RescueTime (YC 08) Data: Are Men more Productive than Women? | Hacker News Reader

RescueTime (YC 08) Data: Are Men more Productive than Women?

blog.rescuetime.com

73 pointswebwright62 comments

Lies damn lies and statistics.

1) Does it surprise anyone that they have 5x as many men as women as users? I wonder if you broke down by occupation what percentage of their users are software developers and engineers compared to others?

2) It's not a random sample. While they say "The data for this report was compiled from 8,000 randomly selected men and women", it is not of all people, it is of their users. Those are two vastly different things.

3) "All this adds up to huge differences in the amount of knowledge work men get done compared to women. Our data shows women only work 76% of the time that men do. Interestingly, the National Committee on Pay Equity found that women earn 77% of what their male counter parts do." is one of the dumbest comments I have ever seen in my life.

THEIR TOOL DOESN'T CATCH ALL WORK. I stopped using it because it is utterly useless if you step away from the computer and are productive in that time. They are saying "Our data shows women only work 76% of the time that men do. [in front of computers]" Dropping out the in front of computers part is huge. Is the President of the United States a knowledge worker? Because he doesn't have a computer on his desk and therefore would be 0% as productive as someone doing data entry according to this methodology.

For that matter, me sitting in front of my computer all day with Eclipse open (no matter how much I actually commit) is more productive than my dad, a CEO, who spends a lot of his time with a pad of paper out talking to people. Hmmmmmm.

I understand that this tool has its place, but to say something so outrageously false really casts the company as a whole in a bad light. Blogging this was poor judgement. At best it is just some dumb people who don't understand data, at worst it is offensive.

I think you should re-read the post. The phrase "on his/her/their computers" is repeated 4 times in the (fairly short) post. I think it's pretty clear that this doesn't apply when comparing a pad/paper CEO and an engineer. And we very purposefully didn't draw any conclusions (though we did admittedly ask leading questions to fuel the conversation!).

We say a few times in the comments that this could well be a reflection of the types of jobs that the 4000 women have compared to the 4000 men-- they may have more social jobs or more "afk" jobs. It'd be an interesting followup to grab 1000 female engineers and 1000 man engineers to see if the differences hold up. I don't know if it will, but what if it did? Would it be so horrible if women were less suited for multitasking and knowledge work? Because they sure as heck are better at a lot of other things. They're, on average, smarter than men. They have better reflexes. Check out "Is there anything good about men" - great essay: http://denisdutton.com/baumeister.htm

If they WERE less suited for it, it would be interesting to see how much culture and education influenced their suitability. i.e. Does the difference fade away if you correct for educational differences, etc.

At the end of the day, it's just an interesting chunk of from a single web service that has a very strong bias towards geeky users.

At the end of the day, you flung up some crap on your company's offical blog that is both horribly misinformed from a statistical perspective and about the subject you are posting on.

Is that professional? Is that good for your company? If I were an investor I'd be PISSED. If I hadn't canned my account to your site about 6 weeks after I made it (cool tool by the way, just missed too much of my work since I don't spend all day on my computer), I'd be canceling it today. And I sure as hell won't ever be trying it again. And I'll specifically be recommending against it.

At my startup we had a discussion about using data from our users to draw attention the way you are trying to here (and Mint.com has very successfully done in the past as just one example). The problem is you have to recognize where the mine fields are.

Replace every single place you used the word "women" and replace it with "black people" and see if it is offensive to you yet.

I'm sorry that you're angry.

For what it's worth, we worked pretty hard to make this as statistically solid as we could with the dataset that we had. The subject we're posting on is "How 4,000 men differ from 4,000 women in RescueTime". While the data might lead to some interesting questions, I don't think anyone would assume that this is necessarily a reflection of a broader population (any more than Mint's data was).

I think your "black people" example is interesting. If we were comparing designers to developers, would you be so incensed? Yours is literally the first actually angry response all day. Is it possible that you're overreacting?

In terms of business effect, signups today have been abnormally high and cancellations have been slightly to the low side.

It was meant to be provocative, but so far this hasn't ended up being a mine field. Again, sorry that we've upset you.

I'm not the only angry response you've gotten today. Ctrl+F this thread for "hackermom", do you think she liked your post? Just one among several.

I know YOU don't believe that women are 77% as productive as men and that explains the pay gap, I get your tongue in cheek tone.

