Reputation Metrics Startups Aim To Disrupt The Scientific Journal Industry(techcrunch.com)
techcrunch.com
Reputation Metrics Startups Aim To Disrupt The Scientific Journal Industry
http://techcrunch.com/2013/02/03/the-future-of-the-scientific-journal-industry/
16 comments
I believe that the two problems you mention, about peer review taking so long, and mathematicians not generally commenting much online, can be solved with reputation metrics.
The reason scientists don't blog a lot, or comment on blogs, is that there aren't reputation metrics associated with that kind of contribution to the scientific canon. It is the same reason that scientists don't share their data-sets. It is work to blog, and to prepare data-sets for public consumption, and there is no reward. If we reward scientists for sharing their comments on each other's papers, and for sharing data-sets, more scientists will be incentivized to make these kinds of contributions to the scientific canon.
The same goes for speed. When the journal editor asks a scientist to peer review a paper, the scientist accepts the request out of a sense of social obligation, but immediately that job goes to the bottom of her list of priorities. She will get no credit for doing the peer review, and so there is no reason to do it quickly.
This de-prioritization of peer review slows down the whole scientific communication system. To speed it up, we need to incentivize scientists to share their comments quickly. If someone sees something wrong the description of an experimental set-up, the system needs to be set up in such a way that they are incentivized to share that insight quickly.
The reason scientists don't blog a lot, or comment on blogs, is that there aren't reputation metrics associated with that kind of contribution to the scientific canon. It is the same reason that scientists don't share their data-sets. It is work to blog, and to prepare data-sets for public consumption, and there is no reward. If we reward scientists for sharing their comments on each other's papers, and for sharing data-sets, more scientists will be incentivized to make these kinds of contributions to the scientific canon.
The same goes for speed. When the journal editor asks a scientist to peer review a paper, the scientist accepts the request out of a sense of social obligation, but immediately that job goes to the bottom of her list of priorities. She will get no credit for doing the peer review, and so there is no reason to do it quickly.
This de-prioritization of peer review slows down the whole scientific communication system. To speed it up, we need to incentivize scientists to share their comments quickly. If someone sees something wrong the description of an experimental set-up, the system needs to be set up in such a way that they are incentivized to share that insight quickly.
> The reason scientists don't blog a lot, or comment on blogs, is that there aren't reputation metrics associated with that kind of contribution to the scientific canon.
Scientists often present their unpublished data at conferences, even when the presentation has little prestige, and in fields where citing conference abstracts is rare, so the effect on one's reputation can't be quantified.
The reason that most scientists don't blog or comment on blogs is that they don't perceive these activities as contributing to scientific progress. This might be because these aren't a good format for presenting original research, because appropriate publishing platforms don't exist, or simply their fellow scientists wouldn't read their blogs. This is quite different from peer review, which most scientists recognize as an integral part of the system.
It makes little sense to create a "reputation" metric to index contributions that the scientific community does not believe are meaningful. First, focus on figuring out why scientists don't think blogging is science, and the rest will follow.
Scientists often present their unpublished data at conferences, even when the presentation has little prestige, and in fields where citing conference abstracts is rare, so the effect on one's reputation can't be quantified.
The reason that most scientists don't blog or comment on blogs is that they don't perceive these activities as contributing to scientific progress. This might be because these aren't a good format for presenting original research, because appropriate publishing platforms don't exist, or simply their fellow scientists wouldn't read their blogs. This is quite different from peer review, which most scientists recognize as an integral part of the system.
It makes little sense to create a "reputation" metric to index contributions that the scientific community does not believe are meaningful. First, focus on figuring out why scientists don't think blogging is science, and the rest will follow.
> The reason scientists don't blog a lot, or comment on blogs, is that...
So, now that I've read the comments on a few of these open-access type articles, it seems like there is so much variation among academic disciplines that broad statements about "scientists" are untrue in many cases and probably isn't a helpful way to phase things. This statement is not true in every field: in Economics (my field, you can decide whether or not we are "scientists," but we certainly try to publish in peer-reviewed journals) there are many blogs by extremely accomplished and prominent Economists. They get a lot of informal but meaningful credit for it, in some cases much more than another top publication would bring (when you go from zero to one or one to two top-tier articles, it affects your career. When you go from 31 to 32, not so much).
Just for specifics: Jim Hamilton at UCSD (my alma mater) started and contributes to the blog http://www.econbrowser.com. His graduate students started landing order-of-magnitude better jobs and interviews once the blog was established (and, just to make clear that it's not sour grapes on my part since most of them are my friends: these are jobs that the students are quite well qualified for; I think previous students if anything got too little exposure). It's a great blog that's really well regarded among Economists, and everyone I've asked thinks that the blog is bringing him a lot of (IMO deserved) attention.
> This de-prioritization of peer review slows down the whole scientific communication system.
In any field that I'm familiar with, scientific communication does not happen through journal articles. It happens through conference presentations, seminar presentations, informal discussion at conferences and when visiting other research institutions, working paper dissemination, and (somewhat, but growing) online.
A lot of that activity becomes formalized by comprehensive letters of recommendation that are solicited for every major promotion (in academia, obviously), so it gets heavily rewarded and is taken seriously.
Peer review exists as a check on those steps to make sure the impressions are right. Polish up the arguments, have an editor and referees sign off on it, and then put down a copy for the record for the people who need it to look over carefully.
If there are specific fields where that is not true, please spell them out.
So, now that I've read the comments on a few of these open-access type articles, it seems like there is so much variation among academic disciplines that broad statements about "scientists" are untrue in many cases and probably isn't a helpful way to phase things. This statement is not true in every field: in Economics (my field, you can decide whether or not we are "scientists," but we certainly try to publish in peer-reviewed journals) there are many blogs by extremely accomplished and prominent Economists. They get a lot of informal but meaningful credit for it, in some cases much more than another top publication would bring (when you go from zero to one or one to two top-tier articles, it affects your career. When you go from 31 to 32, not so much).
