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What do I do with my advisees while on parental leave?
My wife and I have just been notified that we may get children for adoption in the coming month (apparently, it comes at a much shorter notice than having a biological child...). The law allows me to take about 6 months of parental leave, which I will probably need very much. At the present semester I do not teach obligatory courses, and my teaching duties are mostly to advise students in various levels:

I teach a new elective course for undergraduates, designed by me, where the grade is based on an individual project. There are 30 students.
I advise some 10 teams in their final-year projects; 30 undergraduate students overall.
I advise 3 master and 2 Ph.D. students.

Advising takes a lot of time for regular meetings and for reviewing the students' work. I spend about 50% of my time on advising (the other 50% I spend on preparing lessons for my course and writing papers). Most projects are research-oriented, and closely related to my field of research, so it is impossible to give them to another faculty member from a different field. Finding an external advisor from outside the university is also next to impossible. On the other hand, keeping the students "on hold" for 6 months is not fair for them.
During my parental leave, I can technically meet with students in Zoom and read their emails, but I will probably have very little time or mental energy for advising them at the same level they are used to.
Also, I heard that the law forbids me to do any work while on parental leave. But this can probably be solved in some way.
What do other advisors do with their students when they are on parental leave?

Others will probably not be bound by the same laws.

@Buffy right. But the main issue is practical, not legal.

What would happen if you were seriously sick and for that reason unable to work? Because you will be unable to work.

Does your university/department have any policies/guidelines about this?  E.g., the sabbatical leave policy at my US university explicitly says I am expected to continue advising PhD students, but not do other committee work.  While your situation is not the same, presumably it is has come up before at your university.

I don't know the Israeli academic calendar, so when is this non-obligatory course over? Although it seems odd to me to list teaching under "advising."

Also how old are the children you are adopting? People below seem to be assuming they are quite young.

First of all, in my experience, most people are quite understanding when it comes to parents taking parental leave, and many are also very supportive when you ask them for help.
My personal approach was to start preparations as soon as I knew that I would have to take care of a new-born child soon, giving me about eight months time. Basically, I think it is necessary to make use of your entire network to make this work out properly because let's assume that you will not be able to focus on anything job-related in the first months. So you will need a lot of support, and my recommendation is to accept any offer you get.
For students working on their Master's thesis (and similar projects), which usually takes something like six months, I simply did not accept any new students that I could not supervise. I do supervise quite a few students regularly, so I explained the situation to my superiors and thus made it their job to make sure that future students will find the support they need elsewhere. I understand that this will not work for you due to the rather short notice. But I assume there will be some procedure in case a student supervisor drops out for any reason, so you might have to rely on that. Again, you might find the students to be quite understanding and you maybe can work something out together.
PhD students are a different matter. My approach was to find very individual solutions. Some more advanced students were standing on their own feet anyway and had no big problem to fiddle around on their own for a while. These are the easy cases. For others, who were in need of more support, I tried to find it together with them. Some were involved in a research project with other collaborators. I found it useful to ask them to support the students. They might not be experts for the exact same thing, but they know the overall project, they know which ends should meet eventually, and they are great researchers with an open and active mind. Other students might have a special need for very practical, hands-on support in the lab, like for example a Master's student could provide. In such cases, I tried to find somebody from the faculty who would be willing to officially supervise such student work. PhD students might also be able to support each other. You could arrange that your students take part in group seminars of neighboring groups. Again, my experience was that all people involved knew that there was no real alternative, so everybody acted accordingly.
Honestly, teaching should be you smallest problem. Others should be able to take over your responsibilities.
I know it is not easy to let all this go for a while, especially if you feel committed to contribute to the success of the individuals involved, but if you have the chance to dedicate these months to your family, it is absolutely worth it.

Separating the different types of students is a key aspect. The undergrads work on projects on a scale of a few months but there are at a level where it is quite likely that other faculty members can take over. A PhD is usually a 3 to 5 year project. They should be much more independent but it is also a lot harder to find a replacement supervisor. They will still be around after the 6 months.

Indeed, so far my colleagues have been very supportive.

First off, congratulations.
Second, to answer your question, we transferred most of them to our colleagues. Adapting to live with children is a really big change. If you have the opportunity to have some time especially dedicated to that, then use it. Don't waste that opportunity on work.
Don't overestimate how much you can do in that period. It is not just the time you spent with the children, but it is also others things like many parents of young children will be seriously sleep deprived for the first year or so depending on how well the children sleep. Some babies cry a lot (that is pretty much their only means of communication), and don't underestimate how incredibly exhausting that is for the parents. I am not trying to scare you (really I am not).

How can you transfer a research student to a colleague, if the field of research is substantially different?

that depends on how substantially different, how specialized the students are, how willing your colleagues are.

Think of it this way: Over the entire time that you will work in your department there will be times when you have the capacity to fill in for others, and there will be times when others need to fill in for you. That is what colleagues are for.

Suppose they agree to formally be registered as the students' advisors for the coming months. Still, they will not have the time to study all the relevant material in order to provide good guidance. So the students will still be on their own.

You are human, you cannot solve all problems. Be open about it, in my experience students do understand that their teachers are human and sometimes have to prioritize other things than work. Whatever you are going to do will be imperfect, but live is imperfect.

The question here is: who will be with your child while you do this work?
Will your partner also be on leave? Will you be hiring a childcare provider while on leave?
If your child is under the age of 5, it's important to understand that working casually while you also look after your child is a fantasy. Young children do not just sit and play while you pursue emails or zoom, they very much demand constant attention. I'm not exaggerating at all when I say expecting time to even go to the bathroom alone is a stretch. Understand this first, then decide if carving out dedicated work time, including ensuring someone else is taking responsibility for your child for those hours, is worth it during a time when you are on leave.

Firstly, congratulations on your upcoming adoption.  I wish you and your wife joy with your new child.
I'm not aware of any laws that would make it illegal for you to help your students while you are on leave, but I would encourage you to take your leave seriously and ensure that it is not interrupted by unreasonable work expectations.  Leave for raising a child is important to you and your family and you are entitled to have that leave respected.
As to the mechanics of accommodating your students during this time, typically you and the department would make arrangements for some other academic to substitute your role with those students while you are away.  The department will probably ask you to arrange this prior to taking leave (if possible) but they should also be able to assist you if you have trouble finding other academics that can take on those duties.  Dealing with reallocation of tasks due to staff leave is a standard managerial responsibility of a university department, so it is certainly not incumbent on you to do supplementary work during your leave period to assist your students.  You are right that it is unfair to students to keep them "on hold" for six months.  It is the responsibility of the department to take whatever measures it can to avoid this.  Ideally your students will be fully cared for while you are away, but even if they aren't, that is a managerial problem that is incumbent on your department to solve --- it is not your job to work through your leave to fix managerial shortcomings of your department.
One other thing worth mentioning: You will find that some new parents go a bit stir-crazy spending their days at home raising a new child, and completely ceasing their professional work.  Consequently, sometimes people on maternity/peternity leave want to do some sporadic academic/professional work to break up the routine and give their brain some exercise.  That is perfectly healthy and I would encourage you to do that if you feel like it.  The point here is that you should not feel obligated to do your academic work while on leave.


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What is the meaning of the various postdoctoral job descriptions in the US?
As somebody who wasn't born or raised in North America, is there a schematic explanation what those various terms are supposed to be mean? Does it differ between the types of institutions? Are there specific fixed meanings to keywords such as

Assistant
Associate
Visitor
Fellow
Research

If there are not specific meanings, how do committees decide what to call a position?

No, there are no universally agreed standards for those titles.

Are you asking about titles or job descriptions?  They are not the same.  And ultimately neither means much.

Often their are policies at a university that determine what job titles are used for these kinds of positions.  Thus the decision might not be made by the hiring committee.  Unfortunately, since the answer depends on the rules at each university, there is no simple answer to this question.

I'm a bit confused. Are you asking (among other things) about the difference between "Assistant Professor" and "Associate Professor"? These are well defined in US.

As Jon Custer mentioned in the comments, there are no standards whatsoever, however generally speaking:

"Visiting" is a short-term position (I've never seen a post-doc with this title), probably even shorter than a usual postdoc, probably 9 or 12 months.

A "fellow" is usually a prestigious assignment, it may be a  university, college, or departmental soft-money position. For example, my university has "President's Fellows" although I'm not sure if they are funded specially or if that's just an award. However, nothing stops anyone from calling anything a "fellow."

An "associate" professor outranks an "assistant." However, I do not think there is any meaningful difference between "postdoctoral research assistants" and "postdoctoral research associates." One doesn't outrank the other. Probably, people just try to avoid using "research assistant," since that somewhat connotes an junior position.

