text:
What is the purpose of women-only meetings, panels, conferences, etc. in academia?
Since entering graduate school, albeit in a STEM field, I have never been exposed to such an emphasis on women-only meetings, leadership conferences, panels, etc. I have seen most, if not all of these venues, exclusive to women. Most of these meetings are hosted by the WISE (Women In Science and Engineering) organization at this university. I am sure this phenomenon is true elsewhere.
Why is it that in academe, in my experience, it is common for women to segregate themselves in the context of raising gender issues?
How does this behavior exemplify equal opportunity?
How does this behavior develop real solutions to real problems?

Comments are not for extended discussion; this conversation has been moved to chat. Also, since comments on a post can only be moved to chat once, future discussion will have to be deleted instead. So please save the comment flaggers the trouble and just post it in chat.

Please see this meta question about the suitability of this question.

I actually agree with you completely. I think that the women only conference concept is very well intentioned but in practice kind of terrible. I once went to an all girl hackathon and spent 2 1/2 hours not making anything and instead watching everyone pat themselves on the back for being women. Had to sit through a ton of self congratulatory "Ted Talks" while all I wanted to do was code with some other female engineers. It was.... weird.
There are reasons for it though.

I think that the biggest threat to women is other women who view them only as competition. The women only concept removes that competition from the equation so that we can have a safe space to actually support each other.
Working in STEM, it's really unfortunate but sexism is kind of pervasive, and most women don't really feel like they have the tools to deal with it appropriately. These conferences usually provide some sort of structure to help them learn.
Women have been largely ignored by the STEM community for so long that we really do need all these outreach programs. It actually does make a difference to both the women in attendance and our level of visibility and subsequently provides opportunities for growth.
For younger women, these experiences are invaluable. It tells them that it's okay to be who they want to be, that they're not alone, and that they have people who really will rally around them and support them as they grow and come up in the world. Honestly, I wish these things existed when I was a kid.

That being said, isolationism is stupid and self defeating. I'd be much more interested in something that fostered actual dialogue between genders, or provided hands-on technical training in skills that I actually need instead of congratulatory prose about what a good little girl I was for showing up.

Comments are not for extended discussion; this conversation has been moved to chat. (Comments on a post can't be moved to chat more than once, so additional comments here are just going to be deleted. Post them in chat instead.)

"Women have been largely ignored by the STEM community for so long..." is not quite right. For example, consider the first programmers - they were mostly women. (It changed only later.)

It is not the STEM community that ignored women. It's (most) women who ignore (certain) STEM fields, for the same reason (most) men ignore nursing. Men and women, on average, simply have different preferences, determined by different biology. Even in monkeys, we see that males (typically) prefer to play with trucks while females (typically) prefer dolls. Let's please embrace these biological differences instead of forcing "diversity" in the workplace, which in practice means nothing other than the discrimination of men.

My answer is focused on the sessions that usually occur within a larger conference.
The purpose of a successful session is to leave the attendees energized and feeling more confident so that they can be more productive. Please be sensitive to the fact that women, for whom those session are focused, have come to a career in science with the lifetime of acquiring not-particularly-helpful baggage from whatever typical cultural biases they negotiated previously.
I have never seen any of these sessions be closed, (there are no bouncers stopping people at the door for lack of bosom) simply that the circulars and announcements strongly emphasize that they are for the women (for the women's benefit). They encourage an atmosphere that will end up with a room full of women scientists (senior/midcareer/junior/student). The attendees, thankfully, tend to self-select for being truly supportive.
Typically, there will be some formal presentation on results of current research on stereotyping and bias, prevalence of impostor syndrome, etc,  and its impact on career or motivation and confidence. In a well-run session, the primary purpose of such presentations or panel discussions is not to initiate a spiraling negativity of people comparing terrible experiences or feelings, but to get the information out because these facts are powerful. It helps in confirmation of experiences  ("maybe it isn't all in my head after all") - or it simply can be comforting to realize one is not alone ("I'm not the only woman who feels like my successes are probably a mistake"). The sessions that are useful will focus then on making connections, networking, and helping women 'mentor' themselves, showing successful examples.
I have been in a STEM field over 30 years. In my 1st 10 years, I used to be surprised when I saw my reflection off of a window when walking in a street with colleagues. ("Who is that strange-looking person with them? - oh that's me"). Contrast that with having the occasional opportunity to be in a room of scientists, and also majority women. That is a pretty neat in itself, and also is a 'safe' space to ask questions or to make observations and get feedback. It also was very interesting personal observation to recognize a different level of personal comfort being in a space; most of the attendees share similar experiences/feelings that my male colleagues typically have not had (or at least not so pervasively common throughout their career).
I hope that the supportive OP would be self-reflective enough (and informed enough) by now to recognize that we all are 'biased' and that cultural stereotyping and its impact did not disappear overnight. The 'insulted' feeling is natural, (feeling as if you are being told you are inadequate?) but beside the point and not helpful. Perhaps by now you can laugh at yourself a bit realizing that what it sounded like (to me) is that you are so confident about your natural place in STEM that if you feel insulted, you assume it must mean that someone else must be wrong or that it deserves pacifying and explanation. Statistically, women in STEM are a lot less confident. The workshops are to help give little pushes to overcome those insecurities.

As a guy, I was interested to read this and other answers.  I can only guess at what exactly you or other women might not feel "safe" discussing in a mixed group (or especially a mostly-male group, which would be typical I guess outside of women-only sessions).  From this answer, I get the impression that expressing self-doubts (or other signs of "weakness") and getting positive support is something you wouldn't be comfortable with in front of male colleagues, or think might not even happen from male colleagues.  If I'm understand that correctly, that makes sense; thanks for that insight.

@PeterCordes - your comment is a pretty accurate assessment.

Just to add I have found these conferences and events to be completely closed - including once where my code was used but I was specifically told I could not attend or present it which meant I was unable to attend the conference at all. Not really a disagreement just explaining why one may feel "insulted" (I would have said I felt "slighted" in this case)

I have never seen any of these sessions be closed, (there are no bouncers stopping people at the door for lack of bosom) Bouncer jokes apart, I find it difficult to believe that these sessions are not closed in practice. Do men attend them? Are they welcome by the rest of the audience if they show up?

@FedricoPoloni, yes they are open. I am specifically referring to sessions that tend to be embedded within a larger science/engineering conference. They are open. There are men attending, typically chairs of departments, or organization executive members, smattering of students and supportive interested parties (e.g., faculty whose graduate students are presenting at main conference).

@Carol I am not sure we are speaking about the same thing; OP writes about "women-only meetings", and I took that to mean "meetings where all participants are women". Do you mean "meetings where all speakers are women" instead?

@FedericoPoloni, Original question may have been edited or I misread, but my reading was that OP queried about the purpose of what he construed as 'women only' meetings, no matter whether they were 'for women' (misconstrued as women only) or some other event. In my field, 'for-women' sessions embedded within the major conference and have become common. General attendees might assume they are 'women-only' (and obviously they wouldn't be very useful for providing the support/networking noted above if the ratio was poor or if there  were good ratio but included persistent hecklers in the mix.

The vision of the Association for Women in Science focuses on compensation, advancement, discrimination and respect. These are real problems for women in academia. To an extent, conferences for women are a result of the "leaky pipeline" of the 1970s and and 1980s where women were more likely to leave academia then men. While the leaks have been slowed, possibly stopped or reversed, at the Bachelors to PhD stage, the pipeline may still be leaky at later stages.
What is clear is that gender biases in conferences still exist (e.g., https://biaswatchneuro.com/) and the all male conference panel (aka the manel) are still all too common. In presence of these, and other gender, biases, providing women only conferences/workshops seems a reasonable approach as part of a larger strategy towards gender equality.

I don't think that this answers the OP's question.

Comments are not for extended discussion; this conversation has been moved to chat.

[Warning: Male speaking]
If enough people feel the need for such a conference, then there is a need.  Since these conferences keep getting held, clearly there is a need for them.
Now, in an ideal world, conferences would be coed and everybody would feel welcome everywhere. Unfortunately, this is not an ideal world.
Many women feel that they are being judged inferior simply because they are women.  Most of these women are correct about that.
You complain about being called "unsafe".  Remember that there are other men than you in this world and that some of them are definitely unsafe.  Also remember that "feeling safe" is not only about physical safety, but also safety from ridicule, from being ignored, and from getting your self-confidence shattered in other ways.
Most conferences are male-biased.  Having woman-only conferences is not a good solution to this problem, but it is better than doing nothing about it.