Just for specifics: Jim Hamilton at UCSD (my alma mater) started and contributes to the blog http://www.econbrowser.com. His graduate students started landing order-of-magnitude better jobs and interviews once the blog was established (and, just to make clear that it's not sour grapes on my part since most of them are my friends: these are jobs that the students are quite well qualified for; I think previous students if anything got too little exposure). It's a great blog that's really well regarded among Economists, and everyone I've asked thinks that the blog is bringing him a lot of (IMO deserved) attention.
> This de-prioritization of peer review slows down the whole scientific communication system.
In any field that I'm familiar with, scientific communication does not happen through journal articles. It happens through conference presentations, seminar presentations, informal discussion at conferences and when visiting other research institutions, working paper dissemination, and (somewhat, but growing) online.
A lot of that activity becomes formalized by comprehensive letters of recommendation that are solicited for every major promotion (in academia, obviously), so it gets heavily rewarded and is taken seriously.
Peer review exists as a check on those steps to make sure the impressions are right. Polish up the arguments, have an editor and referees sign off on it, and then put down a copy for the record for the people who need it to look over carefully.
If there are specific fields where that is not true, please spell them out.
I've been saying for many years - if scientists can't break past the issue of copyrights, nobody will. Academia concentrates probably the smartest minds on earth. They should do better than cowering under the tyranny of copyright. They should lead the way.
Few realize that signing over copyright to the publisher frees authors from protecting themselves in case of infringements on their creation. Few also realize the marketing and indexing power of the publisher. Break away from copyright? "Be careful what you wish for", because you're on your own from then on.
I also thought that the time lag was a non-issue for math and physics since the advent of the ArXiv. Does anyone know why more fields don't participate, or create their own version of the ArXiv?
(I've heard mumbling about how biology is different because of proprietary issues, but it's never been clearly explained to me.)
(I've heard mumbling about how biology is different because of proprietary issues, but it's never been clearly explained to me.)
In the medical field investments are on the scale of billions to bring a new drug to market, and each invention in part is somewhat independent.
On the other hand, in CS, algorithms are cheap to code and combine much more, it's always a fusion of many algorithms and patterns, so, putting restrictions on them has a chilling effect. Also, the perverse idea that adding "on the internet" to any previous idea makes it new and worthy of a patent.
On the other hand, in CS, algorithms are cheap to code and combine much more, it's always a fusion of many algorithms and patterns, so, putting restrictions on them has a chilling effect. Also, the perverse idea that adding "on the internet" to any previous idea makes it new and worthy of a patent.
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I'm missing the leap here:
> The taxpayer ends up paying twice for the same research: once to fund it and a second time to read it. The heart of the problem lies in the reputation system, which encourages scientists to put their work behind paywalls. The way out of this mess is to build new reputation metrics.
The heart of the problem simply lies in closed-access journals, and a simpler solution is to move to open-access journals, which is already happening. Reputation is not an insurmountable barrier to this. In my field (artificial intelligence) the top two journals are now open-access. No fancy new metrics or removal of the concept of journal needed; problem solved.
I view the solutions proposed here as a bit more problematic. Download counts in particular are likely to just reward linkbaity research, rather than quality research, and exacerbate the already problematic race to put out misleading hyped-up press releases. Citation counts are liable to gaming as well, and are commonly gamed by both citation rings, and by people who consciously choose the subjects they publish in an ADDish citation-maximizing way, jumping in and out of hot areas to drop off a paper that'll turn up in searches. When it comes to judging the quality of AI research, I have a lot more trust in the editorial process of the open-access journals like JMLR or JAIR than I do in gimmicky new metrics that try to reconceptualize scientific publishing as gamification, with all the baggage gamification brings (mostly notably that it's not openly open to, but positively encourages treating it as a points-grabbing system to be gamed).
I don't have much trust in the supposedly "open" motives of this new batch of para-academic for-profit companies, either. Notice how academia.edu won't even let you download the PDFs of articles without registering for an account. I would guess the real purpose of these metrics is to set themselves up as new scientific gatekeepers in one form or another: to transition from a journal-oriented publication system to an "academic marketplace" oriented system where they own the marketplace. I have a lot more trust in the by-scientists, for-scientists model of JMLR.
> The taxpayer ends up paying twice for the same research: once to fund it and a second time to read it. The heart of the problem lies in the reputation system, which encourages scientists to put their work behind paywalls. The way out of this mess is to build new reputation metrics.
The heart of the problem simply lies in closed-access journals, and a simpler solution is to move to open-access journals, which is already happening. Reputation is not an insurmountable barrier to this. In my field (artificial intelligence) the top two journals are now open-access. No fancy new metrics or removal of the concept of journal needed; problem solved.
I view the solutions proposed here as a bit more problematic. Download counts in particular are likely to just reward linkbaity research, rather than quality research, and exacerbate the already problematic race to put out misleading hyped-up press releases. Citation counts are liable to gaming as well, and are commonly gamed by both citation rings, and by people who consciously choose the subjects they publish in an ADDish citation-maximizing way, jumping in and out of hot areas to drop off a paper that'll turn up in searches. When it comes to judging the quality of AI research, I have a lot more trust in the editorial process of the open-access journals like JMLR or JAIR than I do in gimmicky new metrics that try to reconceptualize scientific publishing as gamification, with all the baggage gamification brings (mostly notably that it's not openly open to, but positively encourages treating it as a points-grabbing system to be gamed).
I don't have much trust in the supposedly "open" motives of this new batch of para-academic for-profit companies, either. Notice how academia.edu won't even let you download the PDFs of articles without registering for an account. I would guess the real purpose of these metrics is to set themselves up as new scientific gatekeepers in one form or another: to transition from a journal-oriented publication system to an "academic marketplace" oriented system where they own the marketplace. I have a lot more trust in the by-scientists, for-scientists model of JMLR.
Open access journals, based on authors paying $1,000-$3,000 to publish a paper, are going to be a temporary stepping stone on the way to the decline of the journal.
