and the other technology geeks fondling the fringes of science?

Definitely the mass of the population is not adsorbing better information. Conspiracy theories, misinformation, and youtube algorithms that push more and more extreme videos… the people just using it to share pet pictures are probably better off on the whole.

[Babale]

@DemonTree

As for the second paper, it wasn’t a study but an argument against affirmative action. It should be possible to publish that argument and lay out the evidence without risking one’s job, even if ultimately it proves not to be persuasive

I don’t know about you, but I am an At Will employee, like the vast majority of Americans. I can be fired at any time, for any reason or for no reason at all, aside from belonging to a protected class (which is VERY difficult to prove, unless you can find an email saying “fire his black ass” or something). Anything I post politically online is ‘risking my job’.

A college professor has a lot more job security than someone in the private sector, of course. But if he espouses views that run contrary to the school’s mission, they absolutely SHOULD get rid of him. This would be like me going to prospective customers and telling them our product is crap. I’m welcome to do this of course, but I won’t continue to be employed by my current company.

And now we’re back to taking single lines out of context. Here is what you quoted:

@DemonTree

That’s why I think it’s so harmful.

@DemonTree

She adds that in this moment in particular, when the pandemic has amplified the structural and societal obstacles that women in science are facing, publishing this paper was a mistake.

Of course, if we don’t selectively quote, we see the context of the phrase:

@Babale

“Instead of coming to the conclusion that their data shows the system is biased, they come to the conclusion that women shouldn’t be mentors, which is blaming individuals as opposed to blaming a broken system. That’s why I think it’s so harmful,”

Ie what is harmful is their conclusion and the way they made it.

Your second quote is also taken out of context:

To me, the paper seems irresponsible to the point of malfeasance,” Baucom says. “The researchers didn’t have a control and a treatment group, so they can’t assess the reasons why women might not be as highly cited. To take that and say to young women, ‘You shouldn’t go work with a woman mentor’—that, to me, is malfeasance,” she says. She adds that in this moment in particular, when the pandemic has amplified the structural and societal obstacles that women in science are facing, publishing this paper was a mistake.

Again, this is a very clear criticism of the conclusion, and the methods used to draw that conclusion.

Science IS about finding the truth, which is why your methodology is so important, and why any conclusion you draw actually has to follow from evidence. Multiple people in the field pointed out that this paper had flaws that lead it conclusion to be dubious. The authors reviewed these claims, agreed with them, and retracted the paper. If they are responsible scientists, they will likely release a revised paper, where they:

1. discuss the limitations of their dataset up front
2. discuss the implications of those limitations and how they affect the context in which they draw results
3. state their conclusion (which probably will NOT be “women graduate students should choose male mentors”).

This is what responsible science looks like. Saying “hey, your data is limited in scope” is not some heinous attack; it is crucially important. For example, we do not currently give children the COVID vaccine, because there is no data on how it affects children yet. Pointing that out isn’t an attack on Moderna or Pfizer, it’s a recognition of reality.

Same thing with this study - if the gender identification algorithm is only 80% effective, that leads to some fuzziness in the results. Further, since the question is whether people take a paper more seriously based on whether the mentor names on the paper are male or female, there could very well be a correlation between ambiguous names and number of citations.

Again, this doesn’t mean we throw the paper in the trash and the authors in PC Jail. It means we check what the study actually says, and make sure THAT is what we base our conclusion on. Anything else is not science, it’s pseudoscience.

[Mijin]

@Crane

So, is the net effect of the internet that the mass of the population is absorbing better information? Are we smarter? Or has the internet allowed us to split into two populations: one of social zombies swapping photos of kids and pets and the other technology geeks fondling the fringes of science?

Unfortunately, we were a bit naive when it came to predicting the impact of the Internet. Most people predicted that having accurate information from a plethora of sources at our fingertips would essentially vanquish ignorance.

But humans are not truth collecting machines. There are various motives for watching things on the Internet. What has been created instead is an ecosystem, where ideas that have the properties of spreading most effectively, spread most effectively (yes I’m talking about memetics).

Being true is an attribute that helps an idea spread, as is being useful, which is generally the same thing. But there are other attributes that help an idea spread, such as whether it gets the watcher angry. I recommend this 7-minute video for a good summary on how memetics applies to the internet.

I am vulnerable as the next man. While I watch a lot of educational content from trusted sources, I will also sometimes watch the clickbaity “Ignorant X gets DESTROYED” videos.

[Irishman]

@HMS_Irruncible

Nope. They may be perfectly willing to work. What they aren’t willing to do is change.

Thank you for clarifying your answer.

I would point out that laziness doesn’t just apply to physical situations, but I don’t have an agenda. You answered my question about your intended meaning.

[Irishman]

@HMS_Irruncible

And I’m not talking about white people as a category here. Not all white people are racially aggrieved Trump voters who expect to keep their obsolete coal-mining jobs forever. But those are the ones I’m talking about.

I should also point out my remark was a somewhat facetious remark inverting the common stereotype those people have against black people. It’s the exact same kind of stereotyping. “So-and-so is lazy, therfore all people like So-and-so are lazy.”

[Crane]

Information also spreads when it serves a market. Information products can be manufactured to serve any want.

[HMS_Irruncible]

@Irishman

I should also point out my remark was a somewhat facetious remark inverting the common stereotype those people have against black people. It’s the exact same kind of stereotyping. “So-and-so is lazy, therfore all people like So-and-so are lazy.”

If you’re riffing off what the person actually said, it’s facetious. If you’re mischaracterizing someone and criticizing your own words, that’s just your basic strawman… which is, ironically, one of the laziest arguments there is.

But that’s what I get for responding to a post that starts with “so what you’re REALLY saying is…”

[Irishman]

Whatever. Nothing I said was meant as an attack on you. I asked you to clarify a remark. I also simultaneously attempted to point out an irony. “White people call black people lazy, but they are actually being lazy.” I thought that was obvious.

Maybe I could have tried harder to craft a wittier post that separated the two remarks.

[octopus]

Coal mining may be so-called obsolete but manufacturing, agriculture, other forms of mining, etc. are not. Having those jobs exported is not good long term, strategic policy.

[Mijin]

Manufacturing and coal mining jobs in the US generally pay far more than any conceivable minimum wage. MW is not the problem for those jobs, it’s automation.

Regarding minimum wage manufacturing jobs, I guess the US could start competing for low skill manufacturing work, like assembling iPhones (note this is a very different thing from manufacturing the components). But once again, this literally is sweatshop work with tight margins. No developed country is strategizing winning such work.

If it’s not that, what kind of work are you talking about?

[octopus]

I’m talking about we pay people to not do anything and we lose critical capacity and capability here. If, and I know this is controversial, people have different capabilities, how can those who don’t have the capability to do work such as computer programming or robotics make a living?

[Babale]

You mean like how we pay farmers not to grow crops?