Comments are not for extended discussion; this conversation has been moved to chat. (Comments on a post can't be moved to chat more than once, so additional comments here are just going to be deleted. Post them in chat instead.)

You're quite right in your observation of that segregation does little to exemplify equal opportunity, and is a poor venue to discuss gender inequality.
However, the purpose of these women-only panels, forums, conferences, scholarships, prizes, etc. is not for the express purpose of solving gender inequality or un-equal opportunity.
The purpose of this is three-fold:
1. There is generally funding and resources available to events such as these, therefore the funding and resources are used.
2. These events add value for the women who are able to attend simply by existing.
3. A field criticized for having poor female representation may be able to improve public opinion by holding events that are specifically for women. [sarcasm]How could a field of study possibly be gender biased when they specifically hold special events for the discriminated sex.[/sarcasm]
Items 1 and 3 are fairly straight-forward.
Item 2 above is not very clear. However, imagine you are artistically inclined and you are viewing two possible schools. One of which has listed many art clubs and provides several art forums. You don't know how good any of these forums are. The other school has fewer art clubs and forums. Which one is more appealing?
Similarly, if a field of study holds women-only events, there is a perspective that this field of study is taking steps to be extra-geared toward women. A woman who is deciding between a career field heavily populated by women and a field holding routine events specifically for women, may be swayed won by the field holding events expressly for women.
Frankly, and I realize it's not part of the question, but I don't see many of these approaches being very helpful for purposes of equality.

Do you have any evidence to backup your claims?

-1: When you base your answer (even partially) on sarcasm, you lose (your) credibility and (my) respect. Your argument is that imposing some instances of "X only" inherently works against "equality (or some acceptable bounds on the proportions of) X and Y". That is clearly wrong: if things are highly skewed away from the proportions you want, you don't correct with equal proportions, you correct by skewing in the other direction. Let me ask you this: what do you think is the percentage of female speakers at the most recent International Congress of Mathematicians?

Comments are not for extended discussion; this conversation has been moved to chat.

Additional comments regarding discussion or moderation will be deleted. See http://meta.academia.stackexchange.com/questions/3470/why-are-comments-critical-of-moderators-simply-deleted

The [sarcasm]text[/sarcasm] could be rephrased/inverted to make the same point without relying on sarcasm.

By the way, it is possible to simulate HTMLish/XMLish tags, using the markup.  In a title or a comment, just use ordinary angle brackets.  In a question or an answer, use < and > .  For example, the following text in an answer:  <sarcasm>text</sarcasm> is equivalent to the following text in a comment:  text .  You can even copy-and-paste from this comment.  More help is available next to the edit boxes.  (The comment editor has a "help" link; the question and answer editors have a circled question mark icon, which provides an "advanced help" link.)


text:
Do famous people really have the power to ruin the career of unrelated researchers?
I am a graduate student in some subdiscipline of mathematics and have had the following impressions. One of the senior faculty members (a professor) at my (not too famous) university mentioned, when talking about famous people in the field (high positions at top universities, etc.), that it is very important "not to rub such a person the wrong way". Another senior faculty member mentioned that it is very important to be political when citing the same type of people and giving very much credit and in particular that one does not criticize errors in their papers (in one case the error was anyway corrected in a subsequent paper).
To what extent are they right in saying/doing this? Can such a person ruin your reputation/career? Are there examples of this?
I understand that the answer to these questions are in principle "yes", but would like to have an elaboration if possible and also some examples of this.

Famous people are unlikely to read your papers. However, in some cases, it is a network built around such people (or even a network not built around famous people) that can cause some serious damage. I will leave my comment at that.

What part of the world are you in? I suspect this varies geographically as well as by field.

I find the ''superstars'' are not dangerous, it's usually the ''mediocre, not really superstars and are bitter about it''-type of people that are most ruthless and dangerous for young researchers, especially if you don't yet have a track record of publications and they decide to try and get rid of you.

"and they decide to try and get rid of you. " Care to elaborate on this comment? Do you have an example?

@Vertex bitter researchers can make life difficult, directly or indirectly.  They might make biased recommendations or assignments.  I have met such people, who for instance would never allow students/postdocs other than their own to participate in organizing conferences or meeting with guests, who would go out of their way to advocate against scholarships to certain students, and who expect total fealty from their own students.

All “famous” researchers I have met personally have been gracious and very patient, although I know of examples of famous people (with whom I’ve never interacted) with anger management issues.

@ZeroTheHero I think there's a difference between anger management and being vindictive. One is in the moment and passing while the other is a persistent, concerted effort. Anger is not necessary to be vindictive. Simply not liking them is enough.

@Vertex It's fairly common for a researcher to try and ''get rid'' of a weak PhD student that they have.  I have heard people using these exact words in the common room regarding actually a very famous mathematician who had a bad student, so not going to elaborate further.  I presume ''get rid of'' means try any possible means to get rid of them: try to convince them to leave the PhD, make their life difficult to try to force them to quit or convince them to change to a different supervisor.  Report them for underperformance as many times as possible.

My experience (in North America) in dealing with superstars is that most of them do not care about being cited: they know where they are in the queue, others know where they are in the queue, and citations do not matter to them.
(There are exceptions of real obnoxious superstars but they are thankfully rare.)
The more toxic people tend to be amongst the wannabes below superstar level.  Some of these guys feel their contribution are unfairly ignored or not recognized properly.  These are a dangerous tribe and they will not hesitate to step on others to climb up the ladder of success.
I do not think it is more likely that famous rather than just regular obnoxious people will actively seek to ruin the career of random persons.  It’s simpler for most brilliant people to just ignore the plebs.
This being said, I would double and even triple check before pointing an error in any paper: I have found over the years that in most cases it was I who did not understand the work properly (which can be quite poorly written).  It is unlikely that these errors are serious as the work of such superstars is quickly read by others and such mistakes quickly corrected.

"wannabes" - or worse, Lion King-style hyenas who would zealously defend the current "King" to maintain their subpar status quo just because any alternative is filled with uncertainty. They may not even try to get on the "King's" good side, just be worried to death that if even kings are not invincible, what good is there in this perilous and uncertain world?

the work of such superstars is quickly read by others and such mistakes quickly corrected - Well, ideally.  Unfortunately there are many cases where either there are known issues that aren't corrected in the literature for a long time, or there may be gaps, and it's not clear how serious the gaps are.

Your last sentence is crucial.  Much more common than not understanding the work itself, is not understanding what kind of errors are considered “serious” vs “trivial” by people experienced in the field.

Be charitable to all, without special dispensations for people of high status
It is inherently difficult to predict the future behaviour of other people you don't know, but the mere fact that there is a reputation that is spread around warning you against valid criticism of the work of others is itself worrying; is an indicator of unheathy behaviour and scientific corruption in academia.  Irrespective of whether vindictive behaviour responding to a correction is likely to occur, I don't think it is healthy to approach academic work in a political manner where you formulate your own behaviour in order to accommodate the presumed or suspected vindictiveness of others, based on their power and status in the profession.   If others are not going to act vindictively then there is nothing to worry about, and if they are going to act vindictively then you should be bold and fearless and proceed in the spirit of open scientific criticism anyway.  Therefore, I would counsel against any attempt to speculate on or predict vindictive behaviour by high-level academics; just be faithful to the spirit of scientific inquiry and professional courtesy and take these as your guide for behaviour.
Academics with high status should not get any special treatment here, but obviously you ought to show some appreciation for the fact that they have made valuable contributions to the discipline and put any errors in perspective.  You should also approach critiques of the work of any author with a level of good faith and charitableness appropriate to professional research.  People who do lots of work in a difficult field are going to make lots of errors in the course of doing this work, and occasionally these errors will sneak past discerning eyes, including in the peer review process.  If you find errors in the works of other mathematicians (whether they are famous or not) you should correct those errors as appropriate and proceed using the corrected version of their work.  Typically if you are citing a work and using it but correcting an error then you would have a footnote noting the error and the correction but you would not make a big fuss about it or be harsh on the author --- just make the appropriate correction, make it clear to your reader, and proceed on the basis of the corrected work.  Undertake your corrections in a calm and non-judgmental way that shows respect for the fact that the totality of the work of these other authors has positive value and merit despite occasional mistakes.  You should exhibit this level of appreciation and charity when dealing with errors from any of the practitioners in your profession, irrespective of their status.
As to the question of the power of famous academics, they have quite a bit of power and discretion over others within academia (e.g., decision-making ability over hiring, promotions, reviewing, etc.), but this power is curtailed by ordinary protections for other workers, the tenure system, etc.  A vindictive professor might be able to exact punishment on a lower academic for a perceived slight, but it would harm their own reputation if it became known that they act in such an unprofessional way.