The problem is that there are lots of people who use these half cocked "pieces of data" as part of larger arguments and it is exacerbated by a statement like "a random sample of 8,000 people" when clearly, this is not a random sample. It should say "this is not a scientific sample", because it isn't.

This is how we got birthers, "logical racists", and conspiracy theorists.

Perhaps I am more sensitive to it, I took a class on gender studies, I hung out with some feminists, my wife makes a lot of money (more than I for a while, and she wasn't on a computer nearly as much as I).

I think I just get mad at misapplied statistics, the lack of distinction between correlation and causation, and people saying ridiculous things to get attention (of which this does all 3). Suffice to say fivethirtyeight.com is one of my "read every day" sites.

Please don't blame me for inventing a gun that someone later uses to shoot you. The problem is with the sophists misapplying others' research, trying to find evidence to support their pre-formed conclusions instead of following the evidence where it may lead; the problem is not with the researchers themselves, or the objective facts they produce.

Um, what? I've seen research. I've done research. And this is not research. Research implies some knowledge of statistics and familiarity with the relevant science. Just because a three year old child likes to play with toy planes does not mean they're a pilot. And just because some software geeks like to play with numbers does not mean they have any clue what they're doing.

This is not the boy scouts. You don't get a research merit badge just for showing up and crunching some numbers.

I have to agree that the post wasn't written very sensitively.

Here are the following red flag passages, for me, at least:

"From what I can tell, the 23rd chromosome has a pretty amazing impact on the way people use computers." -Drawing a conclusion from data you admit has large sampling issues.

"Women spend more time socializing and shopping" - You did not mention any comparative "frivolous" activities that men might take part in more than women; say, gaming.

"Evidently, there’s a reason they are called “man” hours." - Using a limited data set to large conclusions about female working habits in all contexts

Generally, the whole thing was both hyperbolic and quite inflammatory.

The only part I cringed on was the "man hours" line. Just does not work in text.

Speaking as one of their investors, I'm not pissed at all. In fact I've found political correctness is if anything inversely correlated with success in startups. It seems to derive from a combination of cowardice and conventional mindedness, which are the last two qualities you'd want in a startup founder.

Lose a customer gain a customer. I applaud your bravery.

These quotes are the ones you should look at:

"4) Women spend fewer hours on their computers Evidently, there’s a reason they are called “man” hours. On average, male information workers spend 14% more time per day working on their computers than women do."

Glossing over a lot in that quote

Or how about trying to make your data way more scientific than it is (based on your own comments it is clear you don't personally understand this concept)

"About the data: RescueTime provides a tool to allow individuals and businesses to track their time and attention to see where their days go (and to help them get more productive!). We have hundreds of millions of man hours of second-by-second attention data from hundreds of thousands of users around the world, tracking both inside and outside the browser. The data for this report was compiled from 8,000 randomly selected men and women."

I couldn't agree more. I've seen countless pieces with flimsier statistics than this claiming that women are in some way more intelligent, more rational, or more ethical than men.

If a study finds that more parts of a man's brain activate when he does X task, the headline reads that women can process it more efficiently and only need to use a small portion of their brains.

If a study finds that more parts of a woman's brain activate when she does X task, the headline reads that women are able to recruit more of their brains and do the task holistically.

This piece was a breath of fresh air.

One could say the same thing about studies that purport to show a huge market-gravity-defying wage/gender gap.*

* it's only important because our President is in favor of establishing a government organization to determine "fair" pay.

Well it is a fact that there is a wage gap in the US if you look at the overall average of men and women. Rarely if you look at a man and a woman in the same job is there a huge pay gap. Those are two different things and the latter was what people used to complain about, the former is what people complain about today. But there are lots of reasons why this is the case.

http://www.marketwatch.com/story/women-earn-less-than-men-bu...

None of those reasons have to do with productivity.

If women really are a discount, why hire a man at all? That is the question I have never seen answered convincingly.

I'm agreeing with you, I don't think the wage gap (today) is talking about two equally qualified people getting paid different amounts for the same job, although it does happen in some rare circumstances it doesn't account for a 20% difference. That is mostly related to personal decisions on what career to choose, work/life balance, etc.

Maybe women have to settle for less because employers consistently underrate their competence. Since most employers want competent people, if they irrationally believe that women are less competent, they will be less likely to hire women, even at a discount.

In general, statements of the form "but that's impossible since all people act as rational utility maximizing agents" demonstrate an ignorance of the many many studies showing that people do not act completely rationally pretty much all the time.