Certainly not universal but it seems like "research assistant" tends to mean "graduate student" and "research associate" tends to mean "post doc". Anything else and you'd want to specifically say it is a post-doctoral position.

@BryanKrause Perhaps. "Research assistant" sounds to me like an undergrad without qualification

True, it does sound that way, but it goes with other graduate funding source titles like teaching assistant, program/project assistant, research assistant. TAs PAs RAs.

@BryanKrause Maybe. I don't have the same sense as you, it seems. I just looked it up, and a staff member in my dept (I'd hesitate to call her a postdoc because it is permanent) does seem to be a "research associate."

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What is the best way of keeping track of academic readings and persons?
I have started a brand new research from start of the year. I would like to know what are the easiest way of keeping track of the academic papers, journals and authors.
I use sites like Google Scholar, informatik.uni-trier.de for discovery of articles and following interesting conferences and people. I have used sites and tools like Mendeley and ResearchGate. I quite like the sites, but I am too reluctant to use them as for each of them I need to find everything by myself, create my own library to suit my interests.
I already got a warning by the stackexchange system saying The question you're asking appears subjective and is likely to be closed. but it would be great help if someone could explain some tools/software which do this?
Summarizing my questions:

How do you keep track of academic papers, authors effectively?
Are there any tools that can search/scrap the internet by some
keywords/name and keep track of them? [I know of
Google alerts, what
I seek is some kind of tool with a management interface]

related if not identical: http://academia.stackexchange.com/questions/5585/how-does-one-keep-herself-updated-with-new-research-without-forgetting-older-res/

Although you are aware of this already, I feel I need to state how satisfied I am with mostly using google scholar + a feed reader + a bibliography manager for this. Although it is not integrated, I don't currently feel any need to search for a better all in one platform.
I use google reader to subscribe to RSS feeds for online first and published articles for journals I am interested in (any reader which you can organize feeds into folders and search should be fine - I suspect many have better search capabilities that google reader). The vast majority of journals this is not much of a time suck to read all the titles and peruse abstracts I am interested in. The most prodiguous publications (e.g. Science/Nature) are only borderline annoying with 60+ posts a week, but even that is not that difficult to quickly navigate through.
I have a few fairly specific google scholar alerts (as well as general google alerts), so as to not get too much in my inbox. I basically have a few key words in articles specific to my research interest, and I have alerts for specific authors. I also have alerts to people who cite my articles.
I use CiteULike to manage my bibliography + personal database on my local machine to export various formats (e.g. bibtex or specific citation format). This has the added benefit that I can send articles directly from google reader to citeulike, but I suspect the same set-up could be crafted for other bibliography managers (Zotero, Mendeley) and possible other feed readers.

Basically in a nut-shell,

feed reader to stay up to date with newly published articles in journals I am interested in,
google scholar alerts for potentially related material that isn't in those journals, and
a bibliography manager to store articles to read later on.

Could you maybe link the RSS URLs for Nature and Science which directly lead to the latest articles? I have trouble finding them.

Added links as requested @zenbomb, they are a certainly a bit annoying to find. If you use google reader you can search for feeds, and using Google Chrome I have an RSS feed extension in the address bar that is available for the Science website. Nature has a ton of separate feeds, that I just happened to find by seeing a link to at the bottom of the home page at http://www.nature.com/.

Google Reader has discontinued. What do you use as a replacement?

@AlexeyPopkov - I use Digg reader now and I am quite happy with it.

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An academic who died over 70 years ago still has Google Scholar profile with verified email. How can this be?
I'm surprised to see that an academic who died over 50 years ago has a Google Scholar profile with a verified email (https://scholar.google.com/citations?hl=en&user=5qvdHjQAAAAJ):

How is that possible? I see the email domain, melipona.org, is some online shop.

On a more serious note, Google seeded Scholar manually with several famous historical scientists (Albert Einstein, Isaac Newton), although these are listed with "no verified email".

@ChristianClason Why is Newton's affiliation MIT, which was founded a century after he died?

I assume somebody is playing a joke on an automated system; presumably, somebody whose last name is "Newton" (and whose first name begins with "I") is working at MIT...

Verified email just mean that the user has done the confirmation in his/her inbox. It means in that case that the person that created this profile has an email with the domain "@melipona.org".
Usually, people will do this verification with their institutional email, adding credence that this is the right person, but technically, anyone within an institution can do it for anyone else inside that particular institution.

So this would appear to be an exceptionally obscure form of search-engine optimization spam?

That's amusing at least, given that he died almost half a century before people started to get email addresses on a larger scale. The person who confirmed his email address might have thought this amusing as well.


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Why does medical research have by far the highest retraction rate of any science?
Looking at the Retraction Watch Leaderboard,
knzhou commented:

the main common feature among the top 10 isn't that they're Japanese, it's that they're almost all medical researchers. Medical research has by far the highest retraction rate of any part of science.

Why does medical research have by far the highest retraction rate of any science?

Should we not be asking about the seeming interaction?

Not my field, but could it be that there is just more examination of claims due to the potential harm that failed research can cause? People can die when medical research is done poorly or the evidence doesn't support conclusions.

I'm not thrilled with the clickbait-style phrasing on the question. "Why does the top of RetractionWatch's leaderboard have so much medical research?" is a lot more honest of a question, since this is asking about 1 trend in 1 dataset, unscientifically gathered.

@user176372 I just took knzhou's comment and added a question mark.

My swag is that medical research probably has many more publications than many other kinds of research.

@ScottSeidman This. PubMed, the literature search engine for medical publications, adds 1.5 million new articles a year. Arxiv, which I'm taking as a proxy for "science which isn't medical" adds 190k a year.

@IanSudbery true, though OP was asking about the retraction rate.

@FranckDernoncourt, if all papers had an equal chance of retraction, just the imbalance is enough to explain the observation.  There's also a ton of money in pharma, so the motivation to cheat may get big.

@FranckDernoncourt the list you've linked to is ranked by number,  not rate. Its there any evidence that the rate is higher is medicine?

@IanSudbery good point indeed, you're right. No evidence in the question but the answer gives some.

@ScottSeidman thanks, the higher financial stakes would be indeed a possible factor.

@IanSudbery I would think that's probably a little rough. Many papers I work with are indexed in PubMed, despite not being medicine per se, and ArXiV undercounts many fields. For example, the ratio of Medicine:LifeSciences in the figure below is more like 2.7x rather than 7.8x

It doesn't.
That the authors with the highest number of retractions tend to be in the medical field does not alone indicate that the medical field has a higher retraction rate than other fields. Data from 2019 at this link from the NSF (https://ncses.nsf.gov/pubs/nsb20206/publication-output-by-field-of-science) shows that the "health, biological and biomedical" field publishes several times as many articles as any other field. It shouldn't really be a surprise that when a plurality of articles are in the medical field, a plurality of top-retracted authors are also in the medical field - you could select authors by any criteria you like and likely find that many of them are in the medical field.
Furthermore, looking at just the top 10 most-retracted authors is using a highly anomalous group of authors - the linked article states that the top fifteen offenders accounted for half of all retractions. The top-most retracted authors simply are not representative of the general group of authors, no matter what field they're in. Concluding that the medical field has a higher retraction rate than other fields because the top retracted researchers are medical is like concluding that Norwegians are in general better at chess because the world's top chess player happens to be Norwegian.
The data linked in the other answer (Grieneisen, M. L., and Zhang, M.. "A comprehensive survey of retracted articles from the scholarly literature." PloS one 7.10 (2012): e44118.) does suggest that the medical field does have a higher-than-average retraction rate, as evidenced by the fact that it is above the 1:1 line. But this phenomenon is not unique to the Medical field - Chemistry, Life Science, and Multidisciplinary Science all account for approximately 1/3 more retracted articles than their background prevalence. In fact, if you draw a line on the plot from the origin to the "Medicine" point, as shown in red below, each of those other three fields lie above that line - they retract articles at a higher rate than the field of Medicine.

Overall, I agree that the medical field does retract more than its share of articles. But the evidence in the question, as well as from my subsequent investigation, doesn't actually suggest the rate of retraction is "by far the highest of any field". The number of articles retracted in medicine is by far the highest of any field, but this is true largely due to the simple fact that the number of articles published in medicine is by far the highest of any field. But the rate at which medical articles are retracted is on par with, or even surpassed by, several other fields.

Thanks, great point.

Yeah, "by far the highest" is hyperbolic, at least going by that plot.