We need new reputation metrics to encourage the sharing of data-sets, videos, code, and generally the full range of a scientist's output. 75% of the world's scientific data doesn't get shared because the rewards aren't there for the scientist to share it. Journals aren't going to start publishing data-sets (or code, or videos, or blog posts), and so we need new reputation metrics, and reward systems, to encourage scientists to share this kind of information.
The other problem with the journal system is that the peer review system is slow and surfaces the opinions of only two or three scientists about a given paper. If you have a community of 20,000 people in the DNA sequencing research community, asking two people what they think about a paper is not going to deliver a statistically significant result. Furthermore the typical time-lag for the system to surface those opinions is 12 months.
We need a more robust peer review system which surfaces opinions from the entire scientific community in real time. Reputation metrics are the key to building that system. We need to provide the rewards for scientists to share their comments on papers, so they can build their reputations off the insights they share on each other's papers.
We need new reputation metrics to encourage the sharing of data-sets, videos, code, and generally the full range of a scientist's output. 75% of the world's scientific data doesn't get shared because the rewards aren't there for the scientist to share it. Journals aren't going to start publishing data-sets (or code, or videos, or blog posts), and so we need new reputation metrics, and reward systems, to encourage scientists to share this kind of information.
The other problem with the journal system is that the peer review system is slow and surfaces the opinions of only two or three scientists about a given paper. If you have a community of 20,000 people in the DNA sequencing research community, asking two people what they think about a paper is not going to deliver a statistically significant result. Furthermore the typical time-lag for the system to surface those opinions is 12 months.
We need a more robust peer review system which surfaces opinions from the entire scientific community in real time. Reputation metrics are the key to building that system. We need to provide the rewards for scientists to share their comments on papers, so they can build their reputations off the insights they share on each other's papers.
Yes, I get that's the sales pitch, but you didn't address gamification at all, which is what you're promoting, and will positively harm science, not improve it.
In addition, peer-review at well-run open access journals, which are the model I think we should be moving towards, does not take anywhere near 12 months, and in CS there are no publication fees (I gather this differs in biology). I typically get very well-thought-out reviews which help to improve my papers in about 6-8 weeks, and if accepted, publication is completely free of charge. And, it's becoming increasingly common to circulate preprints ahead of submission, on places such as the arXiv or at conferences or workshops, to get the feedback of a larger proportion of the community before publishing the final version of the paper.
I agree peer review does not settle the correctness of a paper; it's a system for ensuring a high-quality discourse, not to publish only papers which are the last word on a subject. That's what reply papers, replication studies, etc. are for. I am skeptical that attaching a bunch of points and badges to the discourse is going to improve the quality of that discourse, and suspect it will harm it. I'd rather look at how to improve the discourse by improving the journals. But that won't make money for VCs, so I'm not surprised that we're only seeing it from nonprofit organizations like JAIR and PLoS.
In addition, peer-review at well-run open access journals, which are the model I think we should be moving towards, does not take anywhere near 12 months, and in CS there are no publication fees (I gather this differs in biology). I typically get very well-thought-out reviews which help to improve my papers in about 6-8 weeks, and if accepted, publication is completely free of charge. And, it's becoming increasingly common to circulate preprints ahead of submission, on places such as the arXiv or at conferences or workshops, to get the feedback of a larger proportion of the community before publishing the final version of the paper.
I agree peer review does not settle the correctness of a paper; it's a system for ensuring a high-quality discourse, not to publish only papers which are the last word on a subject. That's what reply papers, replication studies, etc. are for. I am skeptical that attaching a bunch of points and badges to the discourse is going to improve the quality of that discourse, and suspect it will harm it. I'd rather look at how to improve the discourse by improving the journals. But that won't make money for VCs, so I'm not surprised that we're only seeing it from nonprofit organizations like JAIR and PLoS.
With the time-lag, you have to take into account the rejection rate. Most articles don't get into their first choice journal, and perhaps get into their second or third choice. You can't parallel submit, meaning that the time-lag between finishing the paper, and it getting published in a journal, often ranges between 6 and 18 months.
I understand that Computer Science does have a slightly faster peer review process than other fields. Here is a piece where a leading neuroscientist writes "Today the lag [in my field] between submission and acceptance is often more than a year". http://www.pnas.org/content/early/2013/01/25/201300924.short...
Gamification is an important issue. You should note that the journal's peer review system, based on two people reading a paper, gets gamed. There is the wide-spread practice of defensive citation, where you defensively cite anyone who might conceivably peer review your paper, in order to maximize the chances of its getting accepted. Some people know how to play that game better than others.
One way of handling gamification is to look at the quality of the people interacting with a piece of content, and not just the quantity. This is how Google's PageRank algorithm deals with the issue.
There is also the approach, taken by Twitter and Facebook, of picking out the people's whose judgements you trust, and then letting them act as quality filters. Those systems can be gamed too, but aren't typically gamed to a large extent.
I understand that Computer Science does have a slightly faster peer review process than other fields. Here is a piece where a leading neuroscientist writes "Today the lag [in my field] between submission and acceptance is often more than a year". http://www.pnas.org/content/early/2013/01/25/201300924.short...
Gamification is an important issue. You should note that the journal's peer review system, based on two people reading a paper, gets gamed. There is the wide-spread practice of defensive citation, where you defensively cite anyone who might conceivably peer review your paper, in order to maximize the chances of its getting accepted. Some people know how to play that game better than others.
One way of handling gamification is to look at the quality of the people interacting with a piece of content, and not just the quantity. This is how Google's PageRank algorithm deals with the issue.
There is also the approach, taken by Twitter and Facebook, of picking out the people's whose judgements you trust, and then letting them act as quality filters. Those systems can be gamed too, but aren't typically gamed to a large extent.
"Defensive" citations are arguably consistent with good research practice in that they reference all relevant research by the most prominent names in the field; it's certainly no worse than the sort of open trading of citations a PageRank style algorithm theoretically encourages.
