And making your Doctor with emphasis on data science, has nothing todo with understanding simple data like covid-cases right?
BTW Earth science has probably more todo with data than anything else.
There’s a rationale around what is, and is not, included in case definitions and included in dashboards. It’s likely that these decisions are made by epidemiologists with not only specific training, but also access to much more data than the person who builds the dashboards.
Making a decision to include data in a visualization without understanding why is not a good idea because it’s common that people think they know what numbers mean, but only because they have limited visibility.
Having a degree in data science doesn’t mean that I’m a data scientist. If I’m hired in a web dev role, then I hope my input is received well and considered by epidemiologists in charge. And I hope they’d be able to spend time explaining the rationale behind their decisions.
This seems like a similar analogy where the build engineer decides to change the git repo because they know better than the dev team. Then someone reading the article says “well they have a PhD in computer science so they should know what they’re doing, it’s simple.”
Credentialism: belief in or reliance on academic or other formal qualifications as the best measure of a person's intelligence or ability to do a particular job
>making your Doctor with emphasis on data science, has nothing todo with understanding simple data like covid-cases right?
Plenty of employees have been let go for spreading falsities around COVID, most having been on the other side (COVID isn’t real etc). These behaviors are absolutely unacceptable and are dangerous.
In the US, that’s first or second year undergrad territory. Overseas, it’s often covered in high school.
It’s particularly depressing that science reporters regularly get these things wrong.
I can’t imagine what (lack of) credentials are necessary to land such a job, but I often wonder if a basic understanding of statistics is a disqualifying credential.
One of the most important lessons I've learned from poring over this data is that 99% of the things that internet users describe as "obvious" are not only obvious but false. A strange phenomenon, and one we all need to work on overcoming if we're to have real conversation.
For instance, most people agree it is best to exclude totally random testing sites from COVID numbers because even though the false positive rate is very low, at the beginning so was the incidence of COVID which means most of the positive tests would be false positive.
Including them or improperly dealing with that data would be considered base rate fallacy
https://en.m.wikipedia.org/wiki/Base_rate_fallacy
This is just one statistical phenomenon that has to be dealt with. It’s complicated and sometimes messy but it absolutely requires top minds
I wonder why would he say that ;)
Edit to add example : For instance, most people agree it is best to exclude totally random testing sites from COVID numbers because even though the false positive rate is very low, at the beginning so was the incidence of COVID which means most of the positive tests would be false positive.
Including them or improperly dealing with that data would be considered base rate fallacy
https://en.m.wikipedia.org/wiki/Base_rate_fallacy
This is just one statistical phenomenon that has to be dealt with. It’s complicated and sometimes messy but it absolutely requires top minds
Please review https://news.ycombinator.com/newsguidelines.html and stick to the rules from now on.
Moreover, she is repeatedly referred to in the press as a data scientist, but all accounts of her actual work are that of a dashboard developer. Having done both myself, I can attest that they are very different types of work warranting very different training.
Literally all of her research involved gathering and communicating relevant insights from vast and disparate data sets, which is the role you just described.
> Having done both myself, I can attest that they are very different types of work warranting very different training.
She's educated as a data scientist specific to a given field. No different than a rocket scientist running numbers at a hedge fund. And I'd argue training v. education are vastly different; education gives context to job-specific training.
Pedantically pointing out that, literally, this is a false statement.
It’s ok to accurately reflect her work and that advanced degrees are hard without assigning incorrect and hyperbolic characteristics.
My statement is so generic as to be true in the context of fields involving scientific research. And that's in essence the point: that's what data science is in the end.
This isn't an attempt to incense those with Data Scientist in their job title or job description, but it's why so many STEM folks can easily find homes in Data Science without formal education on the topic.
Also, data science is a sort of generic term and trying to generalize to any form of common characteristics is not very productive. I’m not aware of any certified curricula for data science or accreditation bodies so it’s kind of a marketing label assigned to everything from boot camps to GIS programs.
I think this is positive since lots of people work with data. But it’s problematic to assume that it means anything other than someone wants to signal that they work with data.
But that is, in fact, the definition of research ("the systematic investigation into and study of materials and sources in order to establish facts and reach new conclusions") and the publication of research findings fits the definition of communication.
I guess my point is: if you're going to be pedantic on the internet, you should consider whether it's worth your time defending your own contribution. I've got no qualms defending the idea that Rebekah Jones is a data scientist.