First, the best evidence I have seen that medical science has an above average retraction rate was published over a decade ago in Grieneisen, M. L., and Zhang, M.. "A comprehensive survey of retracted articles from the scholarly literature." PloS one 7.10 (2012): e44118. In particular, Figure 2 (reproduced under CC-BY) provides a striking picture:

Admittely, a plot with fresher data would be appreciated. One thing that is clear from more recent publications is that the retraction rate of medical articles has increased during the last 20 years, see for example Fernandes, Bianca Barros Parron, et al. "The Secret Life of Retractions in Scientific Publications." Principles and practice of clinical research 9.1 (2023) (PMID 37693831) and references within. That editorial also highlights the different rates among medical subfields: oncology has 2.8 times the number of retractions of anesthesia despite the top three on the RetractionWatch "leaderboard" being anesthesiologists. The editorial also claims that the majority of retracted medical articles were retracted for plagiarism, and that the retraction rate for plagiarism has been rising. (The same may have happened also in non-medical fields, but I haven't seen comparable results.)
The causes of differences between fields are less clear. It has been noted that, on a journal level, there is a link between retraction rate and impact factor. Besides the potential increased willingness to bend the rules in order to publish in a high prestige venue, the higher impact factor may increase the readership of and scrutiny on individual articles. If the same principle is extended across entire fields, well, medicine tends to have the highest impact factors, which could inflate the retraction rates.
The following are additional potential causes that I consider plausible, but which I'm not aware of compelling evidence for. First, there is the perception that the consequences of research that is wrong can be quite dire in medicine compared to some other fields, which could lead to higher post-publication scrutiny and willingness of journals to retract flawed papers.
Second, there is the issue that, at least from the perspective of a physicist, medicine studies horrendously complicated systems under conditions that often can't really be controlled, so the rate of honest errors and nonreproducible results may well be higher than in some other fields. Training (e.g., in good research practices and methods) could be another factor, but not one I have any real insight into.

Honest errors may occasionally result in author-driven retractions; non-reproducible results really never are handled with retraction, that would be the wrong mechanism for that particular problem. I think the explanation that errors in the publication record in medicine are seen as more important to correct is a better one, but "the majority of retracted medical articles were retracted for plagiarism" is an important data point that suggests this is mostly a cultural thing, my guess would be pressure on medical students to publish who are not really interested in research.

That plot actually suggests to me that the retraction rate in Medicine is actually not all that much higher than Chemistry or Life Science. Each field accounts for roughly 1/3 more retracted articles than their baseline prevalence - these look like roughly equivalent retraction rates. The share of retracted articles which are in the medical field is high mostly because the share of all articles which are in the medical field is high. Although the retraction prevalence in medicine is higher than the background,  we also see that in other fields.

@NuclearHoagie It would be quite interesting to know how the rates vary within those fields, e.g., are there differences between say inorganic chemistry and biochem?

@BryanKrause I was thinking of examples such as this author-driven retraction, where the conclusion changes after more data. The pressure you mention is definitely an issue, and I would guess it is driving the rising number of retractions in some countries, but I'm not sure how it could be compared between fields.

@Anyon I guess it does happen. Ordinarily, though, it would not be appropriate to retract the initial paper if the initial data themselves and conclusions based on them are not flawed. That does not prevent publishing additional work with additional data that refutes the previous work. In an ideal world, both are published and inconclusive results are published as well so that all obtained data can be used together in meta analysis.

Note that the figure you include suggests that the rate of retraction may not be higher in medicine, and it certainly isn't highest "by far" as the original question indicates.  In fact, without actually doing the math, the rate may be highest for Multidisc Sci., which has the smallest denominator

I suggest that increases in the last 20 years possibly involve the shift from paper libraries to electronic access and tools like plagiarism checkers available to just about every reader.

Some possible factors: more scrutiny, high number of medical papers, higher financial stakes (big pharma) and medical authors often don't have much research training.

Not my field, but could it be that there is just more examination of claims due to the potential harm that failed research can cause? People can die when medical research is done poorly or the evidence doesn't support conclusions.  Buffy (Commented on Jul 31 at 20:21)

Note that this is a leaderboard sorted by the number of individual retracted articles. Maybe something about medicine lends itself to enabling multiple publications based on a single set of data, meaning that one instance of fraud can have a wider range of repercussions than in other disciplines. (Reddit user pacific_plywood)

My guess is that most doctors haven't really gone through a research program in grad school, and then they got tossed into it. An MD != a PhD. (Reddit user Eccentric755)

There's also a ton of money in pharma, so the motivation to cheat may get big. Scott Seidman Commented 2 days ago


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How important are poster sessions in conferences?
Many times I've attended and will attend international conferences presenting a poster in my life.
I used to think that this poster works have been considered less important than scientific papers or oral communications, but important anyway for scientific divulgation.
So, when presenting a poster, I've always been thinking: "Okay, it's not as important as a oral communication, but, if they accepted it, this means they found it interesting".
Then I read the "Ten Simple Rules for a Good Poster Presentation" article by Thomas C. Erren and Philip E. Bourne, and I was pretty disappointed after reading point 4:

Rule 4: Poster Acceptance Means Nothing
Do not take the acceptance of a poster as an endorsement of your work.
  Conferences  need attendees to be financially viable. Many attendees
  who are there on grants cannot justify attending a conference unless
  they present. There are a small number of speaking slots compared with
  attendees. How to solve the dilemma? Enter posters; this way everyone
  can present. In other words, your poster has not been endorsed, just
  accepted. To get endorsement from your peers, do good science and
  present it well on the poster.

Do you agree with this statement?
What is the overall importance of a poster session during an international conference?
Is is just a way to collect subscriptions and money, or is it an important occasion for science divulgation?
Thanks
Edit: I'm speaking about poster session vs. oral session, I do know that a poster with presence is better than nothing. As Woody Allen once said: "The 80% of success is just showing up" ;-)

Acceptance of a talk isn't an endorsement either (except in some disciplines like CS where giving a talk is conditioned on successful peer review of a paper).

This is very boread: what subject do you speak about? I've never attended a conference with poster sessions (and I gave many contributed talks) because of my subject. My colleague-next-door has never given a talk (and has made a lot of posters instead) because of his subject.

It's both, they get money and subscriptions, poster presenters get the chance to get some visibility, which may mean citations (not to their poster, but related papers), which means a better h-index, because it's all about impact. Anyway, the visibility pays-off when there is something to make visible, and a poster is not that thing, but an advertisement of that thing.

@DavidKetcheson: Poster papers in some CS subfields are usually peer-reviewded, as well. It's a brief, more superficial review, and the expectations the paper has to live up to are lower, but some submitted poster papers nonetheless get rejected, so the rest could be said to be endorsed to some extent.

@O.R.Mapper: It's worth noting that at some CS conferences, you don't submit a "poster paper" per se, you just submit a paper. You might then be asked post-review to present it as a poster rather than a talk, but the level of peer review involved is no different than for any other paper.

Of course, conference papers in general tend to be reviewed more superficially than journal papers, simply because of the time constraints involved (I've seen people have 6-8 papers to review in a few days), but at the kind of conferences I've attended, both poster and oral papers have been subjected to exactly the same peer review process.

A poster session is a good way to disseminate your work: but it has nothing to do with how you get credit for your work.
Some computer science venues have moved to a model where papers are reviewed and accepted, but the vast majority of papers only get a poster presentation at the conference. Another model is where all accepted papers are invited to a poster session. So it really depends on your area and venue.

Is poster session a good way to disseminate one's work? A talk means (say) 15min x 100people, a poster means 3min x 10people (optimistically). And in the later case, they are distracted by many things.

The right comparison here is not poster vs talk, but poster vs nothing.

Um, have you carefully observed those 100 people - probably 5 are NOT checking email, surfing, making their own slides, or ... And in cs conferences, 100 people for a talk is a large factor over estimate

@Suresh I'm aware of it. But it's easier to estimate effective attention going the other way: for an each day of a conference, I effectively pay attention to 5h of talks, and say - 20min of posters. Of course, it's a very rough estimation, but still there is one order of magnitude of difference.

In a good 6 hour poster session, you can get up to 50 or more people. Busy posters have 10+ people listening at all times.

It might be better if things change in the direction of making "posters" and "poster sessions" have greater weight, but, at the moment, in "research" mathematics, I fear this is not so. (This does not deny that undergrad "research" is typically showcased in exactly this way.)
The questioner's potentially-cynical-sounding quoted "market analysis" is I think perfectly correct, if slightly exaggerated. That is, every enterprise "needs to" support itself, and this is typically by giving larger numbers of people the impression of participation.
I have no experience whatsoever of anyone in graduate admissions or post-doc hiring or... caring at all about any poster-session contribution. A "contributed talk" is also of essentially zero weight, exactly (as other answers mention, and the question anticipates) there's no filter (a.k.a. "peer review").
On the other hand, "doing things", as opposed to "not doing things", is a plus. Passivity and quietude are vastly less valued than activity, whether peer-reviewed or not. Ok, the market drives certain conceits, so don't be fooled by these, but, still, "being seen" is a good thing. Maybe not a resume-padder, but better than not being seen, by far.

