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The title seems to intentionally misrepresent the retraction to push an agenda (or the author has some issues with basic logic) The retraction is that the stro

The title seems to intentionally misrepresent the retraction to push an agenda (or the author has some issues with basic logic) The retraction is that the strong/definitive proof that "the camel has two humps" was fabricated/exaggerated. The converse - that it has one hump hasn't been proven. From the quote, Richard Bornat doesn't say that they re-crunched the numbers and now there is proof of one hump. The camel has gone back to having an unknown number of humps

_pmf_ 10y ago
> The camel has gone back to having an unknown number of humps Some sources even go as far as saying there is no camel involved at all, and might have never been.
braythwayt 10y ago
In the absence of that paper, we had plenty of reasonable hypotheses about the ability to program. Like “Put 10,000 hours into it, and you’ll master it.” Or “It follows a distribution similar to other skills involving mathematics.” The paper presented an unusual hypotheses, that there was this sharp distinction between those who can program and those who never will, and that this distinction was somewhat orthogonal to other measures of scholarship. So for example, one might be a good architect but never get good at programming no matter how much one tried. You’re right we haven’t disproven this hypothesis, but given its novelty, the burden of proof is on "the camel has two humps." With the paper retracted, we do not presume it has an unknown number of humps, we presume that skill writing programs is going to be similar to other skills we observe. As this article observes, unusual outcomes in attempting to teach programming may just as easily be explained by the fact that in a young field, we may not know how to teach programming. If we’re going to chase ‘humps,’ perhaps we should look for unusual distributions in the skill of teaching programming. We may be terrible at it, and perhaps the skill we are really observing is the skill of learning to program in spite of didactic and structural obstacles.
- jkot 10y ago
  Paper is here: http://wiki.t-o-f.info/uploads/EDM4600/The%20camel%20has%20two%20humps.pdf http://wiki.t-o-f.info/uploads/EDM4600/The%20camel%20has%20t...
  - Smaug123 10y ago
    "In the absence of the paper" meant "now that the paper has been retracted" rather than "I couldn't find the paper".
- venomsnake 10y ago
  In my class there were people that groked recursion in half an hour, and the other needed a week. And not a big gap in between. It is anecdotal evidence, but there are people with innate ability. Also - natural distribution makes the one hump camel the default hypothesis.
  - braythwayt 10y ago
    A one-hump camel is a fine hypothesis. But multiple humps, implying “muggles and wizards,” is not.
  - jrochkind1 10y ago
    Or perhaps the people who understood recursion in a week had been writing code since they were 12, and those that didn't were new to it. Or something else we haven't thought of, that is still not innate aptitude. Or the people who understood recursion easily will not be the same people who understand, say, continuations easily. Still, I'd assume that with programming like I assume for most skills (music, athletics, lawyering, foreign language, whatever), some people start out with more aptitude than others, and find it easier than the others. I wouldn't assume it's a markedly more pronounced or separated distribution in CS/programming than for other things though. (Also, I have actually been programming since I was 12, and additionally believe I do have some aptitude for it that makes it easier for me than for some others, I'm pretty good at it -- and I still remember how hard it was for me to understand pointers in Pascal when I first learned them, which seem so straightforward to me now I have no idea why it was challenging at first! And I'm glad I had good teachers in formal coursework.)
    - spdionis 10y ago
      I didn't understand what all the fuss about recursion was about for it to require more words than "a function that calls itself". Sounded trivial to me. Later I understood that a number of implementation details make the technique a bit special. The concept itself still sounds trivial to me though.
      - jrochkind1 10y ago
- throwaway856 10y ago
  Meanwhile, it's taken for granted that not everyone can be a doctor, dentist, or lawyer. You don't see doctors telling people that anyone can "learn to med," but programmers see nothing wrong with devaluing their profession in the eyes of the masses by telling them that anyone can learn to do what they do, or worse, that it's easy, and that we shouldn't assume anything else until its proven otherwise. Programmers are far too egalitarian for our own good and our increasing marginalization and stagnant wages are the inevitable consequences.
  - contravariant 10y ago
    I think saying 'everyone can program' is not the same as 'everyone can be a programmer'. Similar to how saying 'everyone can (learn to) take care of their teeth' is not the same as 'everyone can be a dentist'.
  - JoBrad 10y ago
    Anyone can learn when they have a cold, and what to do about it. In the same way, anyone can learn to write a simple program. Not everyone has the dedication and skill to become a great MD, and the same applies to being a programmer.
    - geebee 10y ago
      I agree. The confounding factor (I'm stating the obvious, I know) here is that it's hard to determine what makes a "programmer", whereas there is a very clear set of criteria for what makes a lawyer or doctor. Although it's always tough to compare fields, I do think that some ways of measuring the skill set and educational requirements for a software developer do place it in one of the most rigorous fields out there. Majoring in computer science at a reputable university (I don't mean an elite one, I just mean one that requires the standard curriculum) typically requires two years science and engineering track calculus (not the easier one year, slower paced track available to econ or bio majors at some universities). Physics is often a requirement, as is an additional year of upper division mathematics (differential equations, calculus based probability), along with some classes that intersect with mathematics had have a heavy computing component, such as numerical analysis which generally involves computational methods to solve mathematical problems that aren't amenable to closed form solutions, or mathematical algorithms that require so many iterations that they aren't practical to solve by hand, optimization, graph theory. Then you add in compilers, operating systems, and other demanding electives. And keep in mind, CS or other Math/Physics/Eng students typically must take a far more substantial general curriculum in humanities than humanities students must take in quantitive fields. We don't get out of writing papers the way they get out of difficult math. People often point out that a field like law requires a three year grad degree, but honestly, in many ways, I think is is like comparing people who run at a 8 minute mile pace for 70 minutes vs people who run at a 6 minute