Feminists often complain, with considerable justification, that Men’s Rights Activists try to turn every conversation about women’s issues into a game of “what about the men?” You’re talking about female rape victims — well, what about the male rape victims?
The trouble with this strategy, from the point of view of the Men’s Rights Activists anyway, is that this little “gotcha” is much less of a “gotcha” then they’d like it to be.
In the case of rape, for example, feminists are well aware that men are raped as well: the “Don’t Be That Guy” ad campaign, which sent so many MRAs into hysterics, focused on male victims as well as female ones. The emergency room rape advocate organization that a friend of mine volunteers for provides advocacy for victims regardless of gender.
So many MRAs have started playing another game: trying to twist the conversation around in order to cast women as the villains. Rape is a bit tough for them here, since the overwhelming majority of rapists are male. So MRAs talk about the alleged epidemic of female false accusers instead. Or they change the topic entirely and make dead baby jokes (see my post yesterday).
Recently, MRAs have tried a new strategy, seizing on data from The National Intimate Partner and Sexual Violence Survey, a massive study conducted in 2010 under the aegis of the Centers for Disease Control, to claim that “40% of rapists are women.”
This is a claim repeated by numerous MRAs on numerous websites; see, for example, this post by A Voice for Men’s Typhonblue on the blog GendErratic. Here’s the same claim made into an “infographic” for the Men’s Rights subreddit.
Trouble is, this claim is flat-out false, based on an incorrect understanding of the NISVS data. But you don’t have to take my word for it: the NISVS researchers themselves say the MRA “interpretation” of their data is based on bad math. It’s not just a question of different definitions of rape: the MRA claims are untenable even if you include men who were “made to penetrate” women as victims of rape (as the MRAs do) rather than as victims of “sexual violence other than rape” (as the NISVS does).
I wrote to the NISVS for clarification of this matter recently, and got back a detailed analysis, straight from the horse’s mouth, of where the MRA arguments went wrong. This is long, and a bit technical, but it’s also pretty definitive, so it’s worth quoting in detail. (I’ve bolded some of the text below for emphasis, and broken some of the larger walls of text into shorter paragraphs.)
It appears that the math used to derive an estimated percentage of female rapists … is flawed. First, we will summarize the assertion and what we perceive to be the basis for the assertion.
According to the web links, the “40% of rapists were women” was derived from these two steps:
1) Combining the estimated number of female rape victims with the estimated number of being-made-to-penetrate male victims in the 12 months prior to the survey to conclude that about 50% of the rape or being-made-to-penetrate victims were males;
2) Multiplying the estimated percentage (79%) of male being-made-to-penetrate victims who reported having had female perpetrators in these victims’ lifetime with the 50% obtained in step 1 to claim that 40% of perpetrators of rape or being-made-to-penetrate were women.
None of these calculations should be used nor can these conclusions be correctly drawn from these calculations.
First the researchers clarify the issue of definition:
To explain, in NISVS we define rape as “any completed or attempted unwanted vaginal (for women), oral, or anal penetration through the use of physical force (such as being pinned or held down, or by the use of violence) or threats to physically harm and includes times when the victim was drunk, high, drugged, or passed out and unable to consent.”
We defined sexual violence other than rape to include being made to penetrate someone else, sexual coercion, unwanted sexual contact, and non-contact unwanted sexual experiences. Made to penetrate is defined as including “times when the victim was made to, or there was an attempt to make them, sexually penetrate someone without the victim’s consent because the victim was physically forced (such as being pinned or held down, or by the use of violence) or threatened with physical harm, or when the victim was drunk, high, drugged, or passed out and unable to consent.”
The difference between “rape” and “being made to penetrate” is that in the definition of rape the victim is penetrated; “made to penetrate” by definition refers to cases where the victim penetrated someone else.
While there are multiple definitions of rape and sexual violence used in the field, CDC, with the help of experts in the field, has developed these specific definitions of rape and other forms of sexual violence (such as made to penetrate, sexual coercion, unwanted sexual contact, and non-contact unwanted sexual experiences). We use these definitions to help guide our analytical decisions.