I may not answer for Mathematics specifically, but I would be generally less pessimistic about the politics in academia. But there are many layers to peel here.
First, "do not try to challenge famous researchers" may be a useful heuristic. They became famous for a reason, and lots and lots of resources were spent following in their footsteps. Challenging some of their results without a strong attack is unwise, and going after foundational principles of any field will cause an instinctive rejection by the community, as it have many times in the past. On the other hand, no guts, no glory - if you DO have a strong attack on a problem, it may very well be the road to fame. Planning research around having a breakthrough is not particularly feasible, however.
Second, in some parts of the world, challenging the authority has broader cultural implications. This is far from universal, but (allegedly) there are places where it may well be a career suicide.
Third, if the previous point does not apply, I would call "giving very much credit" either a poorly worded or poorly understood (either by you or a person who stated that) approach. See, "famous authors were all wrong" implies that anything based on that paper is invalid, and that stance loses immediately. Instead, try to reconcile the development of the field with your newfound results. It may not be that important to pay tribute to specific people, but failure to recognize the value of a significant fraction of research done in the subfield would easily lead to the paper being rejected, ignored, or even labeled as crankery. Starting off by antagonizing the very community receiving this work is very counter-productive, and not being sufficiently specific with the critique may, unfortunately, trigger certain heuristics in fellow researchers that will place your paper straight into the trash bin. "Giving credit" may have the same presentation as "reconciling the differences", but a very different driving force behind it. The latter tries to be impartial even towards oneself, the former makes scientific merit highly subjective and, plainly speaking, feels wrong.
And finally, there is certainly a component of having to work around personalities in academia. The higher up the ladder, the more political it gets. In that sense, yes, famous people wield a lot of power, and if you try to get a big project going, you have to consider who will be in the committee, what they believe has merit and what does not. There are not enough funds going around to pursue every venue meaningfully, and attempts to divert more resources than just venture capital from what seems to be working great otherwise would not be received favorably. Convincing other researchers that what you are working on is important is a substantial part of being an academic, and this is especially significant in mathematics as this acute observation by Alexander Woo attests.

I like to think of the formal "powers" any senior person in a field might have and how that could enable them to harm another researcher. I come from the social sciences but I'm not sure that anything I say works much differently in other fields.
Such a senior person may be involved in various aspects of the process of hiring new colleagues in their department, either via serving on the search committee, serving as department chair, or merely being an influential voice in faculty meetings. So if you seek employment at such a person's institutions, they may hold some sort of bias against you. This could be out of malice or merely due to the underlying disagreement leading them to conclude you don't know what you're talking about.
They could also have various roles in the publication process, like serving as editor, associate editor, or peer reviewer at various important journals (or conferences). Of course, a peer reviewer does not know the identity of authors in many fields but I'm not sure about mathematics. At any rate, this person's influence in the editorial process could potentially close off some small number of avenues for publication.
I'm only familiar with the US system, but part of the process for gaining tenure here is that outside peers are invited to review your file. At many institutions that use these peers, even mild criticism from these peers can be deeply problematic for the candidate's chances at tenure and promotion. Should you be so unlucky, they could cause harm in that way. But the chances of them being invited for this purpose are low and I believe it would be considered inappropriate if you had some sort of public intellectual dispute with them.
The more informal influence such a person could have is by generally using their social status in the discipline to cast doubts about you or your work. I'd say that in general talking negatively to peers about another researcher would come off as very uncouth among the people I spend any time around. On the other hand, criticizing work can be very appropriate under certain circumstances although I'd admit it is not often that I find myself in situations that would open the floor for someone to start badmouthing some non-high profile research.
Besides the above, there's always the potential of the more juvenile and pernicious forms of rumoring and attempts at retribution that any person might try to do. But I don't think many (or any) people have the power to sort of push the red button that destroys some junior person's career. In fact, the most likely person to be able to do that is a person in a graduate student's department. Even then, we know many cases where apparent bad faith by an advisor/mentor/etc. fails to completely derail a researcher's education/career.

As an addendum to the answers already given, it pays to be mindful that some academics can hold positions of various boards or committees that can either open doors to researchers or firmly close them with little explanation or oversight.
Or they may have the ear of the people who sit on those boards\committees.
This is particularly true when it comes to allocating grants or other forms of funding.
Notable academics can ensure that doors are opened to likeminded people, or people who they feel are expanding a particular field in the right direction. Often this is the direction that the academic is trying to take it. They can close them if they feel that you have the wrong mindset or are trying to take the field in the wrong direction.
This shouldn't be the case, and there are many academics who will be agnostic and open doors purely on merit. Knowing which type a person is can be important.

Personal view on these issues is that the problems fall into several categories:

Economic Issues: When many agencies (NSF, NIH, ect...) choose external reviewers, they are often attempting to find known "subject matter experts" in the field, and therefore, a famous or highly cited author in the field is "probably" more likely to be chosen.  Therefore, a famous or highly cited author is more likely to have influence over your financial funding future.
Social Network Effect: Generally, famous academics have more friends, ties, and influence in the community (similar to social media followers) and whether good or bad, their comments often carry disproportional weight.  If a famous author criticizes your work, it can be more damaging than if a "nobody" criticizes your work.
Social Multiplier Effect: Peer effects are captured by the sum of friends' efforts in some activity. An individual pays a price for deviating from a norm. In the latter, as an individual gains more peers who have a certain attribute, they experience greater utility for adopting this attribute.  "Act like us, we'll all do better."
System Gaming: Not all, yet many academic positions have become extremely competitive, and as the Guardian notes "academics is a highly incentivized game".  When faced with this competition, many turn to gaming the system.  This is a well known criticism of author level metrics.  However, the same applies with a social network.  The equivalent of "don't insult them, they're a 'high-level' player."
Viral Infectiousness: Related to the network effect above, a famous criticism has more pathways to infect someone's career.  And if it represents something good for gossip, or viral sharing, then it may spread pervasively. "did you hear what so-and-so said about them?"
Rational Ignorance: In the face of evaluating potential threats to their academic career, a busy academic can't reasonably be expected to evaluate all the possible ways critiquing someone might be damaging.  So you get rules of thumb, 'very important "not to rub such a person the wrong way"'
Anonymous Denial: From many sources of funding, the reviews, and even the denial of funding, may be completely anonymous.  Even if there is a conflict of interest, from the person being denied's perspective, that can never be identified.  Per the economic section above, famous are already more likely to be chosen to review, and there's no way for the submitter to note that the only harsh review was from someone they criticized.

"Are there examples of this?" While neither of the examples below are specifically of the "famous" case, there are numerous examples of the type of behavior that then leads to the pervasive fear of criticizing anyone of influence:

Universities to Fear (Anonymous Issues with Schools) - Many are complaints about interviews, yet several illustrating the social issues above.
Academia is Killing My Friends (Anonymous Stories of Academic Abuse)

An Inside Higher Ed Article from Jennifer Snodgrass, also has several concrete examples of what leads to this behavior, especially the "Egos are huge. People may turn on you" section.
Note the pattern in the sites, there also appears to be a strong trend in current academia that it is not safe to talk publicly.  The following article notes this directly:

The Young Academic's Twitter Conundrum (The Atlantic, Olivia Bateman) - “You can use the story, but don’t mention my name. I don’t want any trouble.”

source: Stack Exchange

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

sort: votes


text:
My university is not issuing a transcript in the form required by a foreign university. What are the options before me?
I'm from a South Asian country, and here marksheets are accepted for all kinds of admissions. Now, I have applied to a UK university, and upon uploading my marksheets, which look like this:

I received this email from them:

Thank you for your application to study on the MSc in Economics. To help us to process your application please provide a breakdown of the Economics modules you have studied in your degree. We need to determine whether you meet the individual modules requirements of background in econometrics, microeconomics and macroeconomics. Thank you for your help.

I had nothing else that I could provide them with, so I sent the syllabus, so that they could get the name and the topics included in Paper 1 and 2. But again they emailed this:

A transcript with details on the modules you have studied and the score you have obtained is required for us to review the module requirement of this course MSc Economics. A syllabus does not serve the purpose unfortunately.