mile pace for 40 minutes. You can't just compare the time spent, you have to compare the rigor of that time. Attrition rates for computer science are typically high even in elite schools, including at the graduate level (elite law schools, by contrast, often have attrition rates below one half of one percent, and many of the students come from fields like history or poly sci - nothing wrong with those fields, they are interesting, but they really don't have anywhere near the same attrition rates as CS or related majors). And if you do get a grad degree, then I'd say you've honestly gone through something much more difficult if you did it in Math/CS/Eng/PhysicalScience. Of course, you don't have to strictly major in CS or a related field to be a programmer, but consider what it takes to get through the google interviews. Try out some of the medium to difficult questions from "cracking the coding interview", and think about the poise, communication skill, analytical ability, and coding ability it takes to do a good job on these question sin 45 minutes at a white board (as an unsuccessful google interviewee myself, I assure you you are expected to make substantial progress on these problems, and medium to difficult is surely fair game!) You could get to this through self-study or formal education, but either way, it most definitely is not a low barrier to entry. Ok, not everyone works at google, and many of us work on crud apps. However, I have yet to see the mythical "simple crud app" that people refer to when they talk about how most programmers don't have hard jobs. These apps usually don't have deep algorithmic complexity, but they are hard to work with. You often inherit a difficult and poorly documented code base that you need to follow through, logically, with a fine toothed comb. You often have to get up to speed with a new framework, or an older one that uses deprecated methods during an era of substantial churn. You need to tease out often elaborate business logic and calculation pipelines from analysts or other non-technical workers that they have trouble communicating to you. And you often have to do this under intense pressure to provide estimates and meet deadlines, often from people who work in much more predictable fields and see your hesitance to commit as a sign of unreliability or a lack of professionalism. These, in my experience, are the "easy" crud projects. Honestly, I think researching and applying a novel machine learning algorithm to a data set can be a lot easier in many ways. That turned into a rant, but in short: this is a really hard job (and JoBrad, I hope it's clear to you that none of this is in disagreement to what you wrote, more riffing on the theme here…). Programming it isn't easy at all. I do think the reason that there is an alleged "shortage" is largely due to the fact that people who can handle this kind of work (it requires a huge about of logical reasoning, quantitative reasoning, consulting and working with vague requirements and end users, and presentation skills under pressure) have a lot of options out there. The market is actually working, pay and working conditions need to improve quite a bit to draw people away form those other things they're doing and into programming in the numbers silicon valley employers would like to see. And it won't happen overnight, ramp up time takes a while, this will be (if it happens) a pretty painful transition that will force the tech industry to dig pretty deep.
- red_admiral 10y ago
  In the absence of that paper, the only related thing I'm familiar with that claims a basis in evidence is Spolsky's [Hitting The High Notes][1]. The hypothesis there was that time spent on assignments and grade obtained are two essentially independent variables. [1] http://www.joelonsoftware.com/articles/HighNotes.html http://www.joelonsoftware.com/articles/HighNotes.html
venomsnake 10y ago
Politics. Science is always better accepted when it conforms or is spun to conform to the current zeitgeist. So it with bad science, no science and pull out of someone's ass (pseudo) science. And right now the zeitgeist in tech is to increase diversity.
- douche 10y ago
  Shh, you can't possibly suggest that different people might have the slightest difference of innate aptitudes! That's super-extra-double-badthink! You don't want to be the subject of the next Two Minutes Hate?
- SolaceQuantum 10y ago
  By this rhetorical implication, you're saying that not only are current demographics in tech (majority male, white, upper middle class) that way because those demographics are more skilled than other demographics, but also that any studies implying as such as stomped out by political pseudoscience proposing less effective diversity measures. And of course, I can't ask you for a source that studies are getting stomped out by political pseudoscience, because those sources will also have been stomped out. So I should instead ask you: how did you get this impression?
  - 8127612981 10y ago
    Just look at the differences inside your purportedly "privileged" "white male" group if you aren't capable of suppressing your ideologies otherwise. In fact, all studies should do so to avoid endless blathering on the Internet.
    - SolaceQuantum 10y ago
      I do apologize. I didn't imply any privilege here and apologize if I came off as trying to treat this is a privilege perspective. My confusion comes from the rhetorical implication that current demographics in computer science are that way because those demographics are somehow just better at it than others, and also that any proof of this us stomped out by political pseudoscience. I'm asking where gp gets this impression. I'm also curious what you mean by 'all studies should do so'. Do what, exactly? Analyze the demographic of white heterosexual upper middle class differently? I'm sure that might be interesting, but it's already a very specific demographic that fits class, sexuality, race, and gender identity. What other categories are being neglected that are skewing the view of demographic majorities in the technology industry?
scotty79 10y ago
> The camel has gone back to having an unknown number of humps Camel has gone back to be assumed to be typical gaussian camel as for many camels we don't know much about.
MustardTiger 10y ago
>The title seems to intentionally misrepresent the retraction to push an agenda (or the author has some issues with basic logic) Almost certainly the former. Notice the dismissal of scientific evidence because they dislike the implications. Every study on the subject has shown clear racial IQ differences. That is not "pseudo-science". Arguing about why that observation exists is fine, but pretending the observation itself must be wrong because it hurts ones feelings is not reasonable. >The retraction is that the strong/definitive proof that "the camel has two humps" was fabricated/exaggerated. It isn't even that. The bimodal distribution is very clearly there, the "retraction" is just to the claim that this is an innate characteristic. Something which was widely repeated, but which the actual paper never even claimed. >The camel has gone back to having an unknown number of humps It still has two humps, we just don't know why. But we never knew that in the first place.