Given that people choose to install this because they think they have a problem, I'd be curious how much selection bias there is in their sample set.

Yes, it seems quite plausible that RescueTime is best known among technology types, who tend to be male.

I can tell you that's not the case for THIS particular data set. There was data from 4,000 men and 4,000 women, randomly selected.

But yeah, we do have a 5 to 1 male to female ratio and a geekier than average audience.

I used RescueTime for a few weeks because I had a problem with time management, as soon as that phase was over I uninstalled it mainly due to privacy concerns. I wonder how many people have a usage pattern similar to this, and what the average usage time is?

Sampling from biased populations does not remove bias.

He said that our population tended to be male, I agreed and said that we selected an equal # of men/women. I'm not a statistics god, but doesn't that account for that particular bias? There are certainly others-- we'd be the last people to say that this represents a perfect cross-section of society.

Given that we selected 4,000 man and 4,000 women (randomly), how does the preponderance of men in our broader dataset effect this particular analysis?

Sorry if I'm being obtuse-- I didn't do the actual analysis and I'm really pretty rusty on my stats.

I think the parent probably meant the "they think they have a problem" bias.

Though, that's not why I use RescueTime - I just love data. (And by the way, would love to download the fine-grained CSV for all of my activity for all time)

If you have a product that is more attractive to men than women, then the women who find it attractive are unlikely to be typical for the larger population.

So yes, you've adjusted for the tendency to have more men than women. But you still haven't wound up with a random sampling of people out there.

To get that you'd have to select a random set of people, ask them to participate in your study, and go from there. Which would immediately hit you with the fact that over half of the USA is functionally illiterate and therefore does not use computers very much.

Ah, true 'nuff and totally agreed. I think it'd be super interesting to try to get a good cross-section with RescueTime. Even if we buried our users in demographic questions, we'd still have a hard time get truly representative data.

More realistically, I think it'd be interesting to correct/adjust by profession. i.e. do this same analysis for JUST software engineers, for example, to correct for the likelihood that RescueTime women probably have a different distribution among the assorted career paths.

My god, you are the one who wrote this and you don't understand why your sample is so biased? No wonder it is so horrible.

How many teachers are in your sample? How many nurses? (extremely few - how would the tool capture that?)

Or more insiduously compare the number of engineers to the number of people in marketing. Both are "knowledge workers", but they have a very different gender breakdown. And they also have a very different day. Someone in engineering is on their computer all day, someone in marketing or sales probably not. If you are making sales calls all day instead of looking at an IDE, you can be vastly more productive than an engineer staring at a blank screen, but that doesn't show up in RescueTime at all. It's one thing one you are on a team and can account for that, it is another when you make a generalization about the population.

All of your data can be explained with other rational besides "men are more productive than women". Your company approaches the world from the view of engineers to begin with, and then slaps that bias on top of a faulty set of data. You should be careful with this or you are going to have NOW breathing down your neck (I guess all press is good press, but do you really want to make your product piss of women to that extent?).

I didn't write it... I thought I made that clear.

Again, it's SUPER obvious to us (and to you, apparently) that our dataset is NOT representative. Do you think it'd help if I added that to the bottom of the post? We just assumed that's obvious once we described the value proposition.

Read what he wrote not what you think he wrote.

He said picking an even sample of male and female removes the male/female bias, but only that bias.

Edit: Granted, that's not strictly sufficient because the human population is not 50:50 M/F, but that's a side issue.

I think you are missing krschultz's point. There is probably an interaction effect between occupation and gender. Sampling equally from each gender doesn't necessarily remove gender bias.

I think your both (+the people that up voted you) are confusing occupation bias with gender bias.

AKA, if the gender bias was caused by an occupation bias fixing the gender bias does not fix the occupation bias.

No offense, but you are repeating exactly what I said. It's likely that gender and occupation are not independent variables.

WTF, read the comment you are responding to before you respond to it.

Depends on how clever your sampling is.

Good catch, I should have said uniformly sampling.

Anyway, this blog post and much of the surrounding discussion make me really sad about how poorly people understand data analysis.

your model: productivity ~ gender

probably a better model: productivity ~ gender + occupation + gender:occupation

You might also throw in p(procrastination | is_user, gender).

Do you have an embedded economist? I'm volunteering but if you really want to get a ton of PR out of this you might try some famous empirical micro guys (this article would make a great Freakonomics chapter) . Cold calling with "I have unique data" won't offend anyone.