So, after this, I procured a transcript from my university, which contained a breakdown of my marks for all three years (not just 3 Year), and emailed it to them along with the syllabus (because this transcript too doesn't include the name of the modules). They replied

A transcript with details on the modules you have studied and the score you have obtained is required for us to review the module requirement of this course MSc Economics. A syllabus does not serve the purpose unfortunately.  Thank you for your understanding.

I'm quite afraid that my application shall be rejected because of this. But what can I do? That was the last thing my university could provide me.

Did you call this a syllabus or did they? This is not what I would call a syllabus. If you called it a syllabus, the person receiving it probably didn't even look at it before telling you a syllabus is not what they need. This looks like a transcript. Call it a transcript if someone is asking for a transcript and this is the document you have to provide.

The transcript shows your marks in the subjects, the syllabus gives them an idea of what topics were covered in the subjects. This is all I needed to transfer to a foreign University. I expect that Bryan is correct that they're simply not looking at the information you've provided them, possibly in part due to language confusion. If they don't accept the syllabus, then I'd suggest explaining your issue to the teachers of each course, and maybe they can flesh out the information more fully in an email you can forward. It wouldn't hurt asking your intended University what they are looking for.

Is it clear that they're asking for a document directly from your precious university with this information? Since I don't know how these things work, I would have guessed that I need to write a document answering the question (and attach some official documents to the end of my document in order to demonstrate that what I wrote is accurate).

How have previous successful applicants from your university/country, to this university, handled this? Is there any online group (WA/reddit/LinkedIn) where you could check?

I think you need to speak to someone at the university (as in a real human, rather than an email address), as that transcript looks fine to me (as someone who reviews grad student applications at a UK university).

Basically it appears that the admissions officer expects to see a number of modules (+marks) for the individual components if your studies. Taught by different professors, examined individually, econometrics and microeconomics are very different subjects.

@PauldeVrieze did you have multiple separate economics modules/ exams? It is common,  particularly in the UK/USA to break things down into modules,  but,  for example,  my degree in Cambridge wasn't broken down into separate modules - I just had one exam at the end of the year.

To add to this, this is a situation where I would call the department. If there isn't a phone number associated with the application process, try looking up a departmental administrative assistant on the university website. Ask them if they have received your latest email and documents and explain that this is how the University releases transcripts. Maybe there was simply a misunderstanding. If they still don't accept this, ask them specifically what information they need, then email your University registrar with the department admin CC-ed and ask if they can provide that information.

They have emailed me this:
"Dear Applicant,
Please see the module requirements for MSc Economics in this webpage:
https://www.birmingham.ac.uk/postgraduate/courses/taught/econ/economics.aspx#EntryRequirementsTab
Your provided transcript does not serve the purpose to review these module requirements.  Thank you for your understanding."
I'm a little confused as what they are saying. Are they saying that module requirements are missing from my uploaded transcript? Or that the uploaded ttranscrript is not sshowing the information sought for?

The requirements state you need good marks in "Microeconomics, Macroeconomics and Econometrics or Statistics modules". You don't have these modules,  you just have "economics ". Can you demonstrate that your economics course covered those 4 areas? Better would be if there were any way of demonstrating good marks in each topic.

There is also a link to look at surviving requirements for specific origin counties. I recommend having a look at that for your country to check there isn't anything in there.

@IanSudbery my degree was in the Netherlands, and there were around 11/12 modules per year (only about half economics related in my case - degree in business information systems) on a large variety of subjects.

I suggest you try to get out of your current position as middle-man in this conversation by getting the UK uni and your current uni to communicate directly. Ideally by phone, rather than email.
Two specific ideas:

Ask the UK uni to contact your uni if they need more/different info. This probably won’t work because it requires effort by the UK uni.
Ask your uni to make a phone call or write an email that says something like “we have provided all the documents that are available, and we have always found them to be acceptable to universities world-wide, including the UK, so we don’t understand what else is required”.

Good luck.

I would try to put them in contact with your university (and vice versa) so that it is clear what the university can provide and what it cannot.
If it is clear to the place you apply to that you are providing all that is possible and that it is honest and accurate, you may be ok. But it is others that need to give that assurance.
A professor of yours might serve rather than a registrar or equivalent, or a department head. But there are no guarantees.

I don't think an admissions committee would lift a finger to run this down.  An approach that requires less effort on their part would be m9re effective.

@ScottSeidman, my expectation is that it would be a staff member, not the committee that followed up.

I've faced similar situations, and here is how I solved them:
Assuming the information the target university asks for actually exists, you compile the information yourself. In this case, this would mean identifying stuff like "I took this much teaching on Microeconomics, and I got that grade. I took...". You then approach someone at your home university to confirm the correctness of your data. Maybe a professor is willing to put this on letterhead and add a statement that to the best of their knowledge, the data is accurate. This could be something stamping it with some kind of official university stamp. Now you have a document you can show to the target university.
If the requested data doesn't actually exist, maybe because teaching at your home university works very differently from the expectations at the target university, you need to contact either an actual decision maker or a supportive academic at the target university to discuss what the next best thing is.

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


text:
What is a committee looking for in a dissertation proposal?
I've started narrowing down the scope of my dissertation, and I have one year before I need to defend my proposal.  I'm curious to know what is expected from a dissertation proposal.  What are the key elements that I should include / exclude?  What criteria typically used to judge whether the proposal defense is successful?  Are the committee's feedback of the proposal typically used as a criteria for the full fledged dissertation defense?

Only your committee can give you a definitive answer.  What does your advisor say?

Good advice here: http://matt.might.net/articles/advice-for-phd-thesis-proposals/

JeffE is correct; talk to your chair and get feedback. That being said, you'll want to include the following in your talk:

An overview of your research topic
A discussion of relevant literature (to demonstrate that you've researched the topic)
A discussion of your specific problem
Another literature discussion, much more focused on your specific problem
Any preliminary results of experiments you may have run, if any
What you plan on doing for the next few years
(Possibly most important) Any specific issues/problems that your advisors have raised about your research. You should specifically address these to show that you're paying attention to what they say and that you listen to their comments.

The best way to prepare is to talk with everyone in advance and find out what their objections/comments/issues/questions will be as much as possible, and then do your best to prepare for that and any related issues. If that sounds like a lot of work, it's because it is a lot of work.
Dan's comments are also spot on; you may have some very difficult committee members who will ask all sorts of questions, and you should make sure your advisor is on your side from the get-go.

Should one also have partial or preliminary results to present as well?

Good point; I added it. Do make sure, though, that you have something to propose; I have a friend who tried to present his completed thesis work at his proposal, and got a lot of extra work because of it.

So, are you saying that one should hold back if you already have lots of results?  Is this a good strategy?

@Paul - No, I'm saying that you should make sure to do your proposal before you complete all your experiments. It isn't really relevant to the question, and it shouldn't be an issue for most people.

Ultimately, your committee has total say about what constitutes a successful thesis proposal.  As JeffE mentioned, you should ask them (particularly your chair).  In my case, I scheduled short meetings (10-20 minutes) with each of my committee members.  (Ideally, this should happen at least 3 before your proposal.)  I asked each one "What are you looking for in my thesis [proposal] for you to judge it as successful?"  I don't remember all of their answers. From three of the four members of my committee (including my chair) I had clear expectations, which I knew I could meet.
Sadly, from one member, I never really got a clear answer.  Not surprisingly (in retrospect), part way through my presentation he complained because he thought that what I was presenting was off-topic.  In the end, everything was okay.  However, I think he was a bit unhappy and had to be persuaded to pass me.  The single most important thing you can do to guarantee a successful proposal (or defense) is to make sure that your chair will strongly support you if you get resistance from another committee member.  Besides that, you should schedule meetings (as I mentioned above) to ask what your committee is looking for.  Start with your chair and get advice from him/her about how to approach your other members.  If you don't get a good answer from one member, try scheduling another meeting to ask again (perhaps after meeting with your chair a second time to ask for help on how to approach the troublesome member).
Edited to account for EnergyNumber's comment.  My own experience (mentioned above) was actually with my thesis defense, but I think the advice applies equally well to a thesis proposal, so I've edited my answer to address that (since it was the subject of the question).

I don't think that the question ist about a thesis defence at the end of the PhD: it's primarily about the proposal defence at the start.

@EnergyNumbers Oh, you're right.  My mistake.  I think most of the advice I gave applies to the proposal too. s/thesis defense/thesis proposal/g;

What are the key elements that I should include / exclude?