My personal experience (atmospheric science / remote sensing) is that poster sessions have little significance. You can present your work, maybe you will have some interesting discussions with scientists or get interesting ideas from others. In my field, posters are not peer-reviewed and virtually always accepted, if not clearly off-topic or rejected for political reasons. For me, the main point of going to a small (<300 people) conference where I have only a poster is to be able to speak with famous scientists in my field (who of course have talks), do networking, etc.
My advice: do your best on your poster, make it informative and attractive (not too much text please!), but don't expect a huge attention or exposure. The conference consists of more, much more, than just the poster session where you present your work. Use the opportunity to be with senior scientists in your field!

This is extremely off-topic, but I'm always surprised at how big some fields' conferences are (I'm in math).  I've only been a handful of conferences with >300 attendees and have thought they were uniformly awful.  <50 seems quite normal to me.

The American and European Geophysical Union annual meetings have >10,000 attendees, but at the particular specialised session you still meet the people from the narrow field of specialisation.

I will speak toward my experience, as a poster presenter, and a poster reviewer. My experience is primarily in the domains of Epidemiology, Public Health or Medicine so take that for what you will.

"Does this mean they liked my work?". It means they don't hate your work. While conferences do need people, and their only rate-limiting factor is the size of whatever room they're having the poster session in, they don't accept all posters. I've reviewed posters, and some of the posters I marked down heavily didn't end up getting accepted. Admittedly, you'll see reject rates of like 20-25%, but that's still not nothing.
"Is it as good as a talk?" Probably not. But keep in mind an abstract gets accepted as a talk because it fits two criteria: Quality and Theme. The talk has to be good. But as importantly, the talk has to be on a subject that fits well within a session, so an organizer will grab it. It's possible this doesn't happen, even if your abstract is amazing - sometimes, it just doesn't fit in somewhere.
"Is it important?" Yes! It's not the most important thing you've ever done, and it's not going to change your career. But from standing next to posters I've gotten complements - and critiques - of my work that have made it better. I've made contacts that have turned into collaborations. I've talked to important people, and had my work in front of them. Someone I know got a "Here's my card, why don't you shoot me an email after the conference..." Admittedly, I've gotten all that from talks as well, but a poster isn't just some sad way to justify your registration fee.

I would guess that this depends on your domain. In computer science, talks at conferences present peer reviewed papers. Posters are also reviewed (e.g., ICST 2011, SEFM 2010). However, in my experience, there are not that many candidates submitting posters, i.e., the reviewing may be less stringent. At some conferences, posters are combined with, e.g., tool exhibitions and/or doctoral symposiums. Advanced PhD students are sometimes encouraged to prepare a poster and to give an overview of their work so far.

One thing that seems to be missing from this discussion is the maturation process of a research effort.
A poster session is ideal for the early stages of the research, when you may not have much more than an idea, and you stand to benefit a lot from discussing your idea with other researchers from the same field. You may get some valuable pointers, and perhaps other conferencegoers will find your idea interesting. I've had some productive conversations with presenters at poster sessions.
A conference talk is better after you have some findings, formed some conclusions, and your are ready to present your results to other experts.
If you have a chance to collect even more data to bolster the validity of your research, you could eventually get it published as a journal article.
So, if you've been working on something for six or seven years, then, indeed, a poster session wouldn't be anything to write home about.
I agree with rule's overall sentiment: Poster Acceptance Means Nothing. In other words, a dozen poster acceptances won't put you on the fast track for tenure. However, that doesn't mean the activity has no value. Poster sessions can be especially beneficial for budding researchers, getting them used to talking about their research with experts from outside their university – maybe for the first time. Plus, some conference attendees will be interested in what they might see talked about at next year's conference.
So, are poster sessions a crowning acheivement? Hardly. But they still can be a productive stepping-stone, which is why I think it's sad when they are looked down upon.

Sometimes a poster session is better than an oral presentation due to time constraints in the latter. During a typical oral presentation you will have 10-15 minutes for questions and comments while a poster session lasts for few hours, allowing for more in-depth discussions.
Moreover, not all people will manage to make it to your oral presentation because there will probably be many panels running in parallel. Poster session will typically run after all oral presentations have been finished.

Recently, several AI/CS conferences, such as AAMAS, or IJCAI put quite a bit of weight on poster sessions. Either each paper is required to be presented as a poster as well (AAMAS), or only selected papers get oral-only presentation and the rest poster-only presentation without making any difference in the conference proceedings (IJCAI). Poster sessions serve for dissemination of good quality work, being either promising, but still relatively preliminary, or targets a narrow audience, instead of general community.
Personally, when planned and executed well, I find poster sessions very useful and  at times even more useful than plain oral presentations. Interactions by posters allow for more involved discussions with the authors. Of course this requires a good thought at logistics of poster sessions from conference organizers.

I basically agree with Rule 4, and analogously feel that giving a contributed paper doesn't count for much (and carries almost no evidence that your work has been vetted).
However, I would encourage you to see a poster presentation (or giving a contributed paper) as an opportunity to practice your presentation skills.
One advantage of a poster session is that you can try explaining a concept in different ways, and see which explanation is most well received.
Although you're obviously honing your ability to communicate verbally, you should also be honing your ability to present information visually in a simple way.  Many of the same principles that make for a good poster also make for good slides.  And these principles are far from obvious to most people when they start out.

I'd say that there is a big difference in breadth vs depth. If you have a paper on a broad subject that is interesting to 50%+ of the researchers in that conference, then obviously a speaking slot is needed, but if you have some advances that are important but in a niche that really interests 5% of the attendants... then a poster would be more efficient in dissemination than a speaking slot.
I've been to conferences where I'm interested in something like 5 out of 50 posters, but those 5 topics were very important to me - it's impractical to have everyone speak, but it would be bad if those poster presenters wouldn't be there.

It's very field-dependent and conference-dependent. I can only answer based on the field in which I work (computer vision).
Generally speaking, the way big computer vision conferences like CVPR work is that you submit a paper, which is peer-reviewed, with the reviewers indicating whether they feel your paper deserves an oral presentation, a poster or rejection. In terms of prestige, it's seen as being distinctly better to get an oral presentation than a poster, but getting a poster is a non-negligible success: the important thing is that your peer-reviewed paper got accepted, and will be published in the conference proceedings. Indeed, most of the papers at conferences like CVPR are presented as posters rather than talks, but they're still very much seen as high-quality work.
Unlike in fields with different conference cultures (e.g. that mentioned by @J.R.), you won't get to present a poster at a conference like CVPR if your work is at an early stage: you'll just get your paper rejected. It's certainly not a medium for disseminating incipient work. Moreover, if you have twelve CVPR papers, most people would think you're doing pretty well, regardless of whether they were presented as talks or posters (primarily because in this context, poster acceptance => paper acceptance, and papers at major conferences are valuable).


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In APA, how should stylized business names be capitalized?
Numerous companies stylize their names or the names of products: "adidas," "eBay," "iPhone" ... how should these be written (in APA style)?

The pair of adidas shoes lasted longer than the pair from Nike.

vs.

The pair of Adidas shoes lasted longer than the pair from Nike.

The Wikipedia Manual of Style is pretty explicit on the topic, but the APA is less clear.  4.16 says to capitalize proper nouns and trade names, but doesn't explicitly refer to stylized trademarks.  My instinct says to capitalize them as unstylized proper nouns, but other manuals of style actually address the topic, even if it's a bit confusing on first read.  For example, the Chicago Manual of Style (search for "business entities" in the page for the specific rules) says to follow camel case capitalization, but for all-caps or no-caps, to title case them (adidas becomes Adidas, LEXIS-NEXIS becomes Lexis-Nexis, DirecTV stays as such).

It's not definitive, but the APA Style Blog has a page on citing mobile apps that uses "iPhone" rather than "Iphone", etc. It's probably the closest you'll get if 4.16 is that vague. I don't have an APA style manual, so I can scour it for better answers.
If this is for an assignment, you're unlikely to get dinged hard for it if anyone even notices. If it's for a journal that follows APA, then you'll get instructions back from an editor if they want a change. If it's for some other writing, you can work with whoever it's going to in order to get it to meet their standards.

