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Why doesn't arXiv have a comment section?
One of the main criticism against arXiv is that while there is some basic filtering, but there is no scientific review of the papers. I wonder whether adding a comment section has already being discussed publicly and why as of now arXiv does not have a comment section.

Probably because it would be hard to filter out all the loonies who do "theoretical physics" as a hobby, know how to prove that P != NP, have their own theory of everything, etc.  Comments would quickly degenerate to the level of what you could find in physics newsgroups on USENET (when it was still popular).  Most people commenting wouldn't be those who actually understand what the paper is about.

Short answer: the people who run arXiv don't have the time, money, or appetite. But there are some efforts by other people to implement something like this. Have you seen this? https://selectedpapers.net/

@ArtiePrendergast-Smith: Another is http://pubpeer.com.

Go to http://harvardmagazine.com/2003/07/who-built-the-pyramids-html. Look at the comments. Do you still want to see comments on arXiv?

@rumtscho Obviously comments would be somehow moderated, and maybe not anonymous, amongst other thrash filters.

This question appears to be off-topic because it is about ArXiv's policies and features, not academia.

@DavidRicherby I suggest you explore the arxiv tag.

There is a browser extension to store and view arXiv comments at https://fermatslibrary.com/librarian .
I have also suggested to arXiv that they include an optional link to submit feedback to the authors of papers. The authors could enable and disable the link themselves.

@Szabolcs Disagree. For all types of academic publications, including but not limiting to articles, comments, and correspondence, anyone has to attach his name with it. It is easy to detect trolls.

Isn’t this solved by requiring some kind of threshold or approval from the inner circle for permission to comment? And for those that are out of the mainstream creating a pay to play option so cranks can feel free to crank out if they donate $1000 a year to science. Then everybody wins and comments can be as open as possible without being a net disruption to science.

http://www.nature.com/news/arxiv-preprint-server-plans-multimillion-dollar-overhaul-1.20181 (published on 29 June 2016) has some interesting statistics on whether users want a comment section:

When asked whether arXiv should embark on more transformational
changes, respondents gave mixed answers. In particular, some questions
focused on whether it should develop into a social forum that allows
scientists to comment on papers or leave ratings. A few social-media
sites have already been built around the repository for just such
purposes — such as SciRate and Arxiv Sanity Preserver — and some argue
that the site itself should begin to incorporate such functionalities.
“ArXiv should be more dynamic — allowing readers to filter the wheat
from the chaff,” says Alán Aspuru-Guzik, a quantum chemist at Harvard
University in Cambridge, Massachusetts. But one-third of respondents
said that this wasn’t important or that arXiv shouldn’t be doing it.
Only 34% voted in favour of such changes.
That response points to a tension between researchers who want to see
the site incorporate aspects of open review, and those who want it to
stick to its core mission of allowing rapid exchange of scholarly
papers, says Rieger. There were hints of a generational divide, with
those aged under 30 more in favour of allowing comments. But even
those who wanted a more social site said that they were keen to avoid
a commenting free-for-all, Rieger adds.
“The message was more or less ‘stay focused on the basic dissemination
task, and don’t get distracted by getting overextended or going
commercial’,” says Paul Ginsparg, a physicist at Cornell University
who launched arXiv in 1991 as a pre-World-Wide-Web-era bulletin board.

Interestingly, bioRxiv does have a comment section, e.g. from https://www.biorxiv.org/content/10.1101/332825v2:

Similarly, Hugging Face allows users to comments on arXiv papers e.g. https://huggingface.co/papers/2309.09400:

There was some study on the usage of the biorxiv comment section after covid-19:https://www.biorxiv.org/content/10.1101/2020.05.22.111294v1.full

Is mikelabs an AI?

Comment systems cost money to develop and moderate.
Some people may not want their preprint commented on.
You can comment by submitting your own preprint.
Third-party sites provide this service.
Journals do not not have comment sections on their websites.
I doubt many people are asking for a comment section.

Do you have any evidence for your claims? Especially the last one.

@alizter People seldom create evidence detailing why they don't do something. Any answers here are likely to be pure conjecture, unless somebody from arXiv comes and says "We discussed it and decided against it because X", or we happen to find a record of one of them saying such a thing.

@Alizter No, it's opinion.  As is most of the stuff on this site.  If you want facts about ArXiv go ask them. http://arxiv.org/help/contact

Regarding your last point: Reference on the authors' willingness to receive public, online feedback on their work.

@Najib I only wanted to know the justification for the points. Whether they are from arXiv or purely skeptical. Sorry if this was a bit of a strange thing to ask but as a user of this site I wanted to know a bit more about what I was reading.

@AnonymousPhysicist Wong! both Nature and Science, the two big academic journals, do have the web-comment section.

The idea of adding comments in some form (not 'on the arXiv' directly) has had some public discussion. See Tim Gower's blog post Why I've also joined the good guys. Sadly I've seen very little of the idea since, so I don't know what the current state-of-play is.

It's been a while since this post, but this idea is now available at https://alphaxiv.org/
This is a Stanford site that allows you to search for and add comments to any arxiv document. I am not affiliated in any way with the website.
Most submissions have 0 comments right now, but open a famous paper like “Attention is all you need” for a proper demonstration

Thanks! Huggingface is doing that too eg  https://huggingface.co/papers/2309.09400 If arXiv doesn't want to support comments, people will just use other platforms.

Do you have an association with this website? https://academia.stackexchange.com/help/promotion

In fact, after some investigation, I'm unable to figure out any site owner. There's no About page. The site uses a Stanford logo in a way that implies affiliation, but does not appear to be registered by them. The site's JavaScript has been run through a typical obfuscation algorithm and serves all the site's content. Is there a reason to trust this site?

@user176372 According to a post on LinkedIn, the connection appears to be that the site was at least created by Stanford students.

Hi! Could you please add more details about the website to make this answer more complete? For example, including any information about the maintainers would be appreciated.

I am not affiliated in any way with the website. I don’t have any more information on who owns it past what the website already says

There is no need for a comment section. The authors have provided their contact information, so you can email them directly with any feedback you have for them.
PLOS has comments, though: http://www.plosone.org/static/commentGuidelines.
When they're used, they don't generate much discussion, so maybe arXiv has guessed right about the user demand for them. http://www.plosone.org/article/comments/info%3Adoi%2F10.1371%2Fjournal.pone.0105948

Readers can benefit from other readers' comments.

@FranckDernoncourt True. But perhaps arXiv just doesn't include that in its problem scope. It's focussed on authors, and their work.

@FranckDernoncourt But, maybe I'm making assumptions about why you would like a comment section. What would you use it for?

Ask for clarifications, point to other related work, miscellaneous questions, etc. (such a a comment section could be organized into categories by the way). But beyond personal points of view I was mostly curious to know whether the arXiv team had made their views public about that matter. (by the way, thanks for the interesting links!)

Make clarifications and point out errors in the paper or things that are misleading or misguided would be of great benefit to other readers.


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Are there any journals or conferences that take into account the availability of the source code when selecting the papers to publish?
Quite too many times I have read in a research article claiming that the source code will be made available, and, when I look for it, it turns out that the source code still hasn't been released.
Are there any journals or conferences that take into account the availability of the source code when selecting the papers to publish? By availability I mean present availability, not some vague promise of code release sometime in the future somewhere on Internet.
Now code availability is one thing, clarity is another. I have seen a lot of emphasis on the papers' clarity in the paper selection criteria, do some publication venues pay attention to code clarity during the paper selection process?
Obviously, I have the same issue with datasets, so I am wondering the same for them, i.e. are there any journals or conferences that take into account the availability of the dataset(s) when selecting the papers to publish?

(If the question contains too many subquestions, let me know and I'll split it.)

What is your field? And to answer your question, yes, there are journals that to my understanding ask you to submit the source code as supplementary material. These often have "Computational" in their title. A quick Google search returned Computer Physics Communications (published by Elsevier). I am not personally very familiar with the journal but they write that "Manuscripts that describe computer programs and NVAs must be accompanied by: the program source code ...". PLoS One recently, as I recall, made headlines by making it an editorial policy that access to datasets be guaranteed.

@amirg: I'd put that as an answer if I were you!

I can confirm the answer given by amlrg in comments. I have recently published a paper in Computer Physics Communications and the referees pay significant attention to the code. There was no requirement, however, to upload the code as Supplementary Material with the paper — the referees were happy to consider our public github repository. It was probably the first time in my practice when referees have actually bother themselves to reproduce the results claimed. We had a number of comments regarding the clarity of the run files in the code (but not in the rest of it), and even a suggestion on design.

There exist at least one journal, Ipol, where it is mandatory to provide the source-code related to the paper. In fact, they raise the bar much higher: the authors must implement the code in a given language, so that the algorithm is available for experimentation on line. You can actually test and try the algorithms of all published papers right now, in a few clicks.
It is a specialized journal in image processing, but it could (should) inspire other fields to do the same.

That's phenomenal... it would be great for computing conferences to have online experimentation like that.

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/

sort: votes


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How much does it cost the publisher to publish a book?
I wonder how much it costs a publisher to publish a book (textbook or research book).
I'm looking for referenced numbers, not guesses. I am mostly interested in the fields of computer science and maths, and English-speaking venues, but I am curious about other fields and languages as well.

I am not an expert here, but I suspect that the only reasonably succinct general answer will be "It depends."  At one extreme there are print on demand publishing companies which are set up to print N copies of any text so long as you will buy N copies, and you would have to think that their cost is less than or equal to the price you pay for those N copies, thus for instance probably $100 or less in some cases.  At the other extreme publishers of a new edition of a best-selling textbook will pay whatever they think will net them more money, so surely more than $100K in some cases.

@PeteL.Clark Sure, I'm ok with a distribution, or a dataset containing several samples.