> [data scientist] is the role you just described.
No. She's not a data scientist and she herself doesn't even make this claim [1] Her job titles were: 1) GIS Analyst and 2) Geographic Information Systems Manager. Both are systems/dev roles. Clearly, neither is a position from which one is qualified to contravene the WHO.
Her degrees (per her own LinkedIn page) are in Geography. Take a look at the degree requirements at Syracuse (which offers both a BA and a BS (Jones earned the BA option)) [2] and LSU [3]. Next, go look at a few DS job postings and tell me the requirements are aligned (they are not).
I'm sure Jones is smart. I'm sure Jones is well versed in Geography. But she's not a data scientist. Even if she were, her skills and experience would not qualify her to overrule WHO guidance.
[1] https://www.linkedin.com/in/stormjones/ [2] http://coursecatalog.syr.edu/preview_program.php?catoid=3&po... [3] https://lsu.edu/ga/programs/msgeography.php
You know what GIS means? Geo INFORMATION System....Analyst.
Not many other Fields produces more Data then geo...maybe Weather...that's more complicated data (and hard to interpret) as most people who claim the title Data Scientist will ever see.
>But she's not a data scientist.
Stop with that it's no even a real job, it's a base training. Do you really think a Data Scientist has any plan what Cern Data s even mean...no.
"My Experts™ are more Experts™ than your Experts™"
Not a single person in this thread as actually made any factual statements or presented any actual evidence of either sides correctness or validity.
It simply "She has these degree;s so we should listens" vs "The WHO Says...."
It would be amusing if it was not so sad...
Nevertheless, Ms. Jones was paid as a web developer by the state, not as a data scientist, and if she was publishing data she thought was important at the expense of data the state's paid data-scientists thought were important, she had to be fired.
What if Ms. Jones was taking advantage of her position as a web developer and publishing her work as a hobbyist data scientist that showed masks are ineffective at the expense of the data science work of official state data scientists who were saying they are likely to be helpful? I'd still consider her a data scientist, I just would want the state to be able to fire her.
Then we just hope you Surgeon is not like that, and has at least a degree in Medicine.
1) People on HN say the person isn't educated, so you link her degrees in varying fields (not statistics or epidemiology).
2) People on HN say that those fields are irrelevant to her work, so you explain their relevance to the field of statistics.
3) People say on HN that credentials don't matter as long as you're doing the work of a data scientist, at which point you declare the importance of a relevant degree to the field.
So, which is it that draws importance? The college-level education of any kind, or the credentials that establish the doctor?
I find your opinions to be largely at-odds with one another.
Personally : I don't care at all about credentials if the quality is there. With regards to this specific case, i'll wait until the facts are in -- but it rubs me the wrong way that authorities don't want to speak of her charges even though she's available and willing to cooperate from what I read in the article.
P.S. I share your pain with those that edit comments in a dishonest way post-reply. It's a real problem on HN.
-I just said that she is probably perfectly capable of interpreting simple data.
-That you don't have to be a "data scientist" to understand simple data.
-Data Scientist is not a real Job but a base training (learn tooling and a bit statistic)
-A Mathematician/statistician/scientific-programmer has probably more of a clue what data's and statistics are and how to interpret them then any "based trained data-scientist".
-If it's so complicated you would need a specialized covid-data-scientist/mathematician, but it's NOT....compared to let's say, what Surgeons do...hence the degree in Medicine, with specialization on surgery.
I did not say she's wrong or right, but to say that someone has no clue because he/she is not even specialized in "fill in occupation" or employed as "fill in occupation" is just plain wrong, and shuts down every other opinion.
Just look for a example at Apollo 1, a fireman or chemist would have probably said: WHAT! filling the Cabin with pure oxygen is a terrible idea!!
But he's/she is not a Astronaut, Doctor or Rocket Scientist. With the logic here, he's maybe capable of understanding rocket-fuel or how to put out fires, but has no clue of humans and what they need in space...and he's not even employed as Human-equipment-specialist.
>>received a dual master's degree in geography and mass communication
>>where she completed course work with an emphasis on data science and was working on a doctoral dissertation titled Using Native American Sitescapes to Extend the North American Paleotempestological Record Through Coupled Remote Sensing and Climatological Analysis
https://en.wikipedia.org/wiki/Rebekah_Jones
...Just a Webdeveloper