I just asked @APA_Style via twitter, which is managed by the APA.
Their answer is no, you should not capitalize those stylized company names that start with a small letter. Additionally you might want to avoid starting a sentence with those names as to avoid confusion by the reader.
In general they seem to suggest to leave the names as they are.
You can find the conversation for references here: https://twitter.com/APA_Style/status/621340750505242626

The intended content of this answer is upvote-worthy, but unfortunately, I find it very unclearly written. In fact, they seem to be saying on Twitter that you should stick with the original stylized capitalization. Hence, a name that, in its stylized form, starts with lower case should, as they and you say, not start with a capital at the beginning of a sentence. However, consequently, that means IMO that in a name that is stylized to start with, or contain, a capital, the respective letters should very well be capitalized.

@O.R.Mapper you are absolutely right. I did not think about that when writing the original answer. I edited the post now to try to clarify that issue.


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Waiting after a review
Regarding
this question on when to ask about a manuscript's status in review
I wonder (since it is happening to me): What does it mean when a paper is "with editor" for two months after a first review?

Seems a bit too broad because it can mean a lot of things. It would help if you could be a little more specific. For example, you may specify which field the topic of your paper belongs to (e.g., it can be math, comp sci etc.) and how the first round review went (e.g., it may be conditionally accepted. Or maybe you're asked to revise the manuscript extensively.) Did you receive the decision letter after the first round and resubmit it? Or is it just the status has changed to "with editor" from "under review" or the like?

"Or maybe you're asked to revise the manuscript extensively" That is!

Related. http://academia.stackexchange.com/questions/900/when-how-should-i-ask-about-a-manuscripts-status-in-review

So, after the first round of review, you were asked to revise your manuscript extensively. And you made changes accordingly and resubmitted a revised version. Two months has passed since then, but it doesn't seem like the revised manuscript has been sent out for external review because the status of your submission you can see online hasn't been changed and is still "with editor." (Edit: I know some journals use "being handled by editor" or something similar at any stage of the review process except when the manuscript is with the author. You're sure it wasn't "with editor" during the first round review, right?)
If that's the case, most likely it means the editor is having hard time finding referees for the second round or maybe simply taking their sweet time examining your resubmission. Or possibly they forgot about your submission so you need to remind them.
I don't know what the norm is in your field. But if I were you, I'd send a short and polite email to the journal to ask what is up with your paper, probably after waiting a bit more. If it doesn't work, I'd send another polite email to someone else working for the journal. In any case, you should understand that the editor is a volunteer (unless you're submitting to a journal with fulltime editors like Nature, Science, PRL etc.), and sometimes it takes a while to handle your submission for various legitimate reasons. So be polite when asking what's going on.
Edit: And the best way to know if two months is too long is to ask experienced researchers in your field like your advisor if you're a student.

There's no way to know for sure except to ask the editor.
If you mean that the editor received the first review from a referee two months ago, it may be that the editor has not yet decided what to do with the paper, based on the review.  Another possibility is that the editor wants a second review, and has not yet found a referee for it.

The situation is that I sent a second version two months ago after a first referee's review. I'm sorry if I didn't express it correctly.

It most likely means that your manuscript is undergoing a second round of review, after you made revisions to it. In most fields, two months is not overly long time to wait for reviews, especially if you made large modifications to the manuscript, or if the editor is not sure what to do and asked for an additional referee’s opinion (or adjudicating referee, in some cases).
You can, however, write a nice email to the editor enquiring about the status of your manuscript.

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


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How to overcome preconceived ideas about social scientists?
I have the opposite problem to this question. Often when I talk to someone from a 'hard' scientific field I am 'taught' how statistics work or how programming works. It is a bit like being mansplained but by a hard scientist (hardsplaining, would that be a word?). Once someone was surprised that I know what the Runge-Kutta method is, and I have lost the count of how many times I have been lectured about stuff like the normal distribution and inferential statistics.
Now, I work with quantitative social science, using statistical methods that many would consider quite advanced (e.g. exponential random graph models for social networks, panel econometrics, simultaneous equations) and had the necessary mathematical training for that.
I am also very familiar with several programming languages. I usually write a lot of code in R or Python, besides being proficient in statistical scripting languages like Stata. I also know a good deal of NetLogo and Java, which I used when I did agent-based modelling. I would write my stuff in Sweave and LaTex if most journals didn't ask for a word document.
My understanding is that precisely because of the observational nature of most social science data, those of us who are into quantitative methods are forced to learn very advanced techniques to deal with issues such as selection bias and unobserved heterogeneity. Furthermore, the intrinsic 'messiness' of social data means that we have to be quite good at data management, usually learning a programming language or two in order to clean our datasets. Moreover, the emergent nature of social phenomena has motivated many of us to use multi-agent simulations in our work, demanding us to learn how to program.
Yet, I get patronised by the person whose randomised experiment allow them to get away with a t-test. How to react when that happens without sounding too defensive?
I know that generations of armchair sociologists theorising about the social construction of this and that probably created this stereotype of the mathematically inept computationally illiterate social scientist, but I believe that this image doesn't reflect a great share of those in my field.
EDIT 1: Given the close vote, I'm adding this clarification to what I'm asking. I want to know of strategies, possibly by others in a similar situation, to assert their research credentials or skills in a friendly manner in a social situation where the phenomenon described happens. The type of prejudice that I describe sometimes leads my opinion or ideas to be disregarded because of judgements made based on an incomplete image of my field of study. I believe that there are others there in a similar situation (Economists, for example), who may have strategies to cope with it. There must be a nice way to convey one's competence past the initial impression caused by the stereotype.

I don't think this problem is really academic in nature. After all, it's hard to treat others as individuals, and applying stereotypes based on some simple traits is much easier. If there were a straightforward answer to this question, then things like racism or sexism would have become bygone issues of our society. You would think that scientists could do better than that...

But there's gotta be a way to go through such situations or perhaps avoid them. Introducing myself as a statistician would be lying, but there may be a way to convey the "I'm not that kind of sociologist" line smoothly.

How about calling yourself a "quantitative sociologist"?

I have to confess that usually forget the 'quantitative,' but I sometimes wonder if it would make a difference.

@Drecate: Sure, the problem of prejudices isn’t academic in nature, but this specific prejudice is and there may be specific strategies for dealing with it.

On the same renaming note suggested by @paulgarrett how about calling yourself a "data scientist, (with specialty in societal systems)"? Or an "applied statistician"?

I'm not fully understanding your question. How does the "hardsplaining" come about? I don't suppose your conversations at parties go like this: "Hi, I'm a sociologist." - "In that case, let me tell you about the t test." Something must have motivated the hardsplainer to start hardsplaining. Did you tell about your data analyses? In that case, anyone with even a passing familiarity with stats should realize after about ten seconds that lecturing you on the normal distribution will not be helpful. So I think I'm missing some context here. Could you elaborate?

You are correct. One example is when I mention that I use statistical models in observational data and describe my findings. Once the response was around 'correlation is not causation, let me tell you about spurious correlations.' I had to explain how econometricians try to deal with these by using panel data (e.g. fixed effects for unobserved heterogeneity constant over time) and quasi-experimental models like instrumental variables regression. Would it be a critique to what I do, I would take it better, but it is usually a lecture departing from the assumption that I don't know simple stuff.

@Kenji Both answers already there seem pretty good, get in there first. Imagine yourself on the other side, someone, say a Phd student you're talking to starts talking about problems you know exactly how to solve but doesn't mention any of the keywords. They might have spent every evening since they were 12 reading books on econometrics but unless they mention any of it you don't know. You could assume they're all secretly masters of the craft hitting no common problems and remain silent for fear of them getting offended but that would be kind of a dick thing to do.

@Murphy That is a fair point, although I wouldn't assume that they are in need of being taught unless it became pretty obvious. It is not like I'm saying "huh, I study Y and I use some numbers and the point and click software to get a table with stars." If I say that I'm employed at a national university to use statistics to study problem X, I would hope that the interlocutor would at least expect me to know the basics of stats.

Roughly speaking that matches the job description of half my department and "point and click software to get a table with stars." isn't so far off what a reasonable fraction do so expecting people to infer that you're definitely in the other part may not be reliable. Thinking back, if people lecturing bothered me I'd be bothered a lot (I actually like when someone starts lecturing on things I'm interested in and don't know) but I think simply quickly waving off the start of lectures on things which I already know about saying I know about them makes the lectures go away before they bother me.

This question is interesting to me, as I work on very similar questions to what you do. I’ve noticed a massive difference in how other scientists respond if I say that I’m a “computational social scientist” vs if I say that I’m a “mathematician.” I tend to go with the later, as that’s my degree and my underlying interest. I just happen to develop computational methodologies for social science research right now.