So you want as an answer a statistical analysis of how much publishers spend on textbooks?  This seems too ambitious for someone to make on demand, but perhaps it already exists in the literature.

@PeteL.Clark Ideally, yes, as I suspect like you that there is some variance.

Hmm, maybe I misunderstood the question.  I was interpreting "a book" as a product being sold by the publisher.  Based on the answer, it seems that it means "each copy of a book."

@Pete L. Clark  One of my math books, paperback, 250 pages, B&W, 8.5 x 11, LaTeXed, is sold by Lulu for $9.54 plus shipping. I am not collecting royalties and Lulu had suggested a price around $20. All this to suggest that the prices currently charged by the few remaining, BIG, publishers have absolutely nothing to do with their costs, even including marketing.

@schremmer: I'm not sure exactly why you made your remark.  I certainly agree with the sentiment behind it.  But you say that prices have "absolutely nothing" to do with costs.  I don't believe you: for big publishers, I am very confident that their prices are greater than or equal to their costs!

By the way, the above comment is mostly pedantic.  (Like many mathematicians, I am not only really good at being pedantic when I want to be, I have also been heavily conditioned to want to be.)  So I wanted to make sure to add: it's really great that you are making math texts available online which are literally free and also making them available for print at cost.  That's what everyone should be doing.  Congratulations.

@BenCrowell Thanks for your comment. I'm interested in all types of costs. If that's too much for one question I can ask several ones. I don't have any preference.

Sorry, but I can't imagine how a well formed answer could look like. Do you think that there is a well formed answer to the question "How much does it cost a company to develop a car/smart phone/cupboard?"

@Dirk Yes, e.g. to manufacture a phone: http://spectrum.ieee.org/static/interactive-apples-and-samsungs-changing-smartphone-recipes

OK, manufacturing is something completely different from developing. For a publisher it is also completely different to print and ship a book or to develop a program and publish the book.

@Dirk Sure, Ben mentioned that earlier, see my reply.

@PeteL.Clark There was no need to  "add" but I disagree: one just does what one thinks one ought/can afford to do. As for my comment, I did not intend to suggest that textbooks should cost around $10 but that, given the low cost of even color printing, I cannot see, as apparently you can, what could account for $200 books when they were LaTeXed by the author as is by now very often the case, if not the norm.

@schremmer: " I cannot see, as apparently you can, what could account for $200 books" Clearly my comments have not been understood: this is the exact opposite of the position I hold.

@PeteL.Clark You are entirely correct: I mentally interchanged costs and prices in your "I am very confident that their prices are greater than or equal to their costs!". I think, perhaps, because of the "equal". In any case, very sorry about that, if  only because I strongly dislike those who rebut something they haven't read correctly in the first place.

Would you please narrow it down to one of textbook or research book? The current version is too broad. Also, narrow it down to certain fields will help to reduce the scope of this question.

@scaaahu Sure, I'll do tomorrow.

@scaaahu ->  How much does it cost the publisher to transform the draft of a textbook as given by the authors into a final publication (for web or print)?

@BenCrowell Why did you close the other question? I tried to follow your comment.

Here is one story on it from US News & World Report... Their example was a Calculus textbook selling for $289 at the bookstore.

Where does all that money go? According to figures from the National Association of College Stores, an average of 21.6 cents of every dollar spent on a new textbook will go to the bookstore, whether for personnel costs, operations, or income. For Kadue's $289 textbook, that's around $62. Another cent of every dollar pays for the freight of shipping a heavy book around, so subtract another $3 from her cost. That leaves around $224 that goes to the publisher, or around 77.4 cents for every dollar.
NACS no longer receives information from publishers about where textbook money goes, but as recently as 2008, they provided that cost breakdown. At that time, around 15.4 cents of every dollar went toward marketing the textbooks, 11.7 cents went to the authors, and the largest chunk—32.2 cents—went to the basics: paper, printing, and paying publishers' employees.

Many years ago I had a discussion with a shopkeeper of a technical bookstore in my country. They told me that only about 10% of the book's price, for imported books, would go to them.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


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What can a non-researcher/academic do to promote open access?
When presenting the academic publishing system to people who don't have a job related to academia or research, they sometimes ask me what they can do to promote open access.
What can a non-researcher/academic do to promote open access to research papers?
The "how to promote open access" lists (example 1, example 2) tend to focus on researchers/librarians/funding agencies/policy makers/students/University administrators.

Why do they want to promote open access? Is it just for ideological reasons, or is it because they have trouble gaining access to papers that they want to read?

@ff524 It is often both.

Some thoughts:

Write their representatives in government. Encourage them to support open access mandates for publicly funded science.
Write the authors of open access papers they do read, and thank them for making their work open access. Positive feedback, even if it's not career-altering, is always nice.
Give to their local university/alma mater/etc.'s capital campaign, specifically to support funding to help cover open access charges for projects that don't have enough funding to pay for those fees themselves (often grad student/postdoc projects).


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Does any scholarship require the benefiting student to make open access any research paper they wrote during the scholarship period?
An increasing number of funding agencies require recipients to make all research papers it funded open access.
Does any scholarship require the benefiting student to make open access any research paper they wrote during the scholarship period?

The Bill & Melinda Gates Foundation funds scholarships and has an open access policy:

[...] We have adopted an Open Access policy that enables the unrestricted access and reuse of all peer-reviewed published research funded, in whole or in part, by the foundation, including any underlying data sets. [...]

The Max Planck Society in Germany funds scholarships and has an open access policy.
These are the two examples I remembered directly.

I work at an MPI and unfortunately this doesn't seem to be common practice.

@LLlAMnYP Most scientists struggle with the open access policies of their funders.

I'm not sure what you mean here by struggle. Our directors don't push us to publish open access, so I guess they feel no pressure to do so, neither does my contract enforce me to do so. It would be nice, but I don't seem to have a point to argue.

Yes. Most research funded by the US Government (both internally by government employees and externally by outsider researchers receiving funding) is supposed to be available for the public. This would cover both direct scholarships/fellowships as well as grants and contracts to Professors that cover graduate assistantships.
This is not open access per say, because the research can be published in closed-access journals, but then is made public after an embargo period on a US Government page or publisher's webpage. The Association of Library Reseachers discuss this and has more details about specific agencies. Additionally, Nature News has a press release on the topic. Last, Columbia's Library also has an informative webpage on how different Federal Agencies meet the open access requirement. From an academic practitioner's perspective, this is probably the most informative page of the three I listed.
As final point, to revisit the "supposed to" caveat. Not all US funded research is covered (e.g., sensitive/classified Defense research). Some agencies may have not setup their methods for storing and releasing publications. Different agencies may enforce the open access policy with different levels of strictness. As a final caveat, most of the open access requirement policy is driven by an Executive Order rather than a Congressional mandated law. This makes the policies more easily subject to change.


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How much money do universities pay to access datasets?
Is there any research/study/survey that tried to quantify how much money universities / academic research labs pay to access data sets?

For example, in the United States, many hospitals as well as health insurance companies charge universities to access patient data.
Another example: in natural language processing, many datasets (including some very commonly used datasets) are sold by the Linguistic Data Consortium.

I am mostly interested in the United States and the field of computer science.

While having been at Penn and used LDC data, I have no idea who pays the crazy fees they request. Presumably you are not interested in specific examples from the LDC or similar groups/data and want totals. Is that correct?

@StrongBad Total is better, but specific examples from the LDC or similar groups/data is better than nothing. FYI Why doesn't the Linguistic Data Consortium release its data sets free of charge? Not a fan.

I'm not sure this can really be answered, because it will depend entirely on the data.  It ranges everywhere from "free" to "super expensive" to "not available at any price".  You could try asking a resource librarian maybe, to find out what a particular school pays, but I'm skeptical that any answer you get would be representative.

@Jeff that's ok as I mostly interested in totals, in which case the price diversity doesn't matter

I can not offer you research, but I can tell you that when I was touring the library at SFSU, the librarian said that they pay something over $200,000. for access to their complete list of journals and databases. I imagine it varies considerably from one to the other university.


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Can anonymized teaching evaluations be made public in the United States?
Can anonymized teaching evaluations be made (legally) publicly available by the teacher who received them in the United States? For example, I have seen a fair amount of teaching statement containing anonymized teaching evaluations in faculty applications, and some of these teaching statements are publicly available (e.g., placed on the applicant's website)

Related: University policy of publishing student course evaluations: Prevalence and pros and cons

@BenCrowell Is it useful to add excerpts from teaching evaluations in a teaching statement?

I have voted to close as duplicate because the question linked by @MadJack shows cases where these are being made publicly available without apparent objection.


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Is it ok to upload joke papers to arXiv?
I have recently stumbled upon this paper on arXiv:
 Stopping GAN Violence: Generative Unadversarial Networks  (mirror), which is a parody/joke paper.
Is it ok to upload joke papers to arXiv?

viXra would be a better place for joke papers.

I think it is okay when the paper is extremely funny, like the one you have linked.

OK, according to whom?

@MadJack arXiv policy.

It is interesting to observe that the cultural split in the answers here, between Oh April Fools Day is all good fun! and This just creates a mess that impacts other people., is the same as at Wikipedia.

To those in the know, "Under review as a conference paper at SIGBOVIK 2017" is also a strong indicator, SIGBOVIK being the Association for Computational Heresy's annual conference held on or around April 1 in in Pittsburgh.

I am surprised (not unpleasantly...) to see such a long list of joke arxiv papers in the field of astrophysics.  There are no joke arxiv papers in mathematics.  Please correct me if I'm wrong....Pretty please?

@PeteL.Clark That is interesting because in mathematics "the genius of Proust is that which he produced" holds most acutely. You cannot B.S a proof to someone actually trying to read it.