_pmf_ 10y ago

> The camel has gone back to having an unknown number of humps Some sources even go as far as saying there is no camel involved at all, and might have never been.

braythwayt 10y ago

In the absence of that paper, we had plenty of reasonable hypotheses about the ability to program. Like “Put 10,000 hours into it, and you’ll master it.” Or “It follows a distribution similar to other skills involving mathematics.” The paper presented an unusual hypotheses, that there was this sharp distinction between those who can program and those who never will, and that this distinction was somewhat orthogonal to other measures of scholarship. So for example, one might be a good architect but never get good at programming no matter how much one tried. You’re right we haven’t disproven this hypothesis, but given its novelty, the burden of proof is on "the camel has two humps." With the paper retracted, we do not presume it has an unknown number of humps, we presume that skill writing programs is going to be similar to other skills we observe. As this article observes, unusual outcomes in attempting to teach programming may just as easily be explained by the fact that in a young field, we may not know how to teach programming. If we’re going to chase ‘humps,’ perhaps we should look for unusual distributions in the skill of teaching programming. We may be terrible at it, and perhaps the skill we are really observing is the skill of learning to program in spite of didactic and structural obstacles.

jkot 10y ago
Paper is here: http://wiki.t-o-f.info/uploads/EDM4600/The%20camel%20has%20two%20humps.pdf http://wiki.t-o-f.info/uploads/EDM4600/The%20camel%20has%20t...
- Smaug123 10y ago
  "In the absence of the paper" meant "now that the paper has been retracted" rather than "I couldn't find the paper".
venomsnake 10y ago
In my class there were people that groked recursion in half an hour, and the other needed a week. And not a big gap in between. It is anecdotal evidence, but there are people with innate ability. Also - natural distribution makes the one hump camel the default hypothesis.
- braythwayt 10y ago
  A one-hump camel is a fine hypothesis. But multiple humps, implying “muggles and wizards,” is not.
- jrochkind1 10y ago
  Or perhaps the people who understood recursion in a week had been writing code since they were 12, and those that didn't were new to it. Or something else we haven't thought of, that is still not innate aptitude. Or the people who understood recursion easily will not be the same people who understand, say, continuations easily. Still, I'd assume that with programming like I assume for most skills (music, athletics, lawyering, foreign language, whatever), some people start out with more aptitude than others, and find it easier than the others. I wouldn't assume it's a markedly more pronounced or separated distribution in CS/programming than for other things though. (Also, I have actually been programming since I was 12, and additionally believe I do have some aptitude for it that makes it easier for me than for some others, I'm pretty good at it -- and I still remember how hard it was for me to understand pointers in Pascal when I first learned them, which seem so straightforward to me now I have no idea why it was challenging at first! And I'm glad I had good teachers in formal coursework.)
  - spdionis 10y ago
    I didn't understand what all the fuss about recursion was about for it to require more words than "a function that calls itself". Sounded trivial to me. Later I understood that a number of implementation details make the technique a bit special. The concept itself still sounds trivial to me though.
    - jrochkind1 10y ago
throwaway856 10y ago
Meanwhile, it's taken for granted that not everyone can be a doctor, dentist, or lawyer. You don't see doctors telling people that anyone can "learn to med," but programmers see nothing wrong with devaluing their profession in the eyes of the masses by telling them that anyone can learn to do what they do, or worse, that it's easy, and that we shouldn't assume anything else until its proven otherwise. Programmers are far too egalitarian for our own good and our increasing marginalization and stagnant wages are the inevitable consequences.
- contravariant 10y ago
  I think saying 'everyone can program' is not the same as 'everyone can be a programmer'. Similar to how saying 'everyone can (learn to) take care of their teeth' is not the same as 'everyone can be a dentist'.
- JoBrad 10y ago
  Anyone can learn when they have a cold, and what to do about it. In the same way, anyone can learn to write a simple program. Not everyone has the dedication and skill to become a great MD, and the same applies to being a programmer.
  - geebee 10y ago