I get patronised by the guy whose randomised experiment allows him to
  get away with a t-test. How to react when that happens without
  sounding too defensive?

I think this is the key aspect in your question. Once the "hardsplainer" starts patronizing you, you are on the defensive. And there is really no good way out of this situation once you react by starting to defend your methods.

Sometimes the hardsplainer will realize that his assumptions were erroneous and that you may indeed know more about stats than he.
Or he will in turn get defensive and start nitpicking your methods, probably getting in deeper and deeper water as he is discussing stuff he may not know much about. This is not a good conversation to have at social gatherings.

I'm afraid the second possibility will happen rather frequently, simply because people are not good at revising preconceived impressions.
So I'd recommend that you nip the problem in the bud, by not allowing your interlocutor to, in fact, preconceive the impression of "look, a social scientist, who probably doesn't know anything about statistics". Specifically, when you discuss your work, invest half a sentence to name-drop your analysis techniques.

I'm looking at how foo relates to bar. Because I only have
  observational data, not experiments, I use econometrical panel data
  models, and I find that...

If you hint that you use advanced models right before the hardsplainer can get the wrong impression that he can lecture you with fundamentals, he will be stopped cold. (Of course, you don't want to overdo it to come across as an arrogant know-it-all.)

Yes, it would be nice if this were unnecessary, because people didn't have the preconceived notion that social scientists are inept in terms of statistics. Unfortunately, this notion does have a basis in facts. I do statistics for psychologists, and I see that while they do get a solid grounding in statistics, they do frequently misapply models, or interpret them incorrectly, or don't understand why p-hacking is a Bad Thing. Then again, some hard scientists do suffer from the delusion that being an expert in some hard science means that they automatically also are experts in statistics.

The point to avoid "defensive-looking" is to treat the hardsplainer as if he were interested in the OPs methods. I personally found that giving these guys fine technical details is just the right level to get rid of the the disingenuously involved and keep the seriously interested on board for a serious scientific conversation - if the hardsplainer would find it arrogant, it says more about him than about the OP.

@CaptainEmacs: as to appearing arrogant, I'm more worried about innocent bystanders. After all, I'm advising on how I'd act before I even know who I'm talking to. I'm standing at a party with four people, none of who I know, and everybody introduces themselves. We need something that keeps a potential hardsplainer from hardsplaining, while not coming across as arrogant to the non-hardsplainers in the group.

@Kolassa That's exactly the point: you treat them as if they are interested in your methods. If they are, great! If they are not, and just are there for show-off, they'll drop out of the conversation. You will be the person, however, that treats them under the assumption of respect by default.

There is an important aspect of this dilemma which I did not see stated in your question: why is the opinion of the "hard-splainer" important to you?
Depending on the answer to this question, there are a number of different approaches that you might take.  Although I am in a "hard" field myself, I face similar dilemmas in my interdisciplinary work, as I find that some researchers often dismiss or misunderstand computer science as "just data analysis," since their own experience with it has been largely limited to simple uses of Matlab, Excel, or specialized data analysis programs.
I have found that it is useful to develop a spectrum of responses, depending on my degree of investment in the interaction.  From least to most investment, these are approximately:

Nod and smile. When dealing with a random boor in an airplane or at a conference cocktail hour, I may simply choose to not engage. Why should I care what a fool believes when they cannot even bother to draw breath long enough for me to speak?  So I nod, smile, say something politely vague, and then go to refill my drink / take care of some work / whatever.
Turn the tables. If the person seems worth talking to and capable of listening, but is uninformed, then I'll turn it into a teaching moment:

"Ah, it sounds like you're suffering from some common misconceptions about [subject]..."

It's good to spend some time with philosophy of science and the history of your field, in order to understand why things are the way they are.  I have some favorite examples and anecdotes, mostly having little to do with my own work, which help illustrate the base pop-science-level points I'd want to make.  Don't be defensive: instead, have fun sharing your love of the field and its complexities, and your conversation partner is more likely to enjoy themselves too and actually learn something about your field.
Face the problem head-on For people whose opinion really matters to me, such as potential collaborators, program managers, and decision-making committees, I often actually have pre-prepared slides or, in some cases, actual published papers.  You don't have to listen to a lecture, but instead say something like, "It sounds like you're concerned about [issue]," and then head for your careful "101-level" explanation of how that issue is approached in your work.  Preparing material of this type can actually be a surprisingly valuable exercise for yourself as well: I have found that many of the assumptions of my field, while valid, have a much more complex backstory than I commonly think about while working within those assumptions, and taking time to understand them has opened up new knowledge and opportunities for me.

Given the example you indicate, how about: "Yeah, a t-test is probably just fine if one has good data. But if you have really bad, realistic, data, you need much more sophisticated methods such as ..."
Ideally mention computational methods the techo (the "techno-macho", or hardsplainer in your language) is not likely to know or understand. If they had only sought to show off their superiority, that'll make them go away.
And if the person is seriously interested to learn, then, that's fine, too. In this case, go forth and explain.

I think this is why some people in biology started calling themselves mathematical/computational biologists. Then you also have bioinformatics people. Mathematical finance is a discipline. Etc. I'm pretty sure people changed their title for this very reason, and I think the quickest change is to change your informal title. If you just say you're a "mathematical/computational/statistical/quantitative __________" it likely sparks interesting conversation towards the direction of your research.
And if anyone is being a patronizing idiot, throw it right back at them. They're using a t-test? "Why wouldn't you be using M-estimators or a Bayesian model with t-likelihoods with the degrees of freedom as a hyperparameter? Your data seems like it would have outliers and so such basic statistics probably don't apply." If they don't get the point, they likely aren't worth talking to.

Let's say you and a hard scientist have just struck up a conversation.  Before saying anything about your work or position or department, make sure to find out a fair amount about what he does, and what statistical or computational methods get him excited, so you can tailor your remarks to his own provincial world view.  (I'm saying he on purpose, because I suspect the behavior you described is more common among men.)  If he peters out and pushes you for information before you've gotten enough from him, say something vague or even misleading, to throw him off the scent of social sciences, so you can get him to talk excitedly about himself a little longer.
When you're ready to start talking about yourself, say something that allows him to view you as a member of his own subtribe.  Your remarks might be a little bit disloyal to your fellow social scientists, but hopefully you can live with that, since this is an informal one-on-one conversation.
For example: "My work is inter-disciplinary.  I use such-and-so techniques that have been long established in the hard sciences, and apply them to interesting problems in the social sciences."  Raise your eyebrows a little as you pronounce the phrase social sciences.  It needs to have just a whiff of a skunky odor in the way you say it.
If you want to go a little further -- "It is remarkable how much can be accomplished by bringing rigorous statistical and computational methods to bear in previously unplowed fields."
(If the conversation eventually leads to criticisms of your area that are uncomfortable for you to hear, you may then safely establish your respect for your colleagues, for example: "You are thinking of the social sciences of 20 years ago.  Actually, there are many researchers engaged in rigorous work in the social sciences currently.  I am not the only researcher in my field applying sophisticated mathematical and statistical techniques to complex social science questions."  Then you could rattle off some names.  Not to convey meaning necessarily -- but to intimidate.)
Please do not take the arrogance and lack of humility of some hard scientists personally.  It's really their problem, not yours.


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Is there away to know who has published several high quality papers in a specific academic field/area during the last 5 years for example
I am trying to submit a paper for publication. The journal is asking to provide a list of experts who have published several high quality papers in the field of interest. Is there away to find this out easily?

Who are the authors of the papers that you cited in your paper?

Would you please clarify "area"?  Do you mean geographic area or academic area?

I mean an academic area

THe easiest way I can think of is to access Elsevier's platform called http://www.scopus.com . There, you can do paper research based on author's name, field, date and nº of citations. Take the top citated works and research their impact factor on google scholar.

This is the wrong notion of 'field of interest' - for the question's purposes, you want a list of experts in Underwater Basketweaving in New England Estuaries, not a list of experts in Basketweaving.

Such purpose wasn't specified in the question. Regardless, it really depends on how the person is going to conduct his/her bibliographic research. He/she can research the keyword "Basketweaving" AND "New England" (treating the latter as another keyword) in order to specify his results for a certain region. It is also possible to cross a keyword search with a title search and, considering that usually articles' titles contain the region the study was developed, this approach might give him a decent a starting point.

@Eric Lino, the website you shared with use is  very useful and helped me a lot. I really appreciate your help.

Note that Scopus is not free -- if your university has not paid big money to Elsevier, you can't access it.