There is a long tradition of posting joke papers to arXiv on or around April Fool's Day, especially in astro-ph - see the list below. The fact that all these papers were approved for arXiv offers some evidence (though not proof) that joke papers are okay.
It's probably best to limit joke papers to around April 1, though, when people know to be on the lookout for this stuff - or at least provide some indicator which is very clear to experts in the field that the paper is a joke, such as listing it as being submitted to Acta Prima Aprilia, SIGBOVIK, or the Annals of Improbable Research.
A history of arXiv joke papers
(mirrored-ish on my website)

Superiority of the Lunar and Planetary Laboratory (LPL) over Steward Observatory (SO) at the University of Arizona (2002)
On the Utter Irrelevance of LPL Graduate Students: An Unbiased Survey by Steward Observatory Graduate Students (2002)
Cosmic Conspiracies (2006)
Natural Dark Energy (2007)
Down-sizing Forever (2008)
Time variation of a fundamental dimensionless constant (2009)
Galaxy Zoo: an unusual new class of galaxy cluster (2009)
Orthographic Correlations in Astrophysics (2010)
Schroedinger's Cat is not Alone (2010)
Non-standard morphological relic patterns in the cosmic microwave background (2011)
On the influence of the Illuminati in astronomical adaptive optics (2012)
Gods as Topological Invariants (2012)
The Proof of Innocence (2012)
On the Ratio of Circumference to Diameter for the Largest Observable Circles: An Empirical Approach (2012)
Non-detection of the Tooth Fairy at Optical Wavelengths (2012)
Pareidolic Dark Matter (PaDaM) (2013)
A search for direct heffalon production using the ATLAS and CMS experiments at the Large Hadron Collider (2013)
Unidentified Moving Objects in Next Generation Time Domain Surveys (2013)
Conspiratorial cosmology - the case against the Universe (2013)
Common origin of superluminal neutrinos and DAMA annual modulation (2013)
"Winter is coming" (2013)
The CMB flexes its BICEPs while walking the Planck (2014)
Bayesian Prediction for The Winds of Winter (2014)
A Farewell to Falsifiability (2015)
Beyond the New Horizon: The Future of Pluto (2015)
Astrology in the Era of Exoplanets (2016)
An unexpected new explanation of seasonality in suicide attempts: Grey's Anatomy broadcasting (2016)
Pi in the sky (2016)
SET-E: The Search for Extraterrestrial Environmentalism (2016)
Stopping GAN Violence: Generative Unadversarial Networks (2017) (the example from the question, included for completeness)
A Neural Networks Approach to Predicting How Things Might Have Turned Out Had I Mustered the Nerve to Ask Barry Cottonfield to the Junior Prom Back in 1997 (2017)
On the Impossibility of Supersized Machines (2017)
Detecting the Ultimate Power in the Universe with LSST (2017)
Sitnikov in Westeros: How Celestial Mechanics finally explains why winter is coming in Game of Thrones (2018)
Independent Discovery of a Sub-Earth in the Habitable Zone Around a Very Close Solar-Mass Star (2018)
Colonel Mustard in the Aviary with the Candlestick: a limit cycle attractor transitions to a stable focus via supercritical Andronov-Hopf bifurcation (2018)
The Long Night: Modeling the Climate of Westeros (2019)
Worlds in Migration (2019)
Forecasting Future Murders of Mr. Boddy by Numerical Weather Prediction (2019)
A new kind of radio transient: ERBs (2019)
Novel approach to Room Temperature Superconductivity problem (2020)
Quantum Godwin's Law (2020)
An Artificially-intelligent Means to Escape Discreetly from the Departmental Holiday Party; guide for the socially awkward (2020)
The search for life and a new logic (2020)
Making It Rain: How Giving Me Telescope Time Can Reduce Drought (2020)
Searching for Space Vampires with TEvSS (2020)
A PDF PSA, or Never gonna set_xscale again -- guilty feats with logarithms (2020)
Defining the Really Habitable Zone (2020)
Pandemic Dark Matter (2021)
"I'll Finish It This Week" And Other Lies (2021)
Using Artificial Intelligence to Shed Light on the Star of Biscuits: The Jaffa Cake (2021)
The Swampland Conjecture Bound Conjecture (2021)
Detection of Rotational Variability in Floofy Objects at Optical Wavelengths (2021)
I Knew You Were Trouble: Emotional Trends in the Repertoire of Taylor Swift (2021)
Quantum analog of resource theory of stinginess (2021)
The secret of the elixir of youth of blue straggler stars (2021)
Science Spoofs, Physics Pranks and Astronomical Antics (2021)
My cat Chester's dynamical systems analysyyyyy7777777777777777y7is of the laser pointer and the red dot on the wall: correlation, causation, or SARS-Cov-2 hallucination? (2021)
The Swapland (2021)
"My Rhodopsin!": Why Adding Dark Mode to Journals Could Make Us All Better Astronomers (2022)
Worry No More, The Hubble Tension is Relieved: A Truly Direct Measurement of the Hubble Constant from Mooniversal Expansion (2022)
Could fresh lava be (warm) dark matter? (2022)
What's for Lunch? A systematic ordering of foods in the Soup-Salad-Sandwich phase space (2022)
Taurine in Taurus. An Over-Caffeinated Search for Coffee in Space (2022)
COWS all tHE way Down (COWSHED) I: Could cow based planetoids support methane atmospheres? (2022)
The popular myth of the drunk fireworks in the Valencian Fallas: "If you run, it chases you" (2022)
Predicting Winners of the Reality TV Dating Show $\textit{The Bachelor}$ Using Machine Learning Algorithms (2022)
The Parking Lot Planet (2022)
Social distancing between particles and objects in the Universe (2022)
Transmogrifiers: Bright of the Exomoon (2022)
On the Possibility of Discovering Exoplanets within our Solar System (2022)
The Three Little Pigs and the Big Bad Wolf: Case Studies of Peer Review (2022)
Follow the Index: A new proposal (2022)
A Modest Proposal for the Non-existence of Exoplanets: The Expansion of Stellar Physics to Include Squars (2023)
When Tails Tell Tales (2023)
On The Planetary Theory of Everything (2023)
As a matter of colon: I am NOT digging cheeky titles (no, but actually yes :>) (2023)
UFOs: Just Hot Air or Something Meteor? (2023)
Nuggets of Wisdom: Determining an Upper Limit on the Number Density of Chickens in the Universe (2023)
ChatGPT scores a bad birdie in counting gravitational-wave chirps (2023)
Chromaticity Effects on the Outcomes of Spheroid-based Scored Events (2023)
Party Planning the Next True Happy New Year: Lunar Orbital Evolution Epochs with Integer Synodic Months Per Year (2023)
Can AI Put Gamma-Ray Astrophysicists Out of a Job? (2023)
A Unified Nomenclature and Taxonomy for Planets, Stars, and Moons (2023)
MO0NFALL: The Great Filter and Exo-Moon Occurrence (2023)
Programmed but Arbitrary Control Minimization of Amplitude and phase for speckle Nulling (PACMAN) (2023)
Macroscopic Dynamics of Entangled 3+1-Dimensional Systems: A Novel Investigation Into Why My MacBook Cable Tangles in My Backpack Every Single Day (2023)
Multi-Messenger Astrology (2024)
Everything's Fine (2024)
Deeper Learning in Astronomy (2024)
Is Winter Coming? (2024)
Why FLAMINGO is the perfect name for an array of Cherenkov telescopes (2024)
Unobserving the Moon: the spurious possibility of orbital decoupling due to solar neutrino Arago spot (2024)
Echoes from a long time ago: Chewbacca inflation (2024)
FOOD I: A New Division Scheme For The Stelliferous Era (2024)
Species Syzygy: Which Animal Has Seen the Most Total Solar Eclipses? (2024)
Circular reasoning: Solving the Hubble tension with a non-$π$ value of $π$ (2024)
The Public Photometry Pipelines for Exoplanets (2024)
In Violation of the Prime Directive: Simulating detriments to Delta-Quadrant civilizations from the starship Voyager's impact on planetary rings (2024)
Vulcan: Retreading a Tired Hypothesis with the 2024 Total Solar Eclipse (2024)
I'm in AGNi: A new standard for AGN pluralisation (2024)
pastamarkers: astrophysical data visualization with pasta-like markers (2024)
A Promising New Dark Matter Candidate, and Implications for the Search for Extraterrestrial Intelligence (SETI) (2024)
Scatophobic Dark Matter (2024)
Nishimori's self-tuning as evidence for the existence of God (2024)
On the Superiority of the University of Arizona's Physics Club (2024)

Note: since this has become what I think is the most comprehensive list of arXiv joke papers I know of, I've made it community wiki so anyone can add to the list. Any additions should be clearly joke papers and, in keeping with the topic of the question, must be posted on arXiv.

As another example there is also Donald Knuth's (quite hilarious) "The Complexity of Songs" which was published in ACM SIGACT - a quite serious and prestigious journal. So the tradition of posting joke papers does not just exist on arXiv but is a wider phenomenon at that.

-1, because I was planning on using my time productively before seeing this.  (+1!)

So how do non-experts know when they're reading a joke article? That sounds unprofessional and childish to me.

@CapeCode Articles on arXiv are targeted at experts. Other people generally won't understand what they're reading whether it's a joke or not.

The best joke paper of all times is Gates, V., et al. "Stuperspace." Physica D: Nonlinear Phenomena 15.1-2 (1985): 289-293.  The published version is available here: https://www.sciencedirect.com/science/article/pii/0167278985901733 and a free e-copy from here: http://languagelog.ldc.upenn.edu/myl/Stuperspace.pdf. It predates arXiv.

Not on arXiv, but relevant: Another article that makes bibliometric analysis a bit harder

@DavidZ Does https://arxiv.org/abs/2203.17060 count as "clearly a joke"? After all, it's making fun of practices that apparently made it past referees of Nature and Science.