Sorry, I don't think Twitter and Facebook's quality filters "aren't typically gamed to a large extent" and I do think they're incomparably worse.
Sorry, I don't think Twitter and Facebook's quality filters "aren't typically gamed to a large extent" and I do think they're incomparably worse.
I think you are confusing gamification and gaming the system, those are not the same thing.
GP was referring to badges, points etc (gamification) and you are referring to gaming the system (ie citing defensively).
GP was referring to badges, points etc (gamification) and you are referring to gaming the system (ie citing defensively).
If so, then mjn needs to clearly distinguish between (bad) gamification and a (good) reputation system, which will necessarily involve something like points or certifications.
> Open access journals, based on authors paying $1,000-$3,000 to publish a paper, are going to be a temporary stepping stone on the way to the decline of the journal.
At least in my field, papers cost roughly $50k-$100k for just the researcher salary and overhead. Paying $2k to get a paper published is not a high hurdle (especially once the norm of closed-access publishing fades away). And this really seems like the minimum cost that needs to be incurred in order to get decent copyediting and the editorial cost of co-ordinating the referees. I love the ArXiv, but if I can get a the copyedited version from the journal I will.
Yes the referees aren't paid, which may or may not change, but paying a PhD editor $500 to figure out the best referees and engage in the back-and-forth with them and the authors is pretty minimal. So $2k for a professionally edited, polished paper which is then free to everyone forever seems like a pretty good deal, and essentially a non-issue.
Your point about the need for incentives for scientists to share non-paper scientific output like code is well-taken (and well-known). But I don't see why this can't be solved by open-access journals. I am completely unconvinced that facebook likes controlled by a for-profit organization are the way to go.
EDIT: By the way, you've mentioned in several places the 12-month time lag for publishing. This was solved for the physics community by the ArXiv; the papers get immediately released, and you can still submit to journals for the benefits of copyediting and refereeing. (Afterwards the ArXiv version is updated.) I don't know of any reason it can't work for all of academia.
At least in my field, papers cost roughly $50k-$100k for just the researcher salary and overhead. Paying $2k to get a paper published is not a high hurdle (especially once the norm of closed-access publishing fades away). And this really seems like the minimum cost that needs to be incurred in order to get decent copyediting and the editorial cost of co-ordinating the referees. I love the ArXiv, but if I can get a the copyedited version from the journal I will.
Yes the referees aren't paid, which may or may not change, but paying a PhD editor $500 to figure out the best referees and engage in the back-and-forth with them and the authors is pretty minimal. So $2k for a professionally edited, polished paper which is then free to everyone forever seems like a pretty good deal, and essentially a non-issue.
Your point about the need for incentives for scientists to share non-paper scientific output like code is well-taken (and well-known). But I don't see why this can't be solved by open-access journals. I am completely unconvinced that facebook likes controlled by a for-profit organization are the way to go.
EDIT: By the way, you've mentioned in several places the 12-month time lag for publishing. This was solved for the physics community by the ArXiv; the papers get immediately released, and you can still submit to journals for the benefits of copyediting and refereeing. (Afterwards the ArXiv version is updated.) I don't know of any reason it can't work for all of academia.
You're right that the cost isn't the main issue. It shouldn't be disregarded though: with 2 million articles published a year, a $2,000 cost per article means $4 billion a year that could be spent on more research. To put that in context, the NIH's budget for tackling cancer is $4.9 billion a year.
The main issues with the journal system are the effects it has on the speed and quality of scientific communication. Peer review by two people is not robust, and it is very slow; secondly, the full range of scientific media aren't shared.
These are the problems that, I believe, require an overhaul of the reputation system in science. The only way to incentivize scientists to share their comments on papers quickly, and at scale, is to provide rewards for them to do that.
The range of media that scientists will start to share will be shared on platforms designed for that media type. Code will be shared on Github. Videos will be shared on YouTube. Data-sets will be shared on sites like Figshare or other sites dedicated to handling that content format well.
The main issues with the journal system are the effects it has on the speed and quality of scientific communication. Peer review by two people is not robust, and it is very slow; secondly, the full range of scientific media aren't shared.
These are the problems that, I believe, require an overhaul of the reputation system in science. The only way to incentivize scientists to share their comments on papers quickly, and at scale, is to provide rewards for them to do that.
The range of media that scientists will start to share will be shared on platforms designed for that media type. Code will be shared on Github. Videos will be shared on YouTube. Data-sets will be shared on sites like Figshare or other sites dedicated to handling that content format well.
The article mentions Stack Overflow reputation. I've always seen it as an extremely bad measure of reputation. In practice, it only measures a few things, none of which are very relevant:
- The length of time somebody has been using SO.
- That person's ability (which usually amounts to just having lots of free time) to repeatedly answer the very basic jQuery or .NET questions that are asked time and time again by new users.
- The number of other people who will blindly upvote an answer after merely seeing a picture of, say, Jon Skeet's face.
None of those are indicative of true knowledge, experience, or natural talent. They're more a measure of popularity than they are of reputation.
- The length of time somebody has been using SO.
- That person's ability (which usually amounts to just having lots of free time) to repeatedly answer the very basic jQuery or .NET questions that are asked time and time again by new users.
- The number of other people who will blindly upvote an answer after merely seeing a picture of, say, Jon Skeet's face.
None of those are indicative of true knowledge, experience, or natural talent. They're more a measure of popularity than they are of reputation.
Service is widely considered a key measure of excellence for academics, along with research and teaching.
I value my SO rep because it accords approximately with how much (whether in quality or quantity) I have served the site's readership. The site is robustly healthy. I think its success is evidence that SO rep is an effective incentive for SO participants.
I agree that unless we examine the specific activities, SO rep validates only a minimal degree of technical ability. I just never thought that was its primary function.
I value my SO rep because it accords approximately with how much (whether in quality or quantity) I have served the site's readership. The site is robustly healthy. I think its success is evidence that SO rep is an effective incentive for SO participants.
I agree that unless we examine the specific activities, SO rep validates only a minimal degree of technical ability. I just never thought that was its primary function.