Why shopping and facebook? Both of those seem to favor women over men (in time spent, not in % who have accounts)... What about hacker news, prog.reddit, github, LtU, Lostpedia, porn, news.google.com, etc? Factor those in, and the numbers might come out quite different.

What about programming projects that I happen to be reading/forking/coding which are unrelated to work? From my anecdotal experience (mostly in software development), women focus significantly better than men on the work-related tasks.

From the article: "Men have their distractions, too. They spend about 15% more of their time reading the news than women."

It would have been useful if the article indicated how much time is actually spent on news sites, rather than simply the relative differences.

To add to your response: we didn't put it in the post, but the stats on the "reference" category (where things like dictionaries and code resources live) were pretty close (7.41% for women, 7.15% for me).

Our data shows women only work 76% of the time that men do. Interestingly, the National Committee on Pay Equity found that women earn 77% of what their male counter parts do. </quote>

I've always been interested in these kind of data. Are women earning only 77% of their male counterparts because

a) They are primarily employed in occupations that pay less

b) They take maternity leave and/or extended vacations/time off (taking care of children etc.)

c) Women are just paid less for the same work?

I think the strong correlation presented in the parent comment suggests that women actually work 77% of the time that men do, period.

Whether that is actually true, or - even better - relates in any way to productivity is out of scope here.

A is the primary reason. B is true, but it is not so much that women take time off and are therefore paid less, it is that women take time off and miss out on a few rounds of promotions and get behind a bit. You only take 5 years out of a 40 year career, but you might take out two of the total promotions and that adds up to a lot.

C happens but rarely in the US is it that a woman makes 77% of a man for exactly the same occupation, the difference might be 5-10% but not 23%.

That's a good point. I recall reading a study that men who take time off to be stay-at-home dads have a similar pay/promotion hit (not QUITE as much, but pretty close).

Some people might misinterpret this but it is very interesting data. I think it is more fun than being damning. I put it in the same category as the studies that say what a mother and work at home mom do are worth 130k+.

I personally love RescueTime and subscribe, it has helped me immensely in managing my own time better. So while some may get angry, I find the data useful and the service even more so. I think they were just trying to draw some traffic and get some more customers to help.

The only people I have shown that don't like RescueTime are the ones that seem to figure out how little work they actually do once they start using it. It surely opens your eyes to your non productive time on the computer.

3 observations:

- Brilliant execution of two 37Signals principles/generally smart start-up strategies (advertise like a chef (give away your information), and pick a fight)

- If this product doesn't "scratch an itch" / solve a real problem (people wasting time on computers) I don't know what does

- RescueTime is awesome

This is a doozy. I think this really deserves much, much more research.

"Theory of gravity", "Theory of relativity", everything in between.

Research complete.

A big thing missing is the context of the work. Perhaps not spending time at the computer and "socializing", distributing information, is actually more productive, or even a bullet point on the person's job description. I think a more accurate description for this blog post is "Men spend their time working on computers more than women".

This is a good point. If you're a marketing exec or advertiser for instance, being on Facebook or shopping sites may indeed be part of your job.

Yaw... To be perfectly forthright there was some discussion around accurate titles versus titles that are clickworthy. Obviously, it's a hard discussion that happens at every blog and newspaper in the country that cares about traffic.

We tried to qualify the heck out of the data (while still being provocative) in the body of the post... And even more in the comments of the post. I hope we did a good enough job!

From some of the heated discussions on this thread, i think you guys were successful at doing that. =)

Please could you publish the raw anonymised data, or at least give us estimates of the variation? Without that, the data are meaningless.

What would be useful, not that I have looked into this to much to know that it isn't possible. Would be to group the time spent on HN with the time spent on anything linked from HN.

It's hard to know how much time I spend on HN/HN articles.

Great tool though, RescueTime and DropBox are the two ycombinator companies which I could instantly see a use for in my everyday work.

I'm pretty sure all of this has a logical explanation to it, most likely involving the time women spend giving birth by the stove in the kitchen.

If there is a significant trend here, it would be better to explore it than to try to suppress exploration with dismissive witticisms.

more time working does not necessarily amount to more productivity.

More data less commentary please.

So men are generally (slightly) more productive at computer-related tasks, based on time working vs procrastination time.

But computers are communication devices (in most cases), and women are generally more productive communicators. So they limited time they spent working on computers is probably more valuable.

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