@Anyon Hmmm, good question... I read the paper and it does have some telltale signs of being intended as a joke, but it wasn't actually clear to me that it was a joke. Or maybe I should say I didn't get it. I mean, part of what typically makes a good joke paper is that it's funny even to non-experts. But that is not part of my stated criteion. So I'm on the fence about including that one, but I think if someone well versed in Majorana research can confirm that they would consider it clearly a joke, I'd put it on the list.

Uploading joke papers to arXiv does not violate arXiv policy, according to this email sent by the arXiv moderation:

---------- Forwarded message ---------- From: arXiv Moderation  Date: Mon, Mar 13, 2017 at 4:38 PM Subject:
  [moderation #189697] Removing a joke paper To: spamme@gmail.com
Dear Spa,
We will not remove this paper as it does not violate any of our
  policies.
-- [retracted name] arXiv moderation
On Sat Mar 11 18:27:47 2017, spamme@gmail.com wrote:

Dear arXiv-moderation,
This paper is a joke paper: https://arxiv.org/abs/1703.02528 (it was
    submitted to an April 1st joke conference: http://sigbovik.org/2017).
Could you please remove it from arXiv?
Best,
    Spa Mme

This seems to be in contradiction with https://arxiv.org/help/moderation  (mirror):

arXiv is distinct from the web as a whole, because arXiv contains exclusively scientific research content. Although arXiv is open to submissions from the scientific communities, our team has worked behind the scenes for a long time to ensure the quality of our content.
arXiv moderators will suggest the removal of a submission that violates arXiv policies in some way. Potential reasons for removal are: Inappropriate format. arXiv accepts only submissions in the form of an article that would be refereeable by a conventional publication venue. This excludes […] papers that contain inflammatory or fictitious content, papers that use highly dramatic and mis-representative titles/abstracts/introductions.

That might be slightly surprising. In ArXiv moderation system page we read:
"arXiv is distinct from the web as a whole, because arXiv contains exclusively scientific research content." and "arXiv is an openly accessible, moderated repository for scholarly papers in specific scientific disciplines. Material submitted to arXiv is expected to be of interest, relevance, and value to those disciplines. arXiv reserves the right to reject or reclassify any submission."
I wonder why ArXiv moderators classify clear joke papers as scholarly papers with scientific content.

@PsySp Yes I was surprised too (and disappointed). I wonder what it takes to be an arXiv-approved joke.

Maybe these excerpts from the Moderation page of ArXiv should be added to your answer because it seem they directly contradict the answer you received from the moderator!
https://arxiv.org/help/moderation
(It is even in bold!)

@PsySp Sounds good, added. Apparently a joke isn't fictitious content, but is scientific research content.

The arXiv (pronounced "archive")is a repository of electronic preprints, known as e-prints, of scientific papers in the fields of mathematics, physics, astronomy, computer science, quantitative biology, statistics, and quantitative finance, which can be accessed online.
So, please do not upload joke papers. These papers are not helping the community, and they are not helping the authors of such papers.
Having said that, if the paper has any scientific value, even if it is a funny paper, then it is more than welcome. TCS has a conference called FUN with algorithms the purpose of which is to publish amusing papers with certain algorithmic flavor.

@FranckDernoncourt I mean, in case the authors use their real names (which I doubt). In any case I do not see why anybody would want to create noise as you say.

I'm an arXiv moderator, and I disagree with this answer.

@JeffE please post your own answer?

@JeffE A good recipe to receove something like my last "Our volunteer moderators determined that your article does not contain sufficient original or substantive research to merit inclusion within arXiv.   Resubmission of removed papers may result in the loss of your submission privileges."

@smci I have added an email sent by the arXiv moderation as an answer.

@PsySp: It wasn't intended as a personal comment, but if it came across that way then I apologise. That said, I do think there's a need to distinguish between entertaining papers written by researchers in a field for the amusement of other researchers in the field (which to my mind are, and should be, welcome on arXiv, if not to excess), and spam papers that have nothing to do with the field in question, or contain junk text. In this case, the authors are serious guys writing under their own names, who've put effort into making the paper entertaining to their community.

It's actually not so easy to do well, and it's somewhat risky if (as in the case of one of the guys) you're well-known in the field - in this case, I think they've judged it carefully and got the balance right.

@StuartGolodetz My opinion is that a joke paper, published under Machine Learning tag, is borderline qualified for spam. There are many other places where such a paper would be more appreciated and could potentially invoke less inconveniences. Because, sometimes, it's hard to judge if it's a clear joke or not.

@PsySp: I think it's subjective - let's move on.

@StuartGolodetz If you are well-known but take your reputation lightly then it is not very risky. Well-known people are HARDER to get sacked, not easier!

Also, realize that people have done this to real journals.  Consider the Sokol hoax. Or the famous math paper about big game hunting mocking. Or the more subtle Physical Review Letter co-author F. D. C. Willard
I would avoid doing it too much.  And if it gets done too much it will damage the resource.  That said, a little bit is kind of amusing.  Especially if skillfully done.  But some pepper is good...too much is bad.

I consider the paper "An Explicit Conjectured Determinant Evaluation Whose Proof Would Make Me Happy (and the OEIS richer)" by Doron Zeilberger
a joke paper, or at least a troll paper.
There are no false statements or non-research in the paper.
The issue is that Zeilberger (cleverly) hides the fact that a solution to his problem also solves the very famous Collatz conjecture.
So people trying to solve the problem stated in his paper are very likely to waste their time on a problem that is way harder than it seems.
On the other hand, there could be a George Dantzig moment a solution is easier found if one believes that the problem is solvable. Dantzig famously mistook two open problems in statistics for class homework, and turned in the solutions a few days later.

It does happen, but there are also humorous journals you may also submit to, especially if it is satirical as the Annals of Improbable research will only accept real research that's funny.
I ran across this because I maintain one, The Journal of Astrological Big Data Ecology (Jabde.com) where we also host The Journal of Immaterial Science which tends to involve more chemistry humor. If anyone runs across this, we always accept paper submissions and do actually publish the really good ones.

authors: Vladimir F Героям слава

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
Does suggesting potential reviewers for one's submitted paper increase the likelihood of the paper being accepted?
Some journals propose authors to suggest potential reviewers for their submitted papers.
Is there any research/study/survey that tried to quantify to what extent  suggesting potential reviewers for one's submitted paper impacts the likelihood of the paper being accepted?

Being in a position to suggest reviewers probably means you are integrated in to your research community and accepted within it. One's prior success is likely the best predictor of future success.

Suggested reviewers are often a path to collusion as well.  I don't think naming them helps your chances.

@JonCuster However, the ancedotal evidence here: https://academia.stackexchange.com/q/10474/19607 suggests that suggesting reviewers lowers the likelihood of a paper being accepted (interpreted in an appropriate statistical sense).

I highly doubt there has been a study on this, and you will not get more than ancedotal evidence such as in the post I linked to above.

One journal I sent one of my articles to had the requirement of naming 4 potential reviewers. If you did not name any or not enough, your submission was not accepted. I don't know if this is the case with other journals as well, but in this instance, it did not improve your chances at all.

This question was asked a long time ago but remains on the unanswered queue. The answer is yes, there was a research paper studying this question. According to this answer on academia.SE, "the overall conclusion seems to be that reviewers suggested by authors provide reviews of equal quality than those selected by the editor. While they are more likely to suggest acceptance in the initial review, at later stages these suggestions seem to equalize."
Does that mean authors should aim for journals where the author gets to choose/suggest referees? I would say not! For an author, it's very worthwhile to point out that "likelihood of the paper being accepted" is the wrong metric to care about for your career, long term. If you want to maximize your likelihood of being accepted, you could publish in a vanity press journal, where you pay them to publish your work and acceptance is essentially guaranteed. But this would not be good for your career.
A better metric would be: "is this journal well-regarded by experts in my field? Will publishing there reach the audience I had in mind when I wrote the paper? Will this journal provide me with a referee report that will make my paper stronger?"
Right now, in math, essentially no journals allow the author to pick the referee. I recently wrote an answer about this, and the ways such a review process would subvert critical reasons for peer review. So, if an author came across such a journal, it would be unwise to try to publish in it, because experts might view the journal (and hence, the author, for having published in it) with suspicion due to this highly unusual referee process. Furthermore, a "soft" referee report from a friend of yours will not make your paper stronger. Others agree with me that this practice should be discouraged.
The OP is a well-respected expert in natural language processing with over 100 publications and surely knows this, so I'm aiming this answer more at a random reader interested in this kind of procedure for picking referees. In every field of science that am aware of, a large majority of experts believe it's important for referees to be chosen by editors, not authors.


text:
What percentage of research papers have been digitalized?
Is there any research/study/survey that tried to quantify the percentage of research papers that have been digitalized?
I understand that the notion of "research papers" may need to be defined in such a study, as well as other boundaries (e.g., date range).

Could you please clarify what you mean by digitalized? Are you looking for the percentage of papers that are now published online and not print-only? Are you looking for old papers that have been published print-only in the past and are now step-by-step digitalized?

@FuzzyLeapfrog I meant stored in some electronic device, e.g. hard drives. I have in mind old papers that have been published print-only in the past and are now step-by-step digitalized.

Even so I'm a little bit familiar with this topic, I couldn't find an overall percentage or at least the amount of digitized papers. But at least I can give you the denominator, i.e. the estimated number of all existing scientific articles: > 50 million in 2010 (source). If you find the numerator, please let me know.

Do you mean, in English, or all languages?