The business models that will emerge in science will be as diverse as the ones on the web at large. There will be advertising businesses; freemium models; and enterprise sales models.
I'm not sure who the author thinks the customers for these services will be. Perhaps universities will pay for access but I guarantee you faculty and students will not. I also can't imagine advertisers paying much to target academics, a small and not particularly unique demographic. In short, I just don't see how these sites hope to generate any revenue. Academia is an incredibly difficult market to get money out of and even if you're going to sell at the university level you're talking about a massive sales effort that is going to take years to yield results (think Blackboard). As other have said here journals are going to end up being open-access and free. Many of them will probably end being run by well endowed university presses (e.g. MIT press).
I'm not sure who the author thinks the customers for these services will be. Perhaps universities will pay for access but I guarantee you faculty and students will not. I also can't imagine advertisers paying much to target academics, a small and not particularly unique demographic. In short, I just don't see how these sites hope to generate any revenue. Academia is an incredibly difficult market to get money out of and even if you're going to sell at the university level you're talking about a massive sales effort that is going to take years to yield results (think Blackboard). As other have said here journals are going to end up being open-access and free. Many of them will probably end being run by well endowed university presses (e.g. MIT press).
> I just don't see how these sites hope to generate any revenue.
Good point. The academic publishing "sector" is definitely a very interesting domain and there is a lot of POWER in knowledge, but it is not clear what the role of a startup company would be in there. We could bring cool new technology but without wide adoption tech is useless.
Mr. Price is trying the generic (and by now annoying as hell) "social network for science" approach but it is not clear that having "likes" for papers inside the academia.edu walled garden do anything for science. What is cool is the tremendous opportunity for better scientific discovery applications and the organization of knowledge. Hopefully at some point Mr. Price will //do// something interesting on that front instead of spending his time in PR mode writing guest posts for tech news sites.
@Richard: Sorry bro, but the "sign up to see the PDF" really pissed me off the other day so you are in the bad books until you change that. Not cool.
My guess is that the future of dissemination looks a lot like the arXiv (self-service, cheap) and that a peer review system can be bolted on top of it. Prof. Gowers was recently mentioned he heard of an initiative to build "arXiv overlay journals" [1].
[1] http://gowers.wordpress.com/2013/01/16/why-ive-also-joined-t...
Good point. The academic publishing "sector" is definitely a very interesting domain and there is a lot of POWER in knowledge, but it is not clear what the role of a startup company would be in there. We could bring cool new technology but without wide adoption tech is useless.
Mr. Price is trying the generic (and by now annoying as hell) "social network for science" approach but it is not clear that having "likes" for papers inside the academia.edu walled garden do anything for science. What is cool is the tremendous opportunity for better scientific discovery applications and the organization of knowledge. Hopefully at some point Mr. Price will //do// something interesting on that front instead of spending his time in PR mode writing guest posts for tech news sites.
@Richard: Sorry bro, but the "sign up to see the PDF" really pissed me off the other day so you are in the bad books until you change that. Not cool.
My guess is that the future of dissemination looks a lot like the arXiv (self-service, cheap) and that a peer review system can be bolted on top of it. Prof. Gowers was recently mentioned he heard of an initiative to build "arXiv overlay journals" [1].
[1] http://gowers.wordpress.com/2013/01/16/why-ive-also-joined-t...
The scientific publication business modell is a work of "genius". In a nutshell
- Outsource content production, get content for free
- Outsource the review process, get quality assurance for free
- Slap brand name on it and charge (many customers being opted in on autopay plans)
I'm looking forward to one of the disruptors succeeding. I think that it is reasonable to demand that any tax funded research should be openly available for society to benefit
- Outsource content production, get content for free
- Outsource the review process, get quality assurance for free
- Slap brand name on it and charge (many customers being opted in on autopay plans)
I'm looking forward to one of the disruptors succeeding. I think that it is reasonable to demand that any tax funded research should be openly available for society to benefit
I see the article kindly submitted here is a guest post by Richard Price, founder and CEO of the Academia.edu website. I have signed up for Academia.edu (and the confusingly similar site ResearchGate, run by a different group of founders), but so far haven't seen a lot of activity on these new sites.
That point is well taken that there needs to be reform in how scientists develop their reputation as researchers. Right now, reviewing submissions to scientific journals is anonymous, and not well rewarded. Jelte Wicherts, writing in Frontiers of Computational Neuroscience (an open-access journal),
Jelte M. Wicherts, Rogier A. Kievit, Marjan Bakker and Denny Borsboom. Letting the daylight in: reviewing the reviewers and other ways to maximize transparency in science. Front. Comput. Neurosci., 03 April 2012 doi: 10.3389/fncom.2012.00020
http://www.frontiersin.org/Computational_Neuroscience/10.338...
suggests new procedures for making the peer-review process in scientific publishing more rewarding and more reliable too. Wicherts does a lot of research on this issue to try to reduce the number of dubious publications in his main discipline, the psychology of human intelligence.
"With the emergence of online publishing, opportunities to maximize transparency of scientific research have grown considerably. However, these possibilities are still only marginally used. We argue for the implementation of (1) peer-reviewed peer review, (2) transparent editorial hierarchies, and (3) online data publication. First, peer-reviewed peer review entails a community-wide review system in which reviews are published online and rated by peers. This ensures accountability of reviewers, thereby increasing academic quality of reviews. Second, reviewers who write many highly regarded reviews may move to higher editorial positions. Third, online publication of data ensures the possibility of independent verification of inferential claims in published papers. This counters statistical errors and overly positive reporting of statistical results. We illustrate the benefits of these strategies by discussing an example in which the classical publication system has gone awry, namely controversial IQ research. We argue that this case would have likely been avoided using more transparent publication practices. We argue that the proposed system leads to better reviews, meritocratic editorial hierarchies, and a higher degree of replicability of statistical analyses."