Use Google Scholar to look up papers on the topic of interest, then look at (a) the papers they cite, (b) the papers that cite them (Google Scholar can give you a list). Keep following the links until you run out of interesting papers, then look to see which authors keep appearing.
Look at the major conferences/journals in your field to get a list of potentially-relevant papers, then look to see which authors keep appearing.

The union of the results of these two approaches will generally get you close to what you want.

Thanks @Stuart, I've used Scopus website and I got what I was looking for. I advise others to use the same approach if they are looking for the same thing.


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Multiple interviews and reimbursement from the same institution
I have two related questions. Here's the situation: I have 3 postdoc interviews at the same university and I scheduled them within the same week for obvious travel reasons.
Question 1: should I mention to all parties that I will be doing other interviews at the university? I only ask because two are in the same department, so it would be awkward if I crossed paths with one while being given a tour by the other. And should I take one of the positions, I would no doubt encounter the others later.
Question 2: I am offered reimbursement for travel by one of the interviewers. I did not ask for reimbursement for the two others nor did they offer (yet). I am not traveling exclusively for the lab offering reimbursement, so is it appropriate to accept?
Question 2A: If I do accept, and another group offers reimbursement, can I recommend that the costs be split somehow? There's no reason for one group in particular to pay for everything.

What field is this? This situation is entirely alien to me. But I imagine that, unless there is bad politics between the groups, this is a good situation and not something to be hidden.

It does sound to me like you should disclose that you are doing other interviews at that campus, particularly since they are likely to notice you back in the same building later in the week and wonder why you are there.  And, the department offering to pay your travel is probably going to wonder why you are spending the whole week there when your interview is just one day.  Finally, I imagine them knowing you're being courted by multiple departments might make you seem like a more attractive candidate.


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Conference and Journal Ranking Websites
I had a hard time deciphering conference and journal rankings in order to find good places to publish. [Disclaimer - I am a computing PhD and this post is intended to have a strong focus in CS]
I think it would be beneficial to have a list of websites which rank conferences and journals (deffo. for my self and maybe others too). My question is, could you all help me build this list?
Conferences:

Conference Ranks
Core Conference Portal
Computer Science Conference Rankings

Journals:

Scimago
Core Journal Portal

Other posts readers might be interested in:

How to find reputed conference and journal?
Impact factor vs journal ranking
Rankings of Computer Science conferences and journals
Difference between conference paper and journal paper

Someone also mention "Webascience" but I haven't been able to find this ranking service.

Other conference ranking include:
CORE Conference Portal
Also useful reading here, a Research Gate post

Find the journal with the highest impact factor; that's the 'best'. I recall reading that in CS, conference presentations take the place of papers (as the field moves so fast). There is likely an informal 'ranking' of best conferences. It is almost certainly implicit knowledge; the only way to obtain it is to ask someone in the know. That will require asking a senior professor, or an emeritus professor, and/or one of their grad students.

I've been told there are websites (and I have included some) that will rank journals by impact factor. The point of this post is to find such websites and state them for others to use.

I feel like this is a "Let me Google that for you" sort of thing? There really isn't a strong 'question' to this question, and that sort of violates the ethos of StackExchange.

Oh yeah, I forgot this is a competition and shared knowledge is frowned upon. I for one think something which helps people is a good thing.

@abdnChap A big issue is that SE is not oriented toward being constantly updated, so in general a list like you're looking for would work better on Wikipedia or maintained by a grad student association for a given field. My sense is that the Academia StackExchange only sets up community wikis to address issues that constantly recur in slightly different forms that span academia, but in general do not want to create lists. I hope that you do come back with other questions, though.


text:
For inclusiveness sake, what is the consensus about which usage of "blind" should be changed?
In academic contexts, what is the consensus on whether we should avoid using "blind" as a category of persons, or should we avoid using it as an adjective (or both or none)? Does it vary between distinct academic communities?
CONTEXT: In a scientific project and its report, I was using the term "blind experiment" (defined by  https://www.thefreedictionary.com/blinds as "2a. Performed or made without the benefit of background information that might prejudice the outcome or result: blind taste tests used in marketing studies."). A colleague recommends to replace the word "blind" (for the sake of inclusiveness) by "masked", "hidden", "anonymous", or "unbiased", as a form of respect toward "blind people".
ISSUE:

I have seen in the past the expressions "non seeing people" (which I think is a negative definition, a problem in itself) or "people with visual impairments" used as alternatives to the expression "blind people".
The request from my colleague seems to be about replacing the use of the adjective itself, which describes many situations not related to visually impaired persons  (e.g. "blind spot" in the mirror, "blinding light" which prevent you to see, "blind experiment", etc.).

I am completely willing to do any language change, but I am confused about whether there is a consensus about replacing the adjective "blind" in all its applications, or about replacing the name used to refer to a category of people. Changing both seems overkill, and not having a clear policy WILL lead to severe miscommunications (of content), when the original purpose was to reduce miscommunication (of connotations) to begin with.
(I am not sure if this question should belong to Academia or to English, feel free to vote to move it to another category if this is inadequate. I am interested in answers in the academic context, but me asking is probably related to my non-native-English-speaker status!)
(I am not trolling nor trying to convince anyone here, and I respect any opinion that anybody could have, and in particular people with visual impairments.)

I've retagged your current questions. Please don't create new tags for keywords. They aren't the same. Search can be used to find keywords. Tags are for classification of questions.

'My understanding was that for inclusiveness purpose, (some) "blind people" might be more comfortable being referred as "non seeing people' So what? Other blind people might find it strange or even ridiculous to be referred to as "non-seeing people" just so someone can get to signal their "inclusiveness" and prefer to be referred to as "blind people". Unless you have some particular reason to believe that the first group is more numerous than the second, the vague claim that "some blind people might prefer X" has no bearing on anything.

Maybe its because I come from a non-American background, but I always seem confused by these things. Isn't "blind" a descriptive of someone, with no historical bad connotations? They are just... blind? Maybe also tall and blonde. Happy to be educated about this, but I am just surprised this is a thing.

@AdamPřenosil: Thanks for your comment! I clarified that I was expressing an observation (some people have been using the term "non seeing people" rather than "blind people") as opposed to a personal opinion.

@AnderBiguri Where does America come into this?

This here seems to be at least one actually affected person objective to the phrase "double blind experiment". https://www.visionlossandpersonalrecovery.com/the-word-blind-is-still-misused-in-everyday-speech-lets-get-rid-of-it/

@Arno: Though one should probably add that (i) the definition given of a "double blind experiment" in this text does not seem to reflect how the term is actually used in, for instance, medical research and that (ii) the text claims that the term "double blind experiment" promoted a "negative [...] idea  of blindness", while it seems more likely that most researchers (i.e., the people who mainly use the term) probably have a rather positive connotation when they hear "double blind experiment".

@AzorAhai-him- In EU/UK a black person is black, not "british-african" or some other thing. Or there wasn't a big deal on trans bathroom use, people just use bathrooms. A lot of the obsession with correctness comes from cultural tensions in America, I have the feel that in this side of the pond, these things are less of an issue. Not that there is no racism/transphobia/homophobia etc, just that its dealt with it a different way. One of those is not trying to be extremely careful with language. But I am a white cis male, so I am certainly not an authority on this...

@AnderBiguri Yet, OP's profile suggests they are Chilean, so your guess seems to be off base.

@AzorAhai-him- oh, you misunderstood (aside from the obvious, Chile is America). I am saying that this is an American driven culture thing, not that American-born people do it. I still think everything I said about this side of the pond is true...

Do you have any citations for “blind” being disfavored as a term by the community themselves?  I had thought that blind was certainly the preferred term, at least in the US. I could be wrong though, I’m less familiar with the blind community than with the Deaf and hard of hearing communities where certainly those terms are strongly preferred to “hearing impaired.”

The consensus is that pejorative and prejudice terminology should be changed.  "Blind," in my experience, is neither.
"Blind experiment" means an experiment where something is hidden to make the experiment more reliable.  That's a positive thing.
"Justice is blind" means it is fair.  That is a positive thing.
Contrast that with "blacklist" which is a list of unwanted things.  "Blacklist" could be interpreted as associating being unwanted with a group of people.  People's opinions on the use of "blacklist" are unrelated to the phrase "blind experiment."
When referring to a person's vision, the term "visually impaired" is preferred by some because it clearly includes people with nonzero vision.
Grammatically speaking, "blinded experiment" would be more accurate than "blind experiment" and should make it even more obvious this has nothing to do with any identity group.

Just to give a counterpoint, I did find one well-reasoned argument taking the opposite viewpoint.  I think the issue is less about these descriptions being negative, and more about the underlying assumption that if you can’t see something then you don’t know anything about it. But I don’t think there’s a strong consensus here the way there is with some of the other examples you give.