@einpoklum I'm interested in both

Not an expert, but I would argue that this would be neigh impossible to determine given the criteria:

Definition of 'research paper'. As you stated, this needs to be defined, would this only include peer-reviewed? Published in a reputable publication medium?
Definition of Digitization. Would microprint count? How about magnetic tape? Without a means of know what is and is not digitized, an accurate count would be impossible.
Knowing the upper limit of all knowledge, known-knowns (such as Google's Index of papers) Known-Unknowns (such as closed-circulation repositories), Unknown-Knowns (some repository that exists but the researcher doesn't know about), and unknown-unknowns (perhaps a hidden server in a soviet bunker from the 80's).


text:
Difference of professor salaries between different department in the United States
Is there any research/study/survey/... that looked at the difference of professor salaries between different department in the United States?

Here's one that's readily accessible, though the full data isn't public (but can be obtained).   Here's another one in a much more concise format, though a bit older.
At least for public universities, it's not too hard to do such a survey since our salaries are public record.  I haven't actually checked but I would imagine that the groups that have done these surveys keep them updated every so many years so you can use the ones I linked to to find more.

Note that sometimes the salaries you find online are not accurate.  My university's salaries were once posted by a 3rd party site in a very misleading manner to make the salaries seem higher than they are.

I'm skeptical the data in the second link is not misleading.  (Though +1--it's not your fault!)  It tells you something, but the variance among schools for a fixed department is so large (e.g., compare research vs teaching, and public vs private) that this should be controlled for to get a better sense of things.  E.g., the variance at my school among certain departments is much larger than what that aggregate data would indicate.


text:
Picking referees for a staff review?
For an interim (or tenure!) review, are their guidelines in place for choosing "neutral" referees, if asked?
Obviously choosing the PhD advisor (and probably postdoc advisor) is a no-no, but are there other things to take into consideration? For instance:

How important is the standing of the referee?
How well should the referee know the candidate?
If someone is working in an inherently multidisciplinary area, how should the referees be selected? According to the "home department" of the candidate, or are other criteria more important?

tl;dr: You want a letter from God.  Until then, do not work with God.
Reference letters for promotion and tenure cases are supposed to be impartial evaluations of the quality, importance, visibility, and impact of the candidate's research, their standing in the research community, and their promise of future intellectual leadership (or in the case of full professor promotions, their proven intellectual leadership.)  So the people who write those letters must be credible independent judges of those qualities.
Here are the rough guidelines applied at my university.  Specific standards my be different elsewhere, especially outside the US — Ask your senior faculty mentors, department chair, and/or dean! — but I suspect the general principles are common everywhere.

Referees must be familiar with the candidate's research.  Promotion letters must discuss the importance and impact of the candidate's research in detail.  It is especially helpful if the candidate's work led to a breakthrough in the referee's research.  (Obviously, you can't dictate the letter; you have to choose a referee that can write such a letter.)  It doesn't matter whether the referee knows the candidate personally.
Referees must be experts in the candidate's research area.  For successful cases, this criterion should immediately imply the first.  However, "research area" must not be defined so narrowly that there are only a dozen experts in the entire world, or the impartiality of the referees is not credible.  Editors-in-chief of major journals, committee chairs of important conferences, and officers in relevant professional societies are all good choices, but for the most part, the expertise should be visible from the language of the letter.
Referees must be obvious experts in the candidate's field.  Here by "field" I roughly mean "department".  The letter-writers will be scrutinized by faculty committees at several levels (department, college, and campus), most of whom don't have the expertise to make a direct judgement; they have to rely on the trappings of success instead.  At my university, it is a de facto requirement that all promotion references must be full professors (preferably with chaired positions) at top departments, in top colleges, in top universities.  Professional society fellows and major award winners are even better.
Referees must be obviously impartial.  Thesis and postdoc advisors are right out.  At my university, any faculty member from the candidate's PhD department is barred, but this is not universal.  Frequent and/or recent coauthors/coPIs are out.  It's okay to have a few letters from former collaborators, as long as the coauthored work is far enough in the past and represents a small fraction of both the candidate's and the referee's research record.
Referees must be familiar with the promotion standards of the candidate's institution. At my university, this means that almost all letters must come from faculty at top American universities.  I was explicitly warned not to ask for letters from European researchers, because they tend to write blunter ("more honest") evaluations than Americans, and in any case, European promotion systems are different.  This is another reason for needing letters from top institutions; a supportive letter from a significantly lower-ranked school will likely be viewed with suspicion, because the writer "doesn't understand our standards".

Multidisciplinary research makes this much more difficult.  The strategy I would recommend (and have applied myself) is to find referees that cover most of the different disciplines of the candidate's research.  To pick a random example, a candidate studying molecular simulations might request letters from other molecular simulators, from other computational scientists, and from polymer chemists.  This may require a higher than usual number of letters.
An additional complication at most US universities is that a majority of the referees must be chosen by the candidate's department, without the candidate's knowledge or direct input.


text:
How to avoid identifying myself in a review?
Occasionally I find myself currently reviewing a paper where I find that many of the criticisms I have are addressed in papers in which I am an author (and often as lead author).
I don't want to make my identity known to the writers of the papers—but how do I make my points clear without breaking the "anonymity" of the review. Even if I cite a bunch of papers each time, it will probably be obvious what's going on.

I recently reviewed a paper in a similar situation. The paper was good but some relevant publications I was aware of (not mine) probably should have been cited. When writing the review I simply suggested the specific topic which should be referred to, rather than specific papers. That way the suggestion is there and all they have to do is look. They got a couple of papers that I had in mind, and some others, so all was well in the end.
I don't personally agree with suggesting citation of your own papers directly in a review since as you point out this leads to suspicion of the identity of the reviewer, but also because reviews should be impartial as far as possible. If a paper that I authored is the most relevant work then any proper search will find it, if not then something else equally suitable will probably be ok for most readers.

I mostly agree, but I would say that if “any proper search will find” the paper, then the authors would have already done so… or they did not conduct a “proper search”.

If you believe that there are papers that the author should cite, list them in your review.  Yes, I mean the specific papers, with complete bibliographic information.  If you include some of your own papers in that list, the author of the refereed paper may suspect that you're the referee, but so what?
On the other hand, if you believe that the only papers that the author should cite were written by you, you're probably wrong.  Look harder.

I agree, not only do I find this approach more common from my own experience of getting reviewed, it also ensures that authors cite the "correct" paper that established a certain concept or idea, rather than a later one that merely mentions it.

I don't want to make my identity known to the writers of the papers

Why?
(Yes, also in my field reviews are supposed to be blinded on one side. But often very good guesses to who was the reviewer are possible. Sometimes it is obvious, and oftentimes I believe I could track down the reviewers at least to their groups because of the specific use of certain terms. And, yes, you could probably track me down because I also have typical questions. Personally, I'd prefer receiving review swith the reviewers' names (it is useless to thank reviewers A and B, as those two review all my papers, and everyone knows it - but I'd like to acknowledge reviewers by name) and to write reviews under my name as well.)
I see several possibilities here.

As was suggested already, name the issue, not the paper. You can also guide the authors to search terms that will lead to relevant papers.
There may be valid exceptions to this:

Sometimes one wouldn't know from title and abstract that the paper is relevant, e.g. when some methodological point was presented in a paper about an application.
Sometimes it is impossible to dig out relevant papers between other papers that use the terms differently or some combination of search terms happens also in irrelevant context*

Your question sounds as if you are well-known for the topic which you found missing in the paper.

If you are The Big Guy for this topic, pointing to your publication does not compromise your anonymity - any other reviewer who is aware of the issue would have done it, too.
If you are not The Big Guy, but maybe the only one in that field looking into this topic, odds are still you were asked to do the review because of this expertise. IMHO, the quality of the review matters much more than semi-existent (see above) anonymity.
In that case, I'd write the review so the authors can understand and address the issue easily. If you really think that this compromises your anonymity, you may write to the editor that you think your review is not anonymous, because ..., and possibly that he may decide to give your email to the authors and that they could contact you in case of further questions (IMHO it is much less work to answer a few questions that to have to review an additional time).

* e.g. "soft classification" in remote sensing is used ina certain way, which I took over into chemometrics. However, one very important classification method in chemometrics is SIMCA, the "S" for soft. It could be used as as soft classifier in the remote sensing meaning. But is usually isn't. So I got tons of hits with SIMCA. No hits excluding SIMCA, and after looking into a certain number of them and never finding it used in this "soft" way, I gave up and had to say that I didn't find any such application. If anyone knows such a paper, please tell me the proper citation. I don't mind if you're the author.

One reason not to identify myself is that they could potentially be asked to review my papers, and would prefer not to be an open target.

@aeismail: valid point (and one of the issues of the only supposedly blinded review system that IMHO speaks for open review: reviewers would be forced to write reviews that don't make them blush when associated with their name...) Though a) you can of course list them as "not suggested reviewers". b) if they don't know of the topics you work at, how would they become reviewers for your papers? c) if you suspect they know, but suppressed it, you should have very good arguments for that, and IMHO that were something the editor should know.

@JeffE: No. The issues in the paper go way beyond citing relevant papers. If it were just a citation issue, I wouldn't have bothered with the question.

@aeismail: Sorry, let me rephrase.   Really?  You expect your colleagues to react that badly to professional criticism?  Really?

@JeffE: Unfortunately, yes. I've already had it happen to me. Once bitten, twice shy.

@aeismail: This is where I would normally write "Don't walk. Run."