That point is well taken that there needs to be reform in how scientists develop their reputation as researchers. Right now, reviewing submissions to scientific journals is anonymous, and not well rewarded. Jelte Wicherts, writing in Frontiers of Computational Neuroscience (an open-access journal),
Jelte M. Wicherts, Rogier A. Kievit, Marjan Bakker and Denny Borsboom. Letting the daylight in: reviewing the reviewers and other ways to maximize transparency in science. Front. Comput. Neurosci., 03 April 2012 doi: 10.3389/fncom.2012.00020
http://www.frontiersin.org/Computational_Neuroscience/10.338...
suggests new procedures for making the peer-review process in scientific publishing more rewarding and more reliable too. Wicherts does a lot of research on this issue to try to reduce the number of dubious publications in his main discipline, the psychology of human intelligence.
"With the emergence of online publishing, opportunities to maximize transparency of scientific research have grown considerably. However, these possibilities are still only marginally used. We argue for the implementation of (1) peer-reviewed peer review, (2) transparent editorial hierarchies, and (3) online data publication. First, peer-reviewed peer review entails a community-wide review system in which reviews are published online and rated by peers. This ensures accountability of reviewers, thereby increasing academic quality of reviews. Second, reviewers who write many highly regarded reviews may move to higher editorial positions. Third, online publication of data ensures the possibility of independent verification of inferential claims in published papers. This counters statistical errors and overly positive reporting of statistical results. We illustrate the benefits of these strategies by discussing an example in which the classical publication system has gone awry, namely controversial IQ research. We argue that this case would have likely been avoided using more transparent publication practices. We argue that the proposed system leads to better reviews, meritocratic editorial hierarchies, and a higher degree of replicability of statistical analyses."
There are a number of aspects of publishing and perhaps reputation academics would like to reboot. We are frustrated with e.g. Elsevier, and there is a big boycott on. Presumably this boycott, and the reasons for it, will extend to Mendeley after it becomes part of Elsevier. Given that all these startups are probably heading for similar exists (if successful), this is just more of the same. When we reboot publishing, it will be in a way we control, not with Elsevier 2.0.
"A few years ago, Google Scholar started displaying inbound citation counts for papers... . Scientists have started to see these inbound citation counts as a way to demonstrate the impact of their work..."
Let's note that article citation counts have been commonly available at research libraries for about fifty years in the Science Citation Index. (Disclaimer/disclosure: I do not speak for the business that produces the Science Citation Index. That business is my current employer.)
Let's note that article citation counts have been commonly available at research libraries for about fifty years in the Science Citation Index. (Disclaimer/disclosure: I do not speak for the business that produces the Science Citation Index. That business is my current employer.)
Yes, that's true. But authors only started including their inbound citation counts on their job applications in the last few years.
I think the main reason for this is that Google Scholar's citation metrics were free and openly accessible, and the Science Citation Index was, and still is, behind expensive paywalls. Scientists were happier to include citation metrics in their resumes when they knew that the committee could easily check them, and wouldn't have to pay to get access to them.
I think the main reason for this is that Google Scholar's citation metrics were free and openly accessible, and the Science Citation Index was, and still is, behind expensive paywalls. Scientists were happier to include citation metrics in their resumes when they knew that the committee could easily check them, and wouldn't have to pay to get access to them.
Supporting your point, astrophysicists have been using citation counts in this way for quite a few years thanks to the citation data provided by the NASA Astrophysical Data System.
Citation counts are biased, but at present they are the best we have. Their main attraction is that they are transparent and hence trustworthy, and a proxy for what we really care about: aggregate expert judgement of importance. Any replacement will have improve one or both dimensions--I don't think timeliness alone is enough.
Citation counts are biased, but at present they are the best we have. Their main attraction is that they are transparent and hence trustworthy, and a proxy for what we really care about: aggregate expert judgement of importance. Any replacement will have improve one or both dimensions--I don't think timeliness alone is enough.
i disagree with the author of this piece about a major premise underlying his thesis: that journals ultimately have no real contribution to the author or community that can't be done away with.
top tier journals are top tier journals not because of marketing but because of their standards. their standards are high because they enforce rigorous quality control (reviews) and solicit the best, most groundbreaking work in the field. they bring on the best editorial staff and set directions, not following it.
arxiv, for example, is not the same as PNAS. anyone can put anything in arxiv, there is no quality control, no editorial board, no selection process.
i think that if you tried to demolish that, you'd wind up with a replacement, not a whole new model.
to outsiders this all seems capricious, fickle, arbitrary and anachronistic. instead, it's important because science - the forward progression of human knowledge and understanding - relies on ensuring that valid, repeatable results get publish, not falsehoods (e.g. "vaccines cause autism" and such tripe) or outright plagiarisms. journals work because they provide this. top tier journals are recognized as such because they publish the best quality work which attracts more top quality work. w
top tier journals are top tier journals not because of marketing but because of their standards. their standards are high because they enforce rigorous quality control (reviews) and solicit the best, most groundbreaking work in the field. they bring on the best editorial staff and set directions, not following it.
arxiv, for example, is not the same as PNAS. anyone can put anything in arxiv, there is no quality control, no editorial board, no selection process.
i think that if you tried to demolish that, you'd wind up with a replacement, not a whole new model.
to outsiders this all seems capricious, fickle, arbitrary and anachronistic. instead, it's important because science - the forward progression of human knowledge and understanding - relies on ensuring that valid, repeatable results get publish, not falsehoods (e.g. "vaccines cause autism" and such tripe) or outright plagiarisms. journals work because they provide this. top tier journals are recognized as such because they publish the best quality work which attracts more top quality work. w
That's the whole reason for adding a reputation system, which is what replaces quality control and selection.
There's one other function of journals that few people seem to be bringing up or addressing: that of filtering the flood of research. Hundreds of papers per week are published a week in "biology" across dozens of journals, but in most weeks, 0-1 of those will be interesting to me. By scanning the titles in Science, Nature, and Cell, I'm much likelier to find the really cool stuff than if I were just given a list of all papers with a given tag.