Your university should have clear regulations about that. Also, ask your supervisor/advisor.

What criteria typically used to judge whether the proposal defense is successful?

So, I'll list a few that should be generally applicable, but if your supervisor feels confident to have you submit your proposal, it's likely you've already met the criteria or close enough to doing so. While the committee can reject your proposal, this isn't like an exam at the end of a course; if you do your work seriously up to the proposal you should pass without surprises. In fact, the defense of the proposal is an opportunity to get useful feedback and guidance.
A few general criteria I believe are always applicable:

Novelty - It must be something that hasn't done before, more than a rehash of existing work. This could be in terms of the results (discovering something we didn't know, creating/manufacturing something which had not previously been attainable) or the methods (e.g. using a novel technique to prove an important mathematical theorem).
Relevance - Your work on efficient separation of mud cakes by the time spent in the sun might not be useful to anyone even if it's novel. This criterion may degenerate into "fashionability" - hopefully not.
Expected breadth of work - The research should involve enough work to be significant but not too much as to risk you not concluding it even with reasonable diligence. Of course, you might eventually be able to get it all done in a week if you're a genius and it's theory rather than experiments; but that's not likely.
Your background - Is it reasonable to assume you personally will be able to carry out this kind of research?
Means and environment - are your supervisor, research group, faculty, university and related facilities and resources likely to be sufficient support for you to pursue your line of research effectively?

Are the committee's feedback of the proposal typically used as a criteria for the full fledged dissertation defense?

So that really depends on your field and on the composition of the committee. Very often the answer is "no" (from my own personal experience it was "not at all"), but it's certainly possible.
Note, however, that if your results get published in journals and conferences, the final dissertation is, again, unlikely to be rejected - since the community will already have recognized your contribution.

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


text:
Are there any particular grants or fellowships in the sciences specifically for non-traditional students?
After obtaining my masters degree, I spent four years doing other things before returning to pursue my PhD.  My advisor has a Dept. of Energy grant which has funded me, but the grant will not be able to fund me for my entire PhD program.  I'll probably need another two years worth of funding to finish my degree.  I may not be able to get a Teaching Assistantship, as they are limited at my institution.  I've also noticed that I don't qualify for some fellowships (like NSF GRFP) because I am not a "traditional" student.  What are some other options for students in the latter part of their PhD program (i.e. dissertation)?  Particularly, for the field of computational science?

Actually, the NSF graduate research fellowship program does award a small number of fellowships to "non-traditional" students, who either spent a significant time out of school or are undergoing a significant change of field.  You still need to apply by the end of your first year in your new program, and you'd have to make a strong case that applied math → computational science is a significant field change (on the order of physics → biology).

@JeffE: I know... Unfortunately, computational science is too close to my master degree to justify it.

In general, you're in a very tough situation. Most of the "big name" fellowships are moving away from funding older students, on the relatively flimsy rationale that they're making a bigger impact by funding less experienced students from the start of their program.
There are a few programs that do support late-term graduate students; these are typically known as dissertation fellowships. Examples include the Ford Foundation Dissertation Fellowships, but these also have other restrictions associated with them (for instance, a commitment to a teaching career). Similarly, the Fisher Doctoral Fellowship primarily supports environmental and energy-related research, while the Merck Fellowship Program is for African-American students in biomedical-related fields.
So there are resources available, but they are certainly very limited in scope, and you'll need to make sure you meet all of the qualification criteria. The other problem for you is that these fellowships are typically only one year in duration, so if, as you say, you are two years away from finishing, you will need to find some means to finance one year of study, either through TA's or other sources of funding. In the meanwhile, you should talk with your advisor if there are other resources within the group to help you—at least partially.

Thank you, aeismail.  I'll look into these opportunities.  It's a shame that there isn't more for us :(

Yes, it is. Funding for graduate study in the US lags way behind many other industrialized nations.

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


text:
Where can I find information about upcoming special issues in a field of study?
How can I find information about upcoming special issues related to a special field of study? There are good websites for upcoming conferences but I could not find any place to search for special issues.

@dgraziotin Thanks. I thought it only indexes conferences, but it awesome for special issues as well.

In addition to the two sources mentioned by William, I can add professional societies or their equivalent. It is usually these that organize meetings that result in special issues. It is rare (may differ between disciplines) that journals themselves, unless they somehow specialize, provide open special issues around a theme. Usually, it is then by invitation, or papers emanating from a workshop or symposia etc.
Hence, looking for especial issues may be a dead end and you should be looking for activities that lead to such issues.
As a final note, the term special issue signals an unregular issue in a scientific journal open for submission of manuscripts. Many conferences issue proceedings but then the prerequisite is usually attendance at the meeting and presentation of the paper there.

As far as I know, there is no website referencing special issues from different journals. However, I see two potential ways to stay informed :

Make a list of the good journals in your field, then browse their website for information (might take some time, especially to stay up to date).
Use social networks. Many journals have twitter accounts and/or blogs and they are likely to advertise their special issues through these media.

Recently, I have found one website to get special issue information regarding sci/scie indexed journal. Please go through the following website.

https://research.com/

Welcome to academia.SE. It is a good practice to indicate whether you are affiliated with the website or not.

@TommiBrander no, I am not affiliated with this website.


text:
When you reference an article, is it always expected that you have actually read it?
Naturally I would say "of course", but my current situation makes me doubt.
In my paper I'm briefly covering various alternative cryptographic constructions. I am (of course) familiar with all of them, but I have not (nor have the time to) read the full papers I'm actually referencing. The reason for this is that they contain lengthy specifications complemented with cryptanalysis.
I'm in doubt whether it's acceptable to reference said papers without having actually read them. Is it acceptable to do so?

Related: http://academia.stackexchange.com/q/12391/64

Also related: http://mathoverflow.net/q/43147/12357 and http://mathoverflow.net/q/98821/12357

Part of this is parallel to asking whether in mentioning the existence of a person, or reporting that they said some particular thing, is one endorsing the person or the assertion. Surely not.

When you reference a paper within whatever your context may be, you are possibly doing several things. First, you may make claims and use other authors names and reputation in support. Second, you may take "facts" from a paper and propagate these facts through yours.
Nothing wrong with that? Not generally. But, what happens if a paper makes a claim that is not at all well supported by the study? You run the risk of propagating errors so that when somebody uses your paper as a reference the original paper is still further away and after a few such iterations the source may be completely forgotten. There are many instances where either errors have been propagated or where "truths" have slowly been misquoted so that they turn into errors. This is clearly not what we want in our papers.
I would therefore say that one needs to (critically) read a paper enough to make oneself sure that the facts can be trusted and that no misinterpretation has occurred in the paper to be referenced or earlier. Hence relying on, for example, other authors references is a very weak link in the chain. One has to try to back-trace vital information as much as possible. Misunderstandings may not necessarily be born out of malice but just by oversight, but the end result is still the same. To therefore, for example, simply gloss over the abstract and use whatever seems to support some idea or vice versa is far from satisfactory.

I'd agree, this is an ideal to be aimed-for, in any case. But it's surely subject-dependent. In mathematics, chains of back-reference can be both wide and deep, and involve nearly-inaccessible sources, so that often it'd be infeasible to check everything personally. That said, indeed, if people don't check, things can get out of control... as they are, to some degree.

Good point, reminds me of https://en.wikipedia.org/wiki/Cargo_cult_science

Here is my take. This is not high school and nobody is going to check whether you've read the papers. The idea is to provide references for the readers for further research not to show that you've read all the literature. Naturally, of course, you don't want to cite a paper that has nothing to do with the subject at hand so you need to have a grasp on its content but nobody expects you to be an expert on every detail in the 100 publications that you reference. Sometimes I only read an abstract to decide if I want to reference the paper or not.

Hm, I don't 100% agree with you, as Peter Jansson stated by citing a paper you basically attest "the statement due to which I cite that paper is true" - if you only read the abstract which usually merely describes the result you may end up vouching for a big error. If you really cite 100 publications, please have the decency to sort them either by importance or put them into two or more sections so one does not have to read 100 abstracts just to figure out only 13 papers are actually important


text:
Monochrome vs grayscale in scientific journals?
Many scientific journals accept only black & white articles.
Does this mean that only monochrome (black and white only) articles or also grayscale (gray is OK) article are OK?
The same question holds for books.

What did your editor say when you asked them?