This is a great question.  I've run into this situation several times, and I'll tell you what I do:

First choice: Post a comment visible to authors.  If I'm lucky, the program chairs have chosen reviewing software that allows me to post comments (which are separate from my review) that will be made visible to the authors.  Then, I mention that the citation in a comment that's visible to the authors.  This way, the citation/comment can't be linked to my review.  The authors might guess that I was one of the reviewers, but they won't know whether I was one of the folks who wrote a positive review or a negative review.
This is the best case, but sometimes you get unlucky and the program chairs have chosen reviewing software that doesn't support this feature.  In which case, my second choice is:

Fallback: Contact the program chairs and ask for their help. I contact the program chairs, explain the situation (that I have a comment I'd like to share with the authors, but I don't want it to be linked to my review, because it might identify me), and ask for their help.  Often they have a way that they can accomodate this.  For instance, most online reviewing software these days can accomodate external reviewers.  In that case, the program chair can send me an invitation as though I were an external reviewer, and I can supply an external review whose only content is the citation.  As another example, the program chairs might be willing to manually send an email to the authors mentioning this additional comment, or they might be willing to submit a review of their own mentioning the relevant citation.

Last resort: Don't mention it in my review. If none of the above options are available, then I do not mention the citation in my review.  I believe reviewers have the right to remain anonymous, and don't have any obligation to the authors that supersedes that.  Instead, I mention the related work in a comment to the program committee, to justify my recommendation on whether to accept or reject the paper.  Then, I might include a general comment in my review that the authors have not done sufficient review of the literature and that they should do a further literature search; and I might even include some tips, like the conferences or journals that they should be reading.  This is not as helpful to authors as I would like, which is why this is my last resort.  And, if I'm forced to this last resort and the program chairs aren't able to help me get my message through to the authors, then I tend to view that as a shortcoming of the arrangements that the program chairs have made.

I think it is great that you are thinking about these issues and doing your best to provide authors with detailed comments and reviews.  Kudos!  That's the kind of spirit we should all applaud and encourage.


text:
Are there any "tells" for faculty hires?
I was curious to find out if there were any "tells" in faculty searches that someone is going to get a formal offer before the official paperwork is received. Are candidates who are about to be hired asked to fill out extra forms or provide additional documentation that might not have been needed earlier in the process, or something similar?

For my current position, the "tell" was the department chair calling me up and saying something like, "We'd like to offer you a job.  Before we start the official paperwork, can you tell me how likely you are to accept?"

This will likely be so utterly dependent on the committee, the university, the country and the moon phase that you won't get any more than anecdotes as answers.

@StephanKolassa I agree. Though if you're coming from another country, they might ask for some more information to check that you are eligible for the requisite visas (particularly if you intend to bring family with you). But I'm just speculating there...

@MarkMeckes That's a pretty good tell, but probably not what aeismail is looking for :)

Positive early signs:

you helped write the job specification;
one or more of the selection panel advised you to apply for the vacancy;
they take up your references;
you hear through the grapevine that members of your target department have been asking around, about you, after your interview;
you get an additional interview, where the main topics of discussion are pay & other benefits, when you could start, and what facilities you'd require in post.

Regarding formal paperwork,: all applicants at our place are required to show eligibility for employment, at time of interview. So there's no additional requests for paperwork between final interview and job offer.

You had me at "you helped write the job specification".

While your points are positive signs, I am not sure they are indicative of a forthcoming offer.

@StrongBad Are you talking about one of them, most of them, or all of them?

For many searches the "official" paperwork is often only received very late in the game such that at the time you receive the contract nothing is left to negotiate. There will often be a very early congratulatory call saying saying we would like to make you an offer (which is not quite the same as making an offer), let's talk about salary and startup. Searches often move quickly once they decide they want to make an offer. Sometimes there is a hold up, for example, waiting for Dean's approval, but generally, I would say once a decision has been reached, they let the candidate know ASAP.
I suggest asking at the interview when a decision will be made. You can then follow up when that date passes and sometimes find out if things are not promising.


text:
What are good periodic color scales for density plots of angle-like function values?
I am writing several papers that require density plots of complex-valued functions of two variables f:R^2→C, where I'm primarily interested in the complex argument arg(f(x,y)) as a function of the input variables, but I wish to emphasize only the regions where the modulus |f(x,y)| is high.
Because of this, my approach thus far has been to produce density plots where the phase arg(f(x,y)) is encoded as the hue, and the modulus |f(x,y)| is encoded as a HSV chroma blend from white (where the modulus is zero, and arg(f(x,y)) is meaningless) to fully-saturated color at maximal modulus, where the phase is a meaningful variable.
However, this scheme suffers from being "non-orthogonal", in that some hue values (notably yellow and cyan) are much lighter than the baseline set by e.g. red or blue. I am looking for a combination that fixes these shortcomings, by providing:

A periodic color scale for the angle-like function value that passes through as many different colors as possible (i.e. at least some six distinct values, with a premium on contrast between them) while still maintaining a constant visual 'strength' throughout that traverse. I care primarily about subjective strength, but lightness is probably a good stand-in.
A conjugate color scale that goes from white to fully-'saturated' color that is as 'orthogonal' as possible to the angle variable.

As an example of what I'm looking for, this is a plot of the function f(x,y) = (x+iy)^2 exp(-(x^2+y^2)) using my current plotting conventions:

Mathematica source via Import["http://halirutan.github.io/Mathematica-SE-Tools/decode.m"]["https://i.sstatic.net/NFhW1.png"]
Note in particular how you can immediately read the ^2 exponent from the fact that over a round-trip around the origin you do a red→green→blue→back-to-red loop twice, while still being able to clearly tell that the function is concentrated at a ring around the origin between radii ~0.5 and ~1.5. However, there are still perceived 'intensity' gradients azimuthally within this ring (notably the perceived 'lobes' around the blue areas), which I would like to avoid. I would also, if nothing else, like to smoothen the visual contrast around the sharp ray-like features at yellow, cyan and, to a slightly lesser extent, magenta.
A few final notes:

This problem arises because I'm attempting the ambitious goal of plotting two-dimensional values on a single density plot. I know that this is an ambitious goal and that it may be impossible to fulfill completely. Nevertheless, I think it is still worth doing as good as possible with it.
I have indeed considered other formats to present the same information; you can assume that I've explored them thoroughly and found that they are too cumbersome or otherwise unclear.
This approach will obviously only work when printed out in color, and grayscale printing (either on the print journal or when readers print it out at home) will leave most of this information out. You can assume that I've weighed the pros and cons of this and decided that it's still worth including.
This is also an accessibility problem for readers with color vision deficiency. This is, I feel, an unfortunate necessity of plotting two-dimensional values on a density plot, and I feel the added clarity for non-CVD readers is a worthwhile tradeoff once the information loss for CVD readers is mitigated via other means.

So, with that said: are there better options for dealing with this problem than the hue-chroma combination I'm currently using?

I'm hoping that this is the correct venue for this question; it cuts across fields and the generalized handling of visual information is of relevance, I think to a large swath of academia. If others have interesting suggestions for alternative venues, I'm happy to consider them.

Have you seen the book Visual complex functions by E. Wegert?

Have you looked at colorbrewer and viridis to see if you can adapt one of those palettes?

@Massimo Judging by the publicly-available extracts, it looks like an interesting approach to complex analysis, but not quite a solution to this question: (i) the color map seems to be a straight hue map, and it shows the same sharp changes at yellow and cyan as my example; (ii) I'm not dealing with analytical functions, so I can't rely on intuition and convention to convey the amplitude information - it is a proper, independent degree of freedom that also needs to be reported. I'll try to get my hands on a copy, though - it looks like a nice book in any case.

@JenB I have (and they're great), but I don't see any periodic color scales there. In a sense, plotting a periodic variable is incompatible with one of those projects' aims (printing well to grayscale) so it is natural that they don't include one. My goals here are in some ways 'orthogonal' to those projects.

I thought that maybe one of the divergent scales could work from colorbrewer, or perhaps two of the viridis palettes back to back (so one runs clockwise from 0,1 to 0,-1 and then the next runs clockwise from 0,-1 to 0,1 but with colours reversed). But I might be misunderstanding what you need.

As you note, there are problems with the typical rainbow colour map.
Kovesi has done some work on perceptually uniform colour maps. Code is available here: https://peterkovesi.com/projects/colourmaps/index.html
In my work, I replaced the rainbow map with the Kovesi's first cyclic colour map for the angle values, and used either saturation or intensity (multiplication) for the modulus. In hindsight, it would probably make sense to map the raw modulus values to saturation / intensity using one of the perceptually uniform greyscale linear maps as well.

I am a fan of the Solarized colour scheme, which amongst others contains eight colours that have:

equal perceived brightness,
distinct tones.