@NoahSnyder I do not agree with those who say "blind" is being used in a way that equates blindness with ignorance.  "Blind" is used to refer to postponing knowledge intentionally for a valid purpose.  That's not like ignorance.

what is the consensus on whether we should avoid using "blind" as a category of persons

I am not an expert on this topic, but a look at this page suggests that “blind” and “the blind” is how blind people in the United States most commonly refer to themselves, at least in the names of their associations and advocacy organizations (e.g., National Federation of the Blind, American Foundation for the Blind). It seems reasonable to infer that this is also how most blind people prefer to be referred to by others.
For other countries, see this page.

I think this summary is correct (the "most" is important!) and if you poke around on blindness advocacy websites, you can often find more direct statements of preference for identity-first language ("blind"/"blind person") as opposed to person-first ("person who is blind"/etc.) For instance, this article. Deaf and autistic groups tend to have similar preferences but this doesn't automatically translate to other forms of disability.


text:
Code of conduct when proposing to open a new lab in a field new at the University
I have no idea what is code of conduct when proposing a new lab and hope you can help me out.
I am looking for a Tenure Track, just finishing my PostDoc, having a good track in an emerging field and looking forward to opening a new group.
I know that at University X there is a program dedicated to opening a new labs and hiring good PIs for that, however, at this University my field is not present at all. I would love to set up a new group there, but have no idea how to approach them and propose it?
Technically the program works like they open a position from time to time, yet then it is already specified, the field, requirements, keywords, etc. Just casual job offer.
So I need to approach them before they open a position, but what is a proper way to do that?
Colleague of mine benefited from the same program, yet he contacted a senior researcher from similar field, who advocated internally for the new lab. I do not have such option, since my field is not even close to the ones already at the Uni (However it would strongly synergise with other Labs and for sure is a prospective and active field).
Shall I already contact with a CV, or first with idea for a lab?
Shall I be transparent and first convince them for a lab before proposing myself as a candidate?
Shall I first call, or mail?
I do not want a faux-pas or being misunderstood, how would you take it?

FYI, it's faux-pas

Why not follow your colleague’s approach? It seems to have worked for him. The fact that he was in the same area as a senior researcher at the program might have been to his advantage, which means the chances the same approach would work for you could be lower, but I don’t see any reason in principle why you shouldn’t try the same tactic. Basically if your area is exciting and you can convince people at the program that the synergies you’re mentioning are real, I’d say you have a chance.

I worry that you would be seen as arrogant if you make such a proposal and are not already on the faculty. An exception would be if you bring a gigantic grant with you, or are already a superstar in your field.

So maybe more general: How a new field opens at the University? E.g. There is no Rocket Science at all, and we want to bring it in? And specifically if you are part of that field and obviously want to bias central decisions so that it opens in your field (and then you may win a position from an opened call.

If I understand this correctly, you are asking if you should contact a university telling them (a), that they definitely need their first lab in field X that they currently have no lab in, or (b), what (a) says plus I’m applying for this to-be-created new position! Neither approach would have any hope in any country or field I’m familiar with.
Your question seems to be prompted by a colleague of yours being hired into a newly created lab (in an already present field) through personal connections. This combines connections with the new lab being in a field that already exists, and so does not really compare.
By and large, you can only apply to specific job openings, no matter how good your fit would be in a place. As you are in a new field, there might be neighboring fields with sufficient overlap that you can apply to openings in them as well. But the case at hand strikes me as fruitless.

Thanks, I agree, that's why I asked this question.
So what to do if:
a) I know there is a bulk of money dedicated for new labs at this Uni
b) There is no overlapping lab at Uni, but my proposed lab would fit into their development policies and long-term agendas
PS. It is particularly hard in Covid when I cannot casually chat with some of senior guys over there at conference or seminar, since they are only online...

@Intelligent: I honestly don’t know. The only way to push for this, in my experience, is through the grapevine - someone who knows someone trying to get faculty/administration where you would like to end up to consider setting up such a lab. Even if that’d work out you’d probably face modern-day opposition to bringing you in as an opportunity hire (in the U.S. at least); instead, that new lab might have to be advertised publicly - and so effective next cycle - first (your colleague’s experience might indicate that this wouldn’t be the case where you are).

@Intelligent: While you’re probably hoping for a tt position (understandable), in this awful cycle maybe also look into being hired as a research professor (non-tt, with the goal to re-apply later). But for that you’d also have to have someone push for you with the dean. It’s tough. Talk to your PI. Maybe extend your postdoc by a year and try to network now. Good luck!


text:
How successful would one be in switching fields from PhD in computational biology/neuroscience to postdoc in computer science?
How successful would someone be who completed his PhD in something such as computational biology or neuroscience but wanted to pursue post-doctoral training and beyond in computer science?
I say computer science because, presumably, dissertation work in computational X involves programming and a working knowledge of data structures and algorithms.

I believe that career changes and "reinventions" are a regular part of modern careers in highly specialized fields. Very few people will be able to work in a single domain for their entire careers, and the ability to move laterally between "adjacent" fields will be a critical skill enabling one to have greater chances and opportunities for success.
Now, that said, your chances of success in any particular job hunt will depend to some extent on how "enlightened" your future boss (or hiring staff) are: some will actively seek out anyone with the appropriate skill set and enthusiasm for the work, while others will be more focused on people who have the "direct" skills they need, assuming such people will require less training to be able to carry out their work. Neither of these positions is "better"; they just happen to coexist.

The most important of all criteria is the interest you have and confidence you feel in the new or adjacent field. In addition to this you need to convince your future post-doc supervisor that you are capable of pursuing post-doc in computer science. This would need from you a specific and honest cover letter and curriculum vitae that highlights your new intentions.
Also, computer science is a broad area and I am not sure if someone offers post-doc in just computer science. This supported by @JeffE (see his comments down) also.

I was not talking about theoretical computer science. My underlying question is how pigeon-holed one is by his PhD because he can show nothing else for his time even if his interest changes and project left him uninspired for a certain area.

Okay. Then somehow you need to highlight your abilities outside the specialization.

No, nobody offers postdocs in computer science, or even in theoretical computer science.  Most computer science postdocs are funded by grants, which fund research on a specific topic.  Some CS postdocs are funded by fellowships, which allow for broader research efforts, but those still require a focused research proposal.

I edited my answer to avoid confusion


text:
On giving gifts to LOR writers
Should one give gifts to those who one's close to, or those who one generally doesn't interact with very much?
If the professors who wrote my LORs seem reluctant to meet me again for some reason (not sure why - maybe they're just busy), should I simply forget about it?
Also, do people usually give gifts to their advisers for PhD programs, or not really?

You can get gifts for writing letters ? Why did I not think of this :) ?

Here's how I would feel about various expressions of thanks, for something like writing a letter of recommendation:

No response at all: I might be a little disappointed but if I am busy I might not even notice.  Some people might be more offended.
Email saying thank you: Feels perfectly sufficient to me.
Handwritten note: A very thoughtful gesture.
Token gift (small box of candy, desk trinket, etc): Appreciative but slightly embarrassed.
Gift of non-negligible monetary value: Quite embarrassed.  I would probably gracefully try to decline it.
Gift of money, in any amount: Very uncomfortable.  Feels like a bribe.  I'd refuse.

Of course this could vary by culture (I'm in the US).
Regarding gifts for an advisor: A common tradition is to give your advisor a nicely bound copy of your dissertation, for their reference and as a memento.    (Also be sure to thank them in the dissertation!)  You could accompany it with a nice personal note.  But again, I wouldn't suggest anything of significant value.

I completely agree with Nate.  Any of #2-4 is good.  In grad school, I think a department secretary helped coordinate sending all the letters of rec that I requested (she got an electronic copy from each letter writer, then sent out the hard copies that I requested).  If you have someone similar to help you, I would definitely at least say thank you.  In that case, I think a token gift would be appropriate.

This is pretty much dead on. Going with any of the options from email through token gift would be fine, and likely won't get either the gift giver or the recommender in trouble.

Thanks! What kind of paper would you suggest for handwritten notes? Are greeting card bought from stores more than handwritten notes?

This may vary from country to country, but I think a simple "thank you" is sufficient.  Writing letters is part of their job.
I'm actually forbidden from accepting gifts from students, on the grounds that an outside observer might interpret the gift as undue influence.  But then, I work for a state whose last two governors are in prison for various flavors of corruption.

AHAH! Jeff that's so funny, but sadly true :). I have lived in Chicago 2 years and I know what you mean ;)