@EnergyNumbers They have not (yet) replied

I have a confession to make.  I absolutely ignore it when a publication tells me they want grey-scale or black and white.
Yes, they want it because somebody is going to put something on some dead trees, they're going to be cheap about it and not use color, and somebody might actually pick up a dead tree and see my mangled image.  But either they're also going to put it in a PDF, or else I'm going to put a pre-print in a PDF and that PDF is going to go online in all its radiant rainbow glory, and that is what people will actually read.
So [CENSORED] monochrome.  That is so 20th century.

Good point. I prefer to read on the computer. But quite a few people I know prefer to print the pdf and read that. And many people prefer to print black and white.

@JeromyAnglim Color printers are very common, and if a figure doesn't render well in B&W, you can always look back at the PDF.  There are just too many things that color is useful for to throw it away so lightly.

I do print out all articles I find worth reading more carefully, and never in colour.

I generally agree, but I do also check that my figures are still (at least mostly) readable in monochrome before submitting. Not only do some readers like to print things out on paper, but there's also the little issue of colorblindness to consider.

@IlmariKaronen Color-blindness and black & white are rather different issues, actually: I, at least, always try to keep color-blindness in mind, particularly not doing red/green distinctions when possible.  If that has a good byproduct in greyscale, well, I may never know...

There are many kinds of color blindness. While deuteranomaly (poor red/green discrimination due to a mutated green pigment) is the most common type, about the only thing you can be reasonably sure about is that a figure that looks OK in monochrome will be readable to most people. Sure, not relying too much on red/green contrast is a good first step, but not relying (only) on color to convey critical information at all is even better.

@IlmariKaronen It's a difficult balance, and I'm not sure where the boundary lies between supporting disabilities and retaining dimensions of expressiveness.  Do you know of anybody who has a good, principled metric for how to draw the boundary?  The one thing I know for certain is: it's not publishers I care about, it's communication with fellow researchers.

I can't say where to draw the boundary (and I suspect it's the wrong question to ask anyway), but here's a nice page on designing colorblind-accessible figures. IMO, the key take-home message should be that good use of color can make your figures easier to read, but color (hue) should never be the only thing that conveys any important distinction, at least not if you can avoid it. See the good/bad examples in particular for some very useful design tips.

@IlmariKaronen Awesome!  Thank you for an excellent resource!

In general some degree of half-toning will be used, meaning that a limited set of grey scales can be output in the printed journal, so figures supplied in greyscale should come out in greyscale.  Figures supplied in colour may (i) upset the editorial staff or software (extra hassle for you); (ii) be chargeable (to avoid this you may have to resubmit figures, extra hassle); (iii) reduce to greyscale rather inconsistently with what you expect.  So if you submit colour figures (and I generally do), you may as well go for good clear distinctions between data sets, and print B&W yourself to check.
It is very possible (and in some cases required) to produce most figures in a way which either doesn't hinder the B&W reader too much, while still aiding the reader who works in colour.  Two examples:

lines on a graph can be dashed etc. as well as coloured, with colours chosen to render different shades of grey.
colour maps can easily be chosen to be continuous and monotonic -- though this isn't usually the default.

Both of these approaches are a small step towards helping colour-blind readers as well.
You can't assume your readers will work on screen -- an interesting paper may want to be annotated (I've not yet found a pdf-markup solution that comes close to pen&paper for this).  Paper copies are also easier on public transport unless you have a very good and large tablet.  It's also not uncommon for B&W printing to be easier (less far to go the the printer) and much cheaper (or uncounted and essentially free) than colour.
Much of this was going to be a comment presenting the opposite point of view to @jakebeal, but another couple of sentences made it an answer.

First, off: I am not sure that many only accept monochrome or B/W (usually implying grey-scale) figures since trends quite some time are for digital publication only (where colour or B/W, technically, is an irrelevant question).
The question about true Black and White versus grey scale is a matter of technique. In the analog days of printing grey-scale images had to be rasterized and this may have been a problem for some reproducing grey-scale illustrations. Today rasterization is done digitally within the printing process and should not pose any problem. It is therefore relatively safe to say that providing grey-scale illustrations will be fine. As I stated above B/W includes grey-scale nowadays and since quite a long time back.


text:
When reviewing a resubmission, can I request a version with changes highlighted if the journal does not require it?
Reviewing is time-demanding. It makes huge sense to re-review if comments and changes are submitted. While first review takes a lot of time, the second can be very quick.
If authors provide a version that shows the changes - this makes re-review very fast. They also don't have to spend too much time on resonse-to-reviews letter.
Can I simply reject to re-review if such changes-highlighted version is not provided?

http://www.adobe.com/products/acrobat/file-compare-two-pdf-files.html might be useful

Some more tools (including cheaper ones) for this purpose are listed here: http://superuser.com/q/46123/119172 (the question mentions windows, but some of the answers apply to other systems as well)

You can certainly ask for it but if the journal does not require authors to provide such files, you are not likely to get one. So why ask? Well, by asking you provide the editors with the wish from reviewers to see this as a permanent feature and in the end such changes may be made by the journal in their instructions for authors.
The reason why I think it is unlikely your request will be immediately heard is that editors usually handle many articles and may work under severe time constraints (often on their free time outside of work). Communicating back and forth with authors of varying background requesting new versions of manuscripts is usually a time consuming venture that could delay the process by weeks, depending on the responsiveness of the author.
So, there may be a good reason to make a request but I would not expect the wish to be heard in many cases.

You could point out that if you don't get something that shows the changes, your review may be delayed by weeks as you trawl through the whole paper again. But threatening to withdraw as referee altogether may annoy the editor, who maybe is someone you'd rather be on good terms with.

What format for such "changes-highlighted version" would you like? Maybe you could just use a tool like DiffPDF?
Another problem with your original intent is that you're going to re-review by looking only at the "changes highlighted". What if there are other changes, not highlighted by the author?

OP probably has something like Latexdiff in mind: https://www.google.com/search?tbm=isch&q=latexdiff


text:
Is it useful to do an MBA after PhD?
I have heard of people who have gone on to pursue an MBA after their doctorates. What are the advantages/downsides of this?
Wouldn't the companies recruiting them after MBA value their doctorate experience less compared to the experience gained at an MNC? Is there a risk of them being valued as "failed" doctorates?

MBAs and PhDs are two different things. If you want to run a business, do an MBA.

It really depends on the degree and what you ultimately intend to do... What do you plan to get your PhD in, and how do you plan to use an MBA as part of your future plans?

Nature just had an article about it: http://www.nature.com/naturejobs/science/articles/10.1038/nj7523-523a

No degree ever goes waste. Most people with PhD and MBA acquire director positions in companies.

"no degree ever goes waste" [citation needed]

"Most people with PhD and MBA acquire director positions in companies." That seems insanely hard to believe.

A qualification regardless of level and field of study is never a waste, one needs to realize how to use it wisely and appropriately. As we navigate life we shift perspective and interests, our education choices therefore need to reflect this. Ph.D provides sound research focus, MBA provides sound business and leadership focus. The two combined is a great and electrifying combination.

A qualification regardless of level and field of study is never a waste — [citation needed]

@JeffE I can indeed think of many examples where a qualification was indeed a waste. However, a (good) MBA is not usually one of those cases.

Right.  A good MBA is not one of those cases.  But many (if not most) MBAs are not good.

PhD = specialist in a subject, research skills, critical mind
MBA = Broad generalist, management, problem solving
The focus and scope is not the same.
Also like it was said most researchers who want to climb the ladder need to take the management track which often require an MBA. Put simply an MD is an MD but a hospital manager needs to be an MD and MBA.
Also to teach at a business school other than math or economics you normally need an MBA. Best is a Phd/MBA but while a lowly MBA can teach that is not usually the case for a PhD.

If a person is smart they will market their experience during the acquisition of their PhD as also providing them with the problem solving and management skill sets. If you are going to be successful in research or business these are good things to have.


text:
With a software engineering bachelor's (BE), how can I work on finding a cure for cancer?
I am in my last year of studies for a bachelor's degree in software engineering and I am currently considering different options for my career path. I don't have any background in medicine, but I would love to work in the medical/research field, specifically relating to cancer treatments. What would be the best/quickest way of doing so, considering my background? I don't plan on doing an additional bachelor's degree in medicine.
Here are some options I came up with:

Find a full-time position in biotech after my bachelor's degree
Do a master's degree in software engineering and find a full-time position in biotech
Do a master's degree specifically in biomedical engineering (if possible)
Doing an additional master's degree in biomedical engineering

A "cure" for cancer? Unlikely. But improving treatments for cancer? Much. Radiotherapy nowadays is basically very advanced software and physics. I am an electrical engineering that did a PhD on cancer treatment, in particular computational methods for 4D imaging with tomography.