Using these eight colours for the angle and then whitening (using Solarized’s white) according to the absolute value gives me for your example:

You may still perceive some sharp transitions, but most of these depend on the specific screen in my experience.
Note that this colour scheme is optimized for screen and not for print. In my experience it also works nice with projectors, and I use it for presentations (using the more intense variants for black and white).
Appendix: Code
Here is the Python code I used to generate the above image:
import numpy as np

def rgb_to_numerical(string):
    return np.array([
            int(string[1+2*i:3+2*i],base=16)
            for i in range(3)
        ])

white   = rgb_to_numerical("#FDF6E3")
colours = [rgb_to_numerical(colour) for colour in [
        "#B58900",  # yellow
        "#CB4B16",  # orange
        "#DC322F",  # red
        "#D33682",  # magenta
        "#6C71C4",  # violet
        "#268BD2",  # blue
        "#2AA198",  # cyan
        "#859900",  # green
    ]]

segment_size = 2*np.pi/len(colours)

def tone(angle):
    segment_num = int(angle//segment_size)%len(colours)
    stride = (angle%segment_size)/segment_size
    left_colour = colours[segment_num]
    right_colour = colours[(segment_num+1)%len(colours)]
    return left_colour*(1-stride)+right_colour*stride

def bleach(colour,amount):
    amount **= 3
    return colour*(1-amount)+white*amount

f = lambda z: z**2 * np.exp(-np.abs(z)**2)

size = (600,600)
re_range = (-3,3)
im_range = (-3,3)
mod_range = (0.55,0)
rgb_array = np.empty((*size,3),dtype=np.uint8)

for k,x in enumerate(np.linspace(*re_range,size[0])):
    for l,y in enumerate(np.linspace(*im_range,size[1])):
        value = f(x+y*1j)
        modulus = np.abs(value)
        angle = np.angle(value)
        intensity = (modulus-mod_range[0])/(mod_range[1]-mod_range[0])
        rgb_array[k,l] = bleach(tone(angle),intensity)

from PIL import Image
Image.fromarray(rgb_array).save("circular.png")

In general a good colour map is perceptually uniform (avoiding how the yellow and magenta stand out in your original), works when printed in black and white, and works for at least the majority of colour-blind people.
I'm not aware of any cyclic maps that manage black and white well (it's not really possible, because you can't have a monotonic progression of lightness and get back to where you started), and I'm not sure how well any of them do for colour-blindness, but perceptually uniform is achievable.
The other answers are good in pointing out the theory and offering some examples.
The "Phase" map from CM-OCEAN is another example, and is available in "ready made" form for Python and Matlab.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
What are good strategies for not losing sight of the novelty and nontriviality of one's work?
I would like to ask this community for help in finding good strategies for avoiding an aspect of my mindset that I don't much like, which I get when I've been working on a given project for a while - I begin to lose track of how novel and nontrivial the work is, sometimes leading to full-on crises of confidence in my work and, in bad cases, in my capabilities.
This happens to me once I'm rather deep into the project, around the stages of writing it up, defending it in correspondence with referees, and preparing presentations on the subject. (To anchor things a bit, I am a theoretical physicist working on analytical approaches in quantum mechanics.) In the initial stages of the project, and particularly at the times I have significant breakthroughs of either a technical or a conceptual nature, the elation and thrill of discovery will carry me a long way, and I end up building quite elaborate conceptual and mathematical structures that I am quite pleased with.
However, as a result of the familiarity that comes with using those initial breakthroughs over and over again, after some time they begin to 'flatten' in my mind as just regular features of my work, and the nontriviality of the tools I've built begins to wash out as the pains I felt when building them begin to fade into the distance. This is a version of 'familiarity breeds contempt', though maybe contempt is a bit too strong - it's just the over-familiarity that's the problem.
Now, this isn't really burnout, as this doesn't impact my day-to-day motivation to work or the energy I have to do it, and I continue to have interesting questions to work on and interesting answers for them. However, when I'm building a case for my work, particularly in writing, I find it hard to muster enthusiasm about the initial building blocks (usually the key advances in the work, particularly as perceived by an outsider) and to see them as anything other than well-trodden ground and everyday sort of fare. I know that it's because that's the ground I tread on every day, and that no one else does thus far, but it still impacts how I write about those tools and it makes it harder for me to present them with their full impact on the field.
I know that to some extent this sense of 'flattening' comes from the fact that as time goes on, I often find simpler routes to the results and tools of interest, and I know at an intellectual level that the existence of those simpler routes does not negate the effort it took to find the first one. That is, a result X that took months to understand can also be seen by spending a modest amount of effort building Y and then you "just add Z", but that still doesn't mean that the result is obvious to outsiders, and I know that the wholesale replacement of complex machinery for simpler tooling is also an achievement by itself. However, at a gut level, I still struggle seeing the result X in its full nontriviality, and it keeps flattening into just a trivial consequence of Z.
Moreover, I also have a good deal of objective evidence that the results are new and nontrivial, particularly in the fact that if I meet someone and walk them through the work, then the sheer amount of time it takes to go from baseline through the problem and tooling and up to the main results tells me that the material is indeed nontrivial, even after the simplifications. Similarly, the positive feedback I get in those situations tells me the work is worth its salt. However, that often lodges at an intellectual level but fails to register too much at a gut level of emotional handling.
I hope I've been able to describe this mindset sufficiently well. If nothing else, I would like the reassurance of knowing that I'm not the only one that faces this, but more importantly, I would like to know how folks with more punches under their belt handle this kind of situation, and what strategies I can try to regain an outsider's view of how novel and nontrivial my results are.

I also think most of what I've done in the past few years is trivial.  But I also think it's new and it's interesting.  These things aren't mutually exclusive.  It's your way of thinking about things that's important.  Selberg once said that the most important ideas in mathematics are the simplest ones.

I find that giving conference presentations helps. The people listening haven't been immersed in that exact topic for years, and are likely to find it newer and more interesting than you do, and their questions can help to remind you of this.

When you write papers or prepare presentations, keep in mind a reasonable audience.
If possible, I prefer to have in mind a specific person whom I've worked with, but I've also written for an imaginary generic grad student of someone I've worked with or tried to construct a composite person from several people (but then I have to be careful that this imaginary person doesn't know everything any of the individuals actually know).
If you don't have an audience in mind, it's easy to default to writing for yourself, which is ridiculous, since you already know everything you're writing.  Having an audience in mind makes you explain ideas at the right level of detail, which will naturally lead you to explain what's new about your work.
Unfortunately, this advice isn't very useful to grad students who don't know any experts in their field other than their advisor, and in particular don't know what other experts don't know already.

The problem isn't really that my writing assumes too much pre-existing knowledge from the audience - I'm generally happy with the accessibility of my writing. (Though of course it can always be improved!) The problem is more in keeping up the excitement about and appreciation for the core results once they become worn down by familiarity - I know how to explain them to an outsider in writing, but I struggle in finding ways to convince them to care about things that have gotten worn down to mundane objects by everyday use.


text:
Is it advisable to upload theses to the arXiv?
I'm currently uploading my MRes thesis to my university website, but I have some doubts regarding the permanence of the link as it may change after I graduate. I do not have many illusions over who may want to read my thesis in the future, but I would like to have a link to give to people or to put on papers in the future without fear of the link breaking in the near/mid/far future. Additionally, I know that having it available in a place spiders are more likely to look makes it (marginally) more visible to web searches and thus more discoverable.
A quick search turns up a good bunch of PhD theses, but it doesn't say how many there aren't very many MSc or BSc theses in there. My reading on this is that it is OK but by no means a standard practice.
Before I upload it though, I would like to know if there are reasons not to put it in such a public place. I am after all a bit of an arXiv fanatic and there may be factors I'm not considering. Any thoughts?

I also debated over putting stuff there and then I read, that you are not able to delete/withdraw that publication anymore?!?

If your university is fine with it, I don't see any reason not to. Well-written Master/Ph.D. theses are very helpful when learning new topics just like good survey/tutorial articles.

Speaking as an ArXiv moderator: MSc theses are definitely welcome on the ArXiv!  @T.F. is correct; once you publish something on the ArXiv, it's public forever.  (You can revise and even withdraw ArXiv papers, but older versions are still available if you know how to look.)  In that respect, posting to the ArXiv is no different from any other form of archival publication.

There doesn't seem to be any real restriction on publishing theses of any kind to arXiv. Therefore, whether you choose to do so is a decision that should be made between you and your advisor, taking into account any regulations your school may have. If your work has been funded by an external agency or company, you should also take their requirements under advisement.
However, so long as your topic falls under arXiv's category guidelines, and there are no restrictions preventing you, there isn't much to lose by submitting the final version of your thesis to a public repository. It would ensure far greater visibility for your thesis than if it's left on your university's website alone.


text:
How to write critique in a paper?
As part of the introduction of a paper I want to write some critique on previous research which was published at some reputable conference. It basically amounts to their research methodology being invalid. Their results are useless, because they did some things which basically amounts to cheating their scores. However they claim to be state-of-the-art. Now it takes a couple of paragraphs to explain what was all wrong with their work, which might clutter the introduction. The audience of the paper may not be familiar with the reason. My intention of the paper is to present something with a correct methodology.
The main point is: if you have some critique on related work, how do you include this in the paper? How polite should you be about the previous work?

If opposing the other paper was really the motivation, why not making that the foundation of your intro?

The main motivation for us was not opposing the other paper. Although if they did their work properly their might not have been a really good reason to write this paper.

First of all, I do not like the tone of your question (no offense). It seems like you are having a personal vendetta with those authors, which is a) silly b) unjustified (they did not anything to harm you personally) c) counterproductive for your purpose of publishing your work.
Let's summarize some facts:

However they claim to be state-of-the-art

Either they are or they are not. If this paper is not the state-of-the-art, you should compare your work against the "true" state-of-the-art. If they are considered the state-of-the-art by the community, you should acknowledge that fact. In fact, if this paper has obvious disadvantages, this is even better for you, since it will be easier to show why your approach is better.

they did some things which basically amounts to cheating their scores

You are probably exaggerating. Some kind of overselling results is normal, but you are implying malpractice, which is not that common. So, tone it down and try to express a cold, neutral and objective evaluation of the other paper, with lots of arguments and experiments that back your opinion in your paper. Also, when you are objective and not trying to trash the other paper, reviewers will buy more into your argumentation. Also, consider that the authors of this paper might also be: a) your future reviewers b) your future collaborators c) your future employers. So, treat your "opposition" with respect. This makes it easier for them to treat you with the same respect and more easily acknowledge and digest the fact that your method is better and their method is worst (they are after all a part of the same community), which makes future collaborations easier and improves your visibility.

As part of the introduction of a paper I want to write some critique
  on previous research

Critique is not a motivation. You should first discuss the problem, why it is important, very briefly what previous methods have done on this problem and then you say very briefly and in a very neutral way the shortcomings of previous methods (not just this one paper but all that have come before) and why your work will be better. Then you slightly augment this argumentation in the related work section (about their shortcomings) again neutrally. It is your experiments section that needs to truly show why your method is better and how much better it performs, only after very thorough and exhaustive experiments that will overcome every reviewers' doubts.
TL;DR. Keep your critique short, neutral and objective. There is not need to be humble about the advantages of your method but that does not need to be by trashing previous works.