    I agree. The confounding factor (I'm stating the obvious, I know) here is that it's hard to determine what makes a "programmer", whereas there is a very clear set of criteria for what makes a lawyer or doctor. Although it's always tough to compare fields, I do think that some ways of measuring the skill set and educational requirements for a software developer do place it in one of the most rigorous fields out there. Majoring in computer science at a reputable university (I don't mean an elite one, I just mean one that requires the standard curriculum) typically requires two years science and engineering track calculus (not the easier one year, slower paced track available to econ or bio majors at some universities). Physics is often a requirement, as is an additional year of upper division mathematics (differential equations, calculus based probability), along with some classes that intersect with mathematics had have a heavy computing component, such as numerical analysis which generally involves computational methods to solve mathematical problems that aren't amenable to closed form solutions, or mathematical algorithms that require so many iterations that they aren't practical to solve by hand, optimization, graph theory. Then you add in compilers, operating systems, and other demanding electives. And keep in mind, CS or other Math/Physics/Eng students typically must take a far more substantial general curriculum in humanities than humanities students must take in quantitive fields. We don't get out of writing papers the way they get out of difficult math. People often point out that a field like law requires a three year grad degree, but honestly, in many ways, I think is is like comparing people who run at a 8 minute mile pace for 70 minutes vs people who run at a 6 minute mile pace for 40 minutes. You can't just compare the time spent, you have to compare the rigor of that time. Attrition rates for computer science are typically high even in elite schools, including at the graduate level (elite law schools, by contrast, often have attrition rates below one half of one percent, and many of the students come from fields like history or poly sci - nothing wrong with those fields, they are interesting, but they really don't have anywhere near the same attrition rates as CS or related majors). And if you do get a grad degree, then I'd say you've honestly gone through something much more difficult if you did it in Math/CS/Eng/PhysicalScience. Of course, you don't have to strictly major in CS or a related field to be a programmer, but consider what it takes to get through the google interviews. Try out some of the medium to difficult questions from "cracking the coding interview", and think about the poise, communication skill, analytical ability, and coding ability it takes to do a good job on these question sin 45 minutes at a white board (as an unsuccessful google interviewee myself, I assure you you are expected to make substantial progress on these problems, and medium to difficult is surely fair game!) You could get to this through self-study or formal education, but either way, it most definitely is not a low barrier to entry. Ok, not everyone works at google, and many of us work on crud apps. However, I have yet to see the mythical "simple crud app" that people refer to when they talk about how most programmers don't have hard jobs. These apps usually don't have deep algorithmic complexity, but they are hard to work with. You often inherit a difficult and poorly documented code base that you need to follow through, logically, with a fine toothed comb. You often have to get up to speed with a new framework, or an older one that uses deprecated methods during an era of substantial churn. You need to tease out often elaborate business logic and calculation pipelines from analysts or other non-technical workers that they have trouble communicating to you. And you often have to do this under intense pressure to provide estimates and meet deadlines, often from people who work in much more predictable fields and see your hesitance to commit as a sign of unreliability or a lack of professionalism. These, in my experience, are the "easy" crud projects. Honestly, I think researching and applying a novel machine learning algorithm to a data set can be a lot easier in many ways. That turned into a rant, but in short: this is a really hard job (and JoBrad, I hope it's clear to you that none of this is in disagreement to what you wrote, more riffing on the theme here…). Programming it isn't easy at all. I do think the reason that there is an alleged "shortage" is largely due to the fact that people who can handle this kind of work (it requires a huge about of logical reasoning, quantitative reasoning, consulting and working with vague requirements and end users, and presentation skills under pressure) have a lot of options out there. The market is actually working, pay and working conditions need to improve quite a bit to draw people away form those other things they're doing and into programming in the numbers silicon valley employers would like to see. And it won't happen overnight, ramp up time takes a while, this will be (if it happens) a pretty painful transition that will force the tech industry to dig pretty deep.
red_admiral 10y ago
In the absence of that paper, the only related thing I'm familiar with that claims a basis in evidence is Spolsky's [Hitting The High Notes][1]. The hypothesis there was that time spent on assignments and grade obtained are two essentially independent variables. [1] http://www.joelonsoftware.com/articles/HighNotes.html http://www.joelonsoftware.com/articles/HighNotes.html