There’s a fifth option you had not listed: Contribute actively to the development of major projects used for this type of reasearch, such as AMORPHA, BOINC, or EMBOSS. That approach requires much less knowledge of biotech and bioinfomatics and thus would be easier to get into, though you would also be making a much less direct impact.

Tuning AI systems to handle cancer research is also possible. If you have the drive, you should talk to student advisors on how to progress in this path. If they can't answer you, they can definitely find people that can.

you definitely need to build a connection with someone in cancer research field, also do  you seek financial reward from this or purely a side hobby? that answer would greatly differ depending on your skill set.

@AustinHemmelgarn There is a 6th option.  Earn a comfortable living.  Eat fruits and vegetables.  Get your covid-19 shot.  Minimize driving.  It is boring but curing cancer requires small changes in behavior from everyone.

computational biology is a huge field. It even spill into SE comunity, see for example this question:
https://mattermodeling.stackexchange.com/questions/10218/how-can-i-use-ss2-or-fasta-files-as-inputs-for-protein-folding-simulation-using

@emory OP would like to work towards finding a cure for cancer, not finding a cure for their cancer. Additionally, the number of non-smokers and non-drinkers having throat or lung cancer should tell you a thing or two about the meaningfulness of reducing cancer simply to one's lifestyle...

+1 on Ander's comment. Basically, at the moment there's a tendency towards the notion that cancer as such is likely to be inherently incurable. As for the question, you'll be welcomed with open arms if you're good at visualisations and/or simulations.

@EarlGrey if OP has cancer it is probably too late.  Non smokers and non drinkers do get cancer.  It is not just lifestyle.  However cancer alley exists.  So a huge part of "curing" or delaying cancer is not obviously cancer prevention but pollution reduction.  It is very complex.

I have also read research that 100% of ultra old men have prostate cancer.  Most men die long before they reach ultra old status.  I like to think that society is using my computer skills for betterment but if all ultra old people have cancer then my meager efforts are actually causing people to live longer and are actually raising the cancer rate.  Of the 1M people Trump killed through inaction, a bunch were going to get cancer.  He cured them!

I am a research administrator who has supported a machine learning professor for 8 years.  She doesn't do cancer research, but she is a CS person who works with hospitals and analyzes their data for them (mostly in autism, diabetes).  CS departments are getting a lot more time with health data.  You could look into a job like that, e.g., as a post-bac if you are interested in moving up into an academic rung.  Alternatively, I have a research administration friend who works at a Cancer Institute.  You could do IT-like work at a Cancer Institute or other type of hospital and support the work that way.  Research administrators frequently cite supporting research as why we stay in the field (which is incredibly stressful).  I have been essential in training PIs in how to get grants for 15 years--sure, I'm not curing cancer or discovering the next big thing--but I know that I am crucial in making those discoveries happen; faculty tell me this, because they don't want to do the work I do, but it is essential if they are going to run a lab at all.
Consider using a job search portal with a job skill you have, e.g., "Agile", "python", etc. + "cancer".  You just have to know what type of job you are looking for (academic vs. staff).  If you look at a program administrator type job in CS that is oriented towards health, that might be a really great fit.  It is incredibly difficult to find qualified folks who will do that work.
Here's an example.

+1 if only for pointing out how much an industry depends on software, but kinda treats it as a necessary evil. The one-trillion-dollar electronics market is supported by the ten-billion dollar design automation market. The former doesn't exist anymore without the later... but suggest raising prices to enhance development and listen to that one-trillion-dollar industry howl. Critical software development is high stress because the specialist PhDs don't want to share credit - but it's just as important as the PhD specialists in their fields.

No additional bachelors is likely to be of much help. It would only get you an entry level position, likely far removed from research. You need something more advanced and more related to medical research. Ideally a doctorate. In the US, you could probably apply directly to a doctoral program, but elsewhere it might be more of a problem.
But a cure for cancer, or any other complex disease, requires training and skills in medical research. That is a long way from SWE. The processes are very different.
Yes, medical researchers need some amount of programming to back up their studies, but that is just support.
A research based masters in the biomedical area, whether engineering or not, might be enough.

"just support" still helps and is necessary, though admittedly not very glamorous. You don't have to be "the hero of the story" to make a positive contribution.

As others have mentioned, it will be difficult for you to pivot into the research side of things without doing a significant amount of retraining in the domain. It's also been mentioned that this will therefore cut off the "glamorous" side of the job. However, let's be realistic: Research is about incremental advancement. Disruptive change can happen, but it's incredibly rare -- increasingly so, I would anecdotally say -- as science becomes a huge enterprise involving hundreds or even thousands of people. My point being, there isn't really a glamorous side!
This is a good thing, as it will allow you to focus on your strengths; that is, software engineering. Modern medical and genetic research -- which covers, e.g., somatic mutation (cancer) -- involves huge amounts of data and sophisticated tools to process and analyse these data. The algorithms for these tools are often designed by domain experts, but software in science has a reputation for being, let's say, "thrown together". (Which makes sense, given the economic factors at play.) A software engineer thus has quite a bit of leverage to improve existing tools or develop new methods that scale with big data (and I mean really big; petabytes).
tl;dr I would look into a masters in bioinformatics. This will give you the domain grounding you'll need -- although it's not strictly necessary, but will give you an edge -- to get into the space and make positive contributions to the field.

As a software engineer, you can do a lot of work in medical fields with little to no medical backgrounds. You will obviously have to learn about the subject you work on, but rarely to a point where you'd need an entire undergrad on a related subject to understand it. However, as it was pointed by other answers, you'll struggle to pivot to something entirely focused on biomedical, such as "cancer treatment".
It obviously depends on your location, and which type of medical research you want to focus on, but I'll give you the example I know about, which is mostly mine and people I work with.
I did my undergrad in software engineering and a Master in AI. After that I found a PhD in deep learning, which is applied to a certain type of medical imaging, specifically on the subject of lungs cancer. The goal is to develop and improve this new modality to replace the current gold standard in cancer detection, to improve the diagnostic and prognosis of cancer.
I also did an internship where I worked on a totally different imaging modality, which was used for blood vessel detection, and I worked on semantic segmentation (both with image processing and deep learning).
In both cases for me, and similarly for the people I work with, learning about the medical side was not "easy". You need to go through a lot of paper (as well as other support). Which is why a PhD can be important.
Additionally, in the example I know about in industry, a lot of researcher offer ask for a PhD (not all, and the requirement may not be mandatory, but still).
While the answer may not exactly what you are looking for, i.e. "cure for cancer" (which is an extremely vast domain anyway), with a SWE background, you can very well make progress in the research against cancer.
The example I can give are as a machine learning researcher for detection of cancer (such as plain detection, classification, segmentation of tumor margin for operation, etc). You can also work as a software developer to create the software that will operates on the different imaging modality. Or create tools that will be used by researchers.

Indeed. I am one example and even got my name on a Nature paper!

If you want to be a researcher you will need a masters degree (and eventually a phd).  For someone like you with a techinical background (Mathematics, Computer Science, Physics, Software Engineering etc), who wants to go into biological research you should be looking for a masters in Systems Biology or Bioinformatics.
I have a similar background (Maths/CS undergraduate) and I made the jump into biological research after my PhD, it was a learning cliff - but fun!  I now teach systems biology masters students and we take students with all different backgrounds.   Those with technical skills do very well in our masters programme and often end up going on to PhDs and becoming researchers.

Many answers recommend getting a master's in bio-informatics, but with your background in SE, you could also consider a different degree: Artificial Intelligence. That's what I did. I found a program that specializes in simulation/computational modeling/neuroscience, did my master's thesis at an academic hospital, and now I'm doing a Ph.D. on using AI to detect dementia. I'm sure you could apply many of the same skills to cancer research.
There are many advantages (and probably some disadvantages) to doing it this way. For one, the switch from SE to AI will probably be smoother than when you try to catch up on 3 years of biomedical knowledge. You can always acquire domain knowledge as it comes along. It will also be much easier to switch careers in the future if you have an AI degree - you could move into any industry you like.