I'm not saying that this recommendation is an intrinsically hard problem, just that it doesn't seem to be getting as much play as the other aspects of the open science revolution.
I'm not saying that this recommendation is an intrinsically hard problem, just that it doesn't seem to be getting as much play as the other aspects of the open science revolution.
Richard's proposition is basically that metrics should be created and used because its always better to have more data. This is only true if the data is good. The biggest problem I can see is that metrics are easy to fake. That's fine on sites StackOverflow where the stakes are very low but when metrics are accorded extremely high value, as is being proposed here, you immediately create a huge incentive to pollute the data.
The only way out of this is to create some kind of quality assurance of the metrics themselves. To me that seems like a monster problem that no startup can possibly handle.
If they restrict their scope a bit more than trying to liberate all of academia from the publishers there are probably ways to add value.
The only way out of this is to create some kind of quality assurance of the metrics themselves. To me that seems like a monster problem that no startup can possibly handle.
If they restrict their scope a bit more than trying to liberate all of academia from the publishers there are probably ways to add value.
> and the primary reputation metric in science is being published in prestigious journals, such as Nature, Science, and The Lancet.
Absolutely not. The primary metric is citations.
Where do people get these ideas?
Absolutely not. The primary metric is citations.
Where do people get these ideas?
Speaking of metrics, using a very rough one (ye olde Google Book Ngrams), we can guess that citation-counting became prominent in the late 1970s: http://books.google.com/ngrams/graph?content=citation+count%...
I remember tenure committees would have "vertical inches" measured from the Science Citation Index.
In the world of big data, not all citations are created equal, and I look forward to new metrics based on quality of citations.
In the world of big data, not all citations are created equal, and I look forward to new metrics based on quality of citations.
I've long wanted some kind of citation-sorting for research, though I'm more skeptical of the whole business for assessment. For research, I think it could improve discoverability and ability to trace chains of influence. If I find a paper that was cited 190 times and I want to see whether anyone's really followed up on it (critiqued it, extended it, revised it, refuted it, etc.), the reverse-citation list is too noisy. It'd be great if I could filter the citations, for example to exclude "related work exists [2,5,12,44]" type throwaway citations.
From my time working with academic researchers it was clear that they absolutely coveted publication in the above journals as they are so widely read - unlike the niche journals in their fields. To paraphrase one of them "They're crap, but everyone reads them and everyone cites them"
That's true, but then a focus on more metrics like citation counts and download counts seems like it'll just increase the strength of those journals, not undermine it. People will try to publish in Nature or Science to get attention for their paper, because those journals are widely read, and have good connections with journalists who'll further publicize your paper, making it easier to improve your metrics.
For young researchers--say, within 5 years of your PhD--you haven't had time for citations to accumulate, and journal name really is the important thing. And even for older researchers, they go after big-name journals because of the citations generated.
> For young researchers--say, within 5 years of your PhD--you haven't had time for citations to accumulate, and journal name really is the important thing.
Maybe for people who don't know better.
For example: 5 years out is when a "real" tenure review takes place. (Tenure occurs at 7 years: Thumbs up or down usually occurs at 6 years, you get most of the readout at 5.) Mere publication may suffice at non-research institutions, which are primarily centers-for-profiting-off-education, but at any place where research is worth a damn, they have already measured impact. One of those measures is citations.
The same was essentially true at places like Bell Labs, but the process was not as formal.
Edit: I see from your profile that you are at TJ Watson? Last I knew, they definitely paid attention to citations for 5 year reviews, much like Bell. I find it hard to believe that they've watered down.
Maybe for people who don't know better.
For example: 5 years out is when a "real" tenure review takes place. (Tenure occurs at 7 years: Thumbs up or down usually occurs at 6 years, you get most of the readout at 5.) Mere publication may suffice at non-research institutions, which are primarily centers-for-profiting-off-education, but at any place where research is worth a damn, they have already measured impact. One of those measures is citations.
The same was essentially true at places like Bell Labs, but the process was not as formal.
Edit: I see from your profile that you are at TJ Watson? Last I knew, they definitely paid attention to citations for 5 year reviews, much like Bell. I find it hard to believe that they've watered down.
Maybe we're talking about different fields, or maybe you misunderstood when I said "say, within 5 years of your PhD"? By this I mean that 5 years is the rough time when citations become useful. Before that, when you're on your first or second post-doc, there just hasn't been enough time for a meaningful number to accumulate. Would you agree with my statement if I had said 3 or 4 years?
EDIT: Let me put it this way: suppose you're 4.5 years out of your PhD and you're applying for a tenure-track assistant professor position after two post-docs. Your competitor has 30% more citations than you, but in average journals, and last year you published in Nature; that article hasn't had time to rack up cites (which it will). Without knowing anything else about situation, who do you think is more likely to get the position?
EDIT: Let me put it this way: suppose you're 4.5 years out of your PhD and you're applying for a tenure-track assistant professor position after two post-docs. Your competitor has 30% more citations than you, but in average journals, and last year you published in Nature; that article hasn't had time to rack up cites (which it will). Without knowing anything else about situation, who do you think is more likely to get the position?
> or maybe you misunderstood when I said "say, within 5 years of your PhD"?
It sounds more like I misunderstood when you wrote "you haven't had time for citations to accumulate, and journal name really is the important thing." Your example above combines journal citations with place-of-publication, which makes more sense than one important item.
And lets face it, there have been some real whoppers in Nature. Jan Hendrik Schön comes to mind. So to your example: I can think of only a single situation in which a last-year-item of any quality affected a decision. The likely answer to your question is that neither of the candidates would be hired, at least at the best institutions.
It sounds more like I misunderstood when you wrote "you haven't had time for citations to accumulate, and journal name really is the important thing." Your example above combines journal citations with place-of-publication, which makes more sense than one important item.
And lets face it, there have been some real whoppers in Nature. Jan Hendrik Schön comes to mind. So to your example: I can think of only a single situation in which a last-year-item of any quality affected a decision. The likely answer to your question is that neither of the candidates would be hired, at least at the best institutions.