Thanks, your concerns are completely justified, and that is actually why I ask the question here. I do not want to make this end up like a vendetta against the other authors. I want to be respectful to them, and have them learn from my input. But none the less I will still say their score is not valid, and I will be the one bringing that up. I fear that it is still really hard to formulate this in a way that they won't feel offended. One thing I consider is try to apply their model with my own methodology and compare it to the score I receive myself.

Include the critique (to motivate your material, and to demonstrate its relevance), be very polite (do unto others etc.), and don't put it too close to the beginning (since that is not the primary purpose of your paper).


text:
Changing methods/ methodologies mid-project
Is changing research methods/ methodologies in the middle of running a research project a good thing? Are there any best practices for doing so?
Links to projects that document a methodological shift mid-project would be much appreciated.

Could you provide a few more details regarding the project you are talking about, as I think the answer would vary a lot depending on that?

+1 for adding more detail as to exactly what you're looking for.

It is a project in social sciences and the methods/ methodology appears to be moving between case study research - action research - evaluations. I arrived mid-project and trying to make sense of it.

Do you keep a methodology notebook? If not, it is high time you start now.
It is important in the experimental sciences to always document exactly how the experiment is performed, and it is often recommended to keep a methodology notebook aside from your data notebook. All current and past/obsolete methodologies should be documented and dated (so it is clear exactly when your lab switched to a new methodology). All data on experiments should include reference to the correct methodology. (A lab wiki may be a good way to manage this.) For a bit more discussion you can see this guideline from the neurosurgery department of UCSF.
Changes in methodology may or may not be a good thing. A change of methodology obviously introduces a new variable into your research. And depending on the research outcome, the data pre and post methodology change may or may not be compatible, and it may or may not be ethical to present the data as one single dataset. So if your experiment only has limited number of runs for which systematic bias that may be introduced by the new methodology cannot be statistically ruled out, you may be better off not switching. (Unless, of course, you are in the biomedical sciences where sometimes methodological shifts are compulsory, even though it means essentially aborting the experiment.)
Methodological shifts are not forbidden per se, as long as all the methodology are clearly documented. The issue is more with how you interpret the data afterwards: it maybe necessary to present your data as two separate experiments instead of one single experiment. (Depending on your field there are different culturally accepted level of "fudging" when it comes to the methodology section of a paper; you should always have an argument handy as to why changing the methodology does not really change the experiment.) As long as each data point can be clearly referenced to the method that was used to obtain that data point, your experiment is reproducible and ethically you've covered your behind.
(This, of course, does not address the bureaucratic issue of whether your funding agency and such would frown on deviating from the funding proposal, and whether your research institution have specific guidelines concerning methodology shifts.)

Although my field is social sciences I found this very insightful, thank you. I especially take on board the one about clear documentation.


text:
Should one include grants that were not finished on the CV?
If one gets a grant, and by some reason (e.g., administration problems with the university) the project needs to be ended before the grant is over. Should one list such grant in the CV? or just let it go into oblivion?
If put it into the CV is OK, then should one state that the grant ended before its time? or even state the reasons?

The main reason to include a grant on a CV is to show that you can get a grant, which you did. Whether or not you made productive use of the grant is generally measured from the publications arising from the grant. You can provide explanations, if necessary, in accompanying letters -- a CV does not contain explanations, it just lists the essential facts.

To add to @user6726's great answer, I would further say that in what I've seen CVs just list the basics of the grant: funding agency, agency grant ID, title, date range, amount, and the role of the CV author in the grant, i.e. PI or co-PI. Often, people also list that they were part of the writing team of a large-scale or important grant even if they were not among the PIs in order to emphasize significant participation where agency regulations do not allow them to be otherwise included*. I rarely see the papers coming from a grant tied to that grant's listing in the CV or vice-versa. Each of the papers will individually acknowledge the funding source, but they are usually not tied together in the CV.
In your situation, I would list the grant with the amount that was awarded (not spent) and the date range that it was active with no further explanation unless it was killed by the funding agency. If it was, you might offer an explanation if you can keep it short. Otherwise, if someone asks about a grant performance period that looks short, you can wait until then to explain it.
*: NSF allows 5 people to be listed as PI/co-PI, but several of our grants have included more significant writers than that.


text:
Site with statistics of publications/citations per country?
I'm looking for a site (other than Scimago) that presents statistics of published papers and/or citations per country. However, I need more detail than that presented in Scimago. Ideally, I would like to have a list of authors, or the list of papers per country (having all the statistics that Scimago shows is a plus).
Is there any site that provides such information?

Dare I ask why you need this?

@JeffE yes you can ask. Actually, I'm doing some survey regarding the publication status of some developing countries, so I wanted more detailed information of the respective fields in the country. Such as active authors, and what are they publishing, etc. Thus, I don't think I will get a huge volume of data.

microsoft.academic is always a great resource. If I had the silverlight plugin I could verify that Academic Map is exactly what you are looking for.

@Gopi: That was a great comment; please add it as an answer.

@Bravo, as stated, I cannot verify what I am saying since I do not have the microsoft plugin (and do not want to install it) so I would rather have someone being able to verify it put it as an answer.

I think what you are asking can be carried out using Web of Science. I used address == "Canada" for the past 5 years, and immediately had published records for 241, 711 articles! You can ask for a citation report, which provides the information that Scimago has at the top. I think the issue you'll face is the sheer volume of data you're asking for. Even limiting the category to "ecology" (my field) yields over 3000 articles.
Of course, this answer won't be much use if your university doesn't have access to WoS.
The other thought I had was using Harzing's Publish or Perish (http://www.harzing.com/index.htm) which uses Google Scholar data. I tried a direct google scholar search, but can't immediately see how to limit it to articles published by people in the country as opposed to being about the country.
I hadn't heard of Microsoft Academic Search (see comment by Gopi) - so I had a look. The short answer is yes, it will show you publications by geographic region, but you have to go in by institution. You can get a google scholar like list of papers - and export those in various formats, but I only found the export option at the level of individual author.
For example, Université du Burundi has 16 publications by 5 authors, with an H-index of 4.
Pretty cool map though.

Adding to Gopi's comment, here's a snapshot of Academic map at work. I could only see the cumulative publication count in every field; but from the highlight of a few Indian universities I doubt if any quality measure has been considered at all. Also it lacks the cumulative country statistic and the citation counts you ask for.


text:
What is the difference between SCI and SCIE?
I knew that the difference between SCI (Science Citation Index) and SCIE (Science Citation Index Expanded) is that SCI has a list of top quality journals, while SCIE includes more than the former.
I found a link that seems to support this previous statement. However, I can't find any official information on this regard.
Does someone has some official links to what the difference is? if any.

From Thomson Reuters:

... the evaluation of and acceptance of a journal for the SCI or the SCIE is essentially the same with ONE major difference. The only difference is the storage media. SCI is only available on CD/DVD format; however, SCIE is available online.

This answers the question of why there are fewer journals in SCI. But it doesn't say why a given journal that is in the SCIE is or is not included in the SCI. It seems that Ishan's answer  touches on that: I.e., that SCI covers journals that are more highly cited in each category.

Thomson Reuters customer support explanation on SCI and SCIE:.

The Science Citation Index (SCI) is a sub-set of the Science Citation
  Index Expanded (SCIE), containing journals that rank competitively
  among the most highly-cited core journals in their category or
  categories. The Science Citation Index Expanded is essentially the web
  version of what used to be a database available only on
  CDRom/Diskette.
When selecting the journals for the Science Citation Index we choose
  the top journals from each subject category and supplement this with
  top regional journals from each category to give broad geographic and
  multidisciplinary coverage. The evaluation of and acceptance of a
  journal for the Science Citation Index Expanded or the Science
  Citation Index is essentially the same with one major difference.
This difference is in the application of citation analysis to the
  journal. While every science journal in our database is covered in the
  Science Citation Index Expanded and only those journals of relatively
  significantly higher citation impact are selected for the Science
  Citation Index. In other words, Science Citation Index covers only the
  most highly cited, highest impact journals in each category. This is
  because of the constraints of the CDROM and print media there is no
  difference in the selection process for Science Citation Index and
  Science Citation Index Expanded journals.

I think the correct understanding is that:
1) All journals in SCIE and SCI undergo the same selection process, i.e. the regularity of publication, the peer review process, the editorial team, etc. So you can said they all passed the "quality check" (this doesn't mean they are the same quality..., even not all journals in SCI are same quality, aka Science/Nature/PNAS vs PLoS ONE - which is better? why rank journals on impact factor or why even publish their impact factor if they are same quality?)
Now comes the difference ...
2) Every journals in SCI is in SCIE, but not the reverse. The reason is "only those journals of relatively significantly higher citation impact are selected for the Science Citation Index"
I think we can figure this out.

I got an explanation from Clarivate Analytics:
Based on the fact that Thomson Reuters selects journals of SCIE (including SCI) through a strict selection process, we hereby prove that journals of Science Citation Index® (SCI) and Science Citation Index ExpandedTM (SCIE) have the SAME QUALITY as the journal selection process for journals of SCI and SCIE is essentially identical.
The only small difference between of Science Citation Index® (SCI) and Science Citation Index ExpandedTM (SCIE) is the storage format. As known, both SCI and SCIE are available online. However, SCI is available on CD/DVD format but SCIE is not.

Another difference between SCI and SCIE journal is that SCI has non zero impact factor but SCIE journals are just ranked for impact factor.

Can you give a reference for this?

I think that the researchers who published their work in a sci journal say that the scie journals are of low standards.
As they have pulished in sci so sci is superior to scie.
But most of the phd scholars says them same with a difference related to media.