Find a full-time position after my bachelor's in biotech

This.
I've worked in biotech  / bioinfomatics for 15+ years, and one of the biggest problems is poorly written and maintained software and datasets, and a general lack of understanding of what computers can and can't do. For me it is paid well and with good conditions & security (as most software engineering careers do, and doubly so once you have some bio experience). It is very much a team effort though, and there are plenty of biologists and scientists that can do the bio side, so good communication skills will help.
I suspect you could find a very fulfilling position even if it isn't directly science/research related. Something as "boring" as an appointment system or medication reminders can make a huge difference to quality of life for patients!

Since you have no experience in wet lab, you have to go down the path of computational research.
In order to do that you have to take a thesis about Cancer research in Masters. Your supervisor must be from the field you are looking for.
Next, you should go for a Ph.D. as Masters won't be enough to gather experience.
After a huge amount of self-study, you will be able to become a researcher in Cancer research.

Why get a masters if you plan to get a PhD eventually? And if you're getting a PhD, there's no reason to foreclose everything but computational research. You can learn those skills, even if it means spending your first year of a PhD program taking upper-division undergrad courses. This answer really just boils down to "get a PhD", which is definitely sufficient to get into academic research on cancer, but doesn't seem to answer the question that was asked.

@CodyGray-onstrike, Why get a masters if you plan to get a PhD eventually? --- Coz, I don't know where he lives. Europe doesn't allow a Ph.D. without a Master's.

@CodyGray-onstrike, And if you're getting a Ph.D., there's no reason to foreclose everything but computational research. --- Coz, that would simply be a total waste of time. Besides, wet lab jobs are not as frequent as computational jobs.

@CodyGray-onstrike, This answer really just boils down to "get a PhD", which is definitely sufficient to get into academic research on cancer, but doesn't seem to answer the question that was asked. --- What is missing in my answer?

@CodyGray-onstrike Where I'm currently studying (Quebec, Canada), it is generally required to get a master's before a PhD; I didn't realize you could actually skip that part in different countries:') I am considering studying abroad though, so I guess it still applies.

I think this answer takes a very narrow view of what can be 'cancer research'. For example, there are algorithms which detect cancer cells on MRI scans. To build this you don't need an ounce of biomedical knowledge and a lot of computer vision knowledge, but it's still cancer research. People with a Ph.D. in maths or physics cross over to computational modeling all the time.

If you want to work in research on cancer or in another biological field you will need a PhD, and prior to that a masters, options for the masters could be bioinformation, biotechnology, bioengineering, biophysics which would be natural ways to move from a more technical focus to gain skills in biology.
Given your lack of background in biology, you should probably do some background study for these masters. You could also look around in the biology department at your university and see if there is a biology colloquium that you could attend and perhaps speak to some of the researchers there who might be able to direct you better. They can probably also give you some insights into the field which might help you decide on what you really want to do and how to get there.
Once you have the masters, then you can apply for a PhD on a topic of interest to you, if you can find a supervisor who is willing to supervise you for it. If you apply in the US then the masters is merged with a PhD and you can go into a PhD program directly from your bachelors. However I would recommend you do a master's program in order to develop your background in biology even if you choose to do a US PhD (and are therefore in effect doing 2 masters).
Something the other questions haven't mentioned is that there is a developing focus on complex systems in biology research. Mathematically this is probably similar to the complex systems and ecosystems that you're familiar with in software and are currently studying. in this language you can probably think of cancer as a rouge process that is requesting resources (RAM, comp cycles) while avoiding the kill commands. Similarly you could probably think of parts of the immune system as algorithms that rely on pseudo random number generators. You may be able to leverage your familiarity with complex systems from computing if you learn the associated biology (or biophysics) to give a different view on these kinds of problems. This might not just be cancer research but other biological process or tools (I'm imagining CRISPR here).
PS: for context I'm a (quantum information) physicist and not a biologist, so it is natural I'd think about biology from a computational perspective.

@fordcars Does it have to be scientific research, or will engineering do? Realistically nobody is going to "cure cancer" unless they get a product to market, and that involves engineering spanning a number of disciplines: microfluidics, mechanical, electronics, and software.
I retired a while ago from a career in software engineering, and the last 12 years were spent working on medical devices, including two cancer projects: we developed code to drive robots that were amplifying RNA for a autologous tumour cell vaccines; and we developed the software for a test for HPV, the precursor to cervical cancer (instead of curing cancer, why not prevent it instead?).
If that is a path you want to go down, you might benefit from learning about developing software for medical devices. IEC62304 would be a good start.

I'm definitely open to the engineering side; maybe even more so than research (considering it is the field I've been studying). That definitely sounds like a career I'd like to have. I'll take a look at the standard.

@fordcars Diagnosing cancer is very important; the earlier we find the little blighters, the easier it is to kill them. Have you looked at kaggle? There have been several competitions aimed at detecting tumours, e.g. RSNA-MICCAI Brain Tumor Radiogenomic Classification. Maybe you could sharpen your skills?

You could consider the emulation of biological structures in a virtual environment. It may be easier to join in on an existing project, rather than having to do another degree. Bonus points if you make it a Citizen science project, when people around the world can effectively contribute to fighting cancers and other diseases, including everyday citizens who do not have any medical or biological expertise. Distributed computing projects are a fantastic way to make use of people's computers, smart phones and tablets to donate their computing power to solve real-world problems.
There have been lots of distributed computing projects.
Here are just a few select distributed computing projects running currently:
Folding@home, Rosetta@home - Uses the computational power of people's computer systems to 'fold' protein structures in 3-dimensional space. Protein structures are 'folded' (compacted) in an attempt to reach their optimal state, a stable shape that allows them to function correctly and survive in their immediate environment. Solving naturally occurring protein structures helps scientists understand the function of those proteins more accurately. Novel protein structures can also be created to aid real-world problems, such as treating diseases (vaccines), or creating new materials.
Mapping Cancer Markers - Project that attempts to find markers that relate to different kinds of cancer from the tissue samples of cancerous patients. The markers are compared to identify patterns of markers, to detect signs of cancer growth earlier and customise treatments for specific patients based on their genetic profile. This is a child project of the World Community Grid program, which has featured over 30 different distributed computing projects.

You could also consider the gamification of biological structures, which could make it more appealing for people to install and try out. Existing projects incorporate the 2D or 3D modelling and sequences of biological structures with the goal of allowing everyday citizens without much knowledge in the field of medicine, to contribute towards research in curing various diseases, including cancer. The structures may represent the inner-workings of diseases, or the medicines to fight them with, with the intention of understanding more about them in a virtual environment on a computer system.
Users of a computer program that employs this concept would be expected to interact with a spatial or logical representation of a biological structure on screen, as a kind of puzzle to be solved. The structure may be manipulated in real-time using a keyboard or mouse, and may have a suite of virtual tools that can be used to manipulate the structure in various ways, for various purposes. The gamification aspect helps to maintain their interest, while they work towards achieving a publicly recognised goal or score.
Here are some examples of existing game projects that you may want to check out:
Cancer Crusade - A 2D mobile game featuring treatment management for cancerous cells of individual patients. Use varying amounts and frequencies of chemotherapy, HAPs (Hypoxia Activated Prodrugs), and pro and anti-angio drugs, to slow down and control the growth of cancers over a period of time.
Genigma - A 2D mobile game that aims to fight cancer by studying human genomes. Originally focused on fighting breast cancer, it has since expanded to include the analysis of other cancers. Please note that the game is currently closed for data analysis.
Foldit - A 3D computer game featuring protein structure folding. Similar to Folding@home, it differs in that it allows people the ability to interact with virtual proteins structures themselves using various virtual tools in a user-friendly GUI. People are able to manipulate protein structures in real-time, and can even generate 'recipes' (think programmable sequences of tools) in the Lua language, which can run by themselves at the user's command.
Eterna - A 2D game featuring RNA folding. Similar in concept to (and inspired by) Foldit, it focuses on folding RNA strands by changing sequences of base molecules such that specific shapes are formed for medical purposes. Now available on mobile devices.
If you want to go down the path of making your own citizen science game, or perhaps even a citizen science project that doesn't require interaction (like Folding@home), consider using Unity. It is a game development environment capable of making games (and other programs) that operate on multiple platforms and operating systems, and takes a lot of the ground work out of coding. It uses the C# language natively, and other languages based on the .NET framework may also be used as alternatives.

You might consider high performance computing, which is a field that always needs people and will likely bring you frequently into contact with bioscientists needing help with scaling up their research.