Now the researchers get into the details of the math:
Regarding the specific assertion in question, several aspects of mistreatments of the data and the published estimates occurred in the above derivation:
A. While the percentage of female rape victims and the percentage of male being-made-to-penetrate victims were inferred from the past 12-month estimates by combining two forms of violence, the percentage of perpetrator by sex was taken from reported estimates for males for lifetime (a misuse of the percentage of male victims who reported only female perpetrators in their lifetime being made to penetrate victimization). This mismatch of timeframes is incorrect because the past 12-month victimization cannot be stretched to equate with lifetime victimization. In fact, Table 2.1 and 2.2 of the NISVS 2010 Summary Report clearly report that lifetime rape victimization of females (estimated at 21,840,000) is about 4 times the number of lifetime being made-to-penetrate of males (estimated at 5,451,000).
B. An arithmetic confusion appears when multiplying the two percentages together to conclude that the product is a percentage of all the “rapists”, an undefined perpetrator population. Multiplying the percentage of male victims (as derived in step 1) above) to the percentage of male victims who had female perpetrators cannot give a percentage of perpetrators mathematically because to get a percentage of female rape perpetrators, one must have the total rape perpetrators (the denominator), and the number of female perpetrators of this specific violence (the numerator). Here, neither the numerator nor the denominator was available.
C. Data collected and analyzed for the NISVS 2010 have a “one-to-multiple” structure (where the “one” refers to one victim and the “multiple” refers to multiple perpetrators). While not collected, it is conceivable that any perpetrator could have multiple victims. These multiplicities hinder any attempt to get a percentage of perpetrators such as the one described in steps 1) and 2), and nullify the reverse calculation for obtaining a percent of perpetrators.
For example, consider an example in which a girl has eight red apples while a boy has two green apples. Here, 50% of the children are boys and another 50% are girls. It is not valid to multiply 50% (boy) with 100% (boy’s green apples) to conclude that “50% of all the apples combined are green”. It is clear that only 20% of all the apples are green (two out of 10 apples) when one combines the red and green apples together. Part of the mistake in the deriving of the “50%” stems from a negligence to take into account the inherent multiplicity: a child can have multiple apples (just as a victim can have multiple perpetrators).
D. As the study population is U.S. adults in non-institutional settings, the sample was designed to be representative of the study population, not the perpetrator population (therefore no sampling or weighting is done for the undefined universe of perpetrators). Hence, while the data can be analyzed to make statistical inferences about the victimization of U.S. adults residing in non-institutional settings, the NISVS data are incapable of lending support to any national estimates of the perpetrator population, let alone estimates of perpetrators of a specific form of violence (say, rape or being-made-to-penetrate).
E. Combining the estimated past 12-month female rape victims with the estimated past 12-month being-made-to-penetrate male victims cannot give an accurate number of all victims who were either raped or being-made-to-penetrate, even if this combination is consistent with CDC’s definition.
Besides a disagreement with the definitions of the various forms of violence given in the NISVS 2010 Summary Report, this approach of combining the 12-month estimated number of female rape victims with the 12-month estimated number of male victims misses victims in the cells where reliable estimates were not reported due to small cell counts failing to meet statistical reliability criteria. For any combined form of violence, the correct analytical approach for obtaining a national estimate is to start at the raw data level of analysis, if such a creation of a combined construct is established.
So you’re going to need to go back to the drawing board, MRAs.
What is especially distressing here is that the NISVS data could have been the starting point for a serious discussion of male victims of sexual assault by women, which is a real and often overlooked issue. Unfortunately, MRAs have once again poisoned the well by misusing data in an attempt to exaggerate the purported villainy of women and score cheap rhetorical points.
NOTE: A regular in the AgainstMensRights subreddit approached the NISVS researchers with this same question some months back. Unfortunately, the statement they got back from the NISVS contained an incorrect number. The statement I’m quoting here corrects this number and adds more context.
I can provide contact info for the NISVS representative who got back to me on this to any serious (non-troll) person who requests it.
@argenti, just curious, the ‘inconvenient’ stat of majority of male victims raped by men is also of a lifetime figure?
Yes, the 12 month number was too small to be statistically reliable. And I’ll review your link in a bit, I need coffee to process Teh Maths 🙂