venomsnake 10y ago

Politics. Science is always better accepted when it conforms or is spun to conform to the current zeitgeist. So it with bad science, no science and pull out of someone's ass (pseudo) science. And right now the zeitgeist in tech is to increase diversity.

douche 10y ago
Shh, you can't possibly suggest that different people might have the slightest difference of innate aptitudes! That's super-extra-double-badthink! You don't want to be the subject of the next Two Minutes Hate?
SolaceQuantum 10y ago
By this rhetorical implication, you're saying that not only are current demographics in tech (majority male, white, upper middle class) that way because those demographics are more skilled than other demographics, but also that any studies implying as such as stomped out by political pseudoscience proposing less effective diversity measures. And of course, I can't ask you for a source that studies are getting stomped out by political pseudoscience, because those sources will also have been stomped out. So I should instead ask you: how did you get this impression?
- 8127612981 10y ago
  Just look at the differences inside your purportedly "privileged" "white male" group if you aren't capable of suppressing your ideologies otherwise. In fact, all studies should do so to avoid endless blathering on the Internet.
  - SolaceQuantum 10y ago
    I do apologize. I didn't imply any privilege here and apologize if I came off as trying to treat this is a privilege perspective. My confusion comes from the rhetorical implication that current demographics in computer science are that way because those demographics are somehow just better at it than others, and also that any proof of this us stomped out by political pseudoscience. I'm asking where gp gets this impression. I'm also curious what you mean by 'all studies should do so'. Do what, exactly? Analyze the demographic of white heterosexual upper middle class differently? I'm sure that might be interesting, but it's already a very specific demographic that fits class, sexuality, race, and gender identity. What other categories are being neglected that are skewing the view of demographic majorities in the technology industry?

scotty79 10y ago

> The camel has gone back to having an unknown number of humps Camel has gone back to be assumed to be typical gaussian camel as for many camels we don't know much about.

MustardTiger 10y ago

>The title seems to intentionally misrepresent the retraction to push an agenda (or the author has some issues with basic logic) Almost certainly the former. Notice the dismissal of scientific evidence because they dislike the implications. Every study on the subject has shown clear racial IQ differences. That is not "pseudo-science". Arguing about why that observation exists is fine, but pretending the observation itself must be wrong because it hurts ones feelings is not reasonable. >The retraction is that the strong/definitive proof that "the camel has two humps" was fabricated/exaggerated. It isn't even that. The bimodal distribution is very clearly there, the "retraction" is just to the claim that this is an innate characteristic. Something which was widely repeated, but which the actual paper never even claimed. >The camel has gone back to having an unknown number of humps It still has two humps, we just don't know why. But we never knew that in the first place.