I agree that my statement was muddied. Thanks for your thoughts.
> The primary metric is citations.
What field are you in? This is absolutely wrong for tenure decisions in economics. It is pretty wrong for promotion from associate to full professor.
What field are you in? This is absolutely wrong for tenure decisions in economics. It is pretty wrong for promotion from associate to full professor.
Richard, do you have any plans of making tools for making writing scientific articles easier? Right now, the tools and output are too rooted in the old ways of deadtree publishing - after all, articles are still called "papers". The whole format is based on printing.
Since you're trying to get scientists to publish new types of media, don't you think you need to provide software that makes creating such media easier?
You can't move from books to blogs to tweets, if all you have is a typewriter.
Since you're trying to get scientists to publish new types of media, don't you think you need to provide software that makes creating such media easier?
You can't move from books to blogs to tweets, if all you have is a typewriter.
A more straightforward solution would be to pass this bill [1], which would require that tax-payer funded research be made publicly available. Once this becomes mandatory the publication/reputation system will be forced to adjust accordingly (and many journals may not survive the transition).
[1] http://www.govtrack.us/congress/bills/112/hr4004
[1] http://www.govtrack.us/congress/bills/112/hr4004
"Disrupt[ing] the scientific journal industry" is a massively ambitious goal. Good luck! I'd really like to know more about startups that are trying a less ambitious first step; something like "wordpress for marine biologists who want to start an open-access journal" or "reddit for geneticists." The issues in different disciplines seem different enough that intimate domain knowledge is almost mandatory and something that starts with the idea "I want to talk to these people about this subject in this way" could work out better than "kill the journals." Since it's fun to quote PG:
> The way to get startup ideas is not to try to think of startup ideas. It's to look for problems, preferably problems you have yourself. [1]
I guess, "I want to read other people's research for free" counts as a problem, but I'd actually be surprised if it were literally a problem that the founders of this startup (and the others mentioned in the article) were facing.
I mention this in a comment below [2], but Economics is extremely open by a lot of standards (maybe because of the policy-relevance of a lot of the research, but that's speculation on my part). There is a large blogging community that includes very accomplished researchers, most working papers are available online well before publication (and will typically reflect at least one round of referee comments), there are comprehensive citation-based rankings, etc. Anyone interested in this stuff should check out http://repec.org; the html is dated, but it seems like an established unwalled-garden version of what this article, and others, describe (one that uses email and rss feeds rather than direct-messages and social-network-type friends; decide for yourself which you prefer).
Economists still publish any important research in peer-reviewed publications, and most of them are closed-access. So I find it unlikely that just the right infrastructure and "metrics" are going to kill peer-reviewed publication. I think it's possible that some set of tools could kill the crappy scientific journals in one or two fields and certainly could kill all of the crappy closed-access journals in those fields, and then iterations and incremental improvements could lead to something that worked across fields and worked for higher-quality publications.
[1] http://paulgraham.com/startupideas.html [2] https://news.ycombinator.com/item?id=5160633
> The way to get startup ideas is not to try to think of startup ideas. It's to look for problems, preferably problems you have yourself. [1]
I guess, "I want to read other people's research for free" counts as a problem, but I'd actually be surprised if it were literally a problem that the founders of this startup (and the others mentioned in the article) were facing.
I mention this in a comment below [2], but Economics is extremely open by a lot of standards (maybe because of the policy-relevance of a lot of the research, but that's speculation on my part). There is a large blogging community that includes very accomplished researchers, most working papers are available online well before publication (and will typically reflect at least one round of referee comments), there are comprehensive citation-based rankings, etc. Anyone interested in this stuff should check out http://repec.org; the html is dated, but it seems like an established unwalled-garden version of what this article, and others, describe (one that uses email and rss feeds rather than direct-messages and social-network-type friends; decide for yourself which you prefer).
Economists still publish any important research in peer-reviewed publications, and most of them are closed-access. So I find it unlikely that just the right infrastructure and "metrics" are going to kill peer-reviewed publication. I think it's possible that some set of tools could kill the crappy scientific journals in one or two fields and certainly could kill all of the crappy closed-access journals in those fields, and then iterations and incremental improvements could lead to something that worked across fields and worked for higher-quality publications.
[1] http://paulgraham.com/startupideas.html [2] https://news.ycombinator.com/item?id=5160633
Seems like Pagerank would be an ideal reputation metric, following citations in papers instead of links in web pages. Except it's patented until 2018 or so.
Pagerank is a citation based ranking system, it existed in the academic world long before it was applied to the web.
That patent should not apply to anything, but it certainly doesn't apply to citation ranking of academic papers.
That patent should not apply to anything, but it certainly doesn't apply to citation ranking of academic papers.
Do you mean the general idea of citation ranking, or the specific math used by Pagerank?
This seems absurdly farfetched for me. It is easy and common for mathematicians to share their work (e.g. on the arXiv) and I consider myself fortunate to get two or three good comments, let alone hundreds. (Of course, this is a claim made by TC, not by academia.edu.) Whatever the virtues of academia.edu or any other technological solution, I do not expect it to multiply the audience for my work by an order of magnitude.
By way of comparison, check out Terry Tao's math blog. His reputation, his expositional ability, and the size and enthusiasm of his audience are surpassed by no one. And of course, the blog (and the ability to comment) are freely available to everyone with a web browser.
http://terrytao.wordpress.com/
Look at the comment counts. For many posts, in the single digits. And this low, even though Tao personally responds to many of the comments and questions.
I suggest that this is likely to be an upper bound for responses to math writing posted anywhere, in any format, with or without restrictions on how can read, write, or respond to what's posted.
I don't think peer review is broken, at least not in math. It can be annoying to do (which is why it takes so long), but we regard it as an obligation and that's why we do it.
The issue, in my mind, is to separate peer review from "publishing", or more to the point, from dissemination. The reason this problem is so thorny and obnoxious (again, in my mind) is that in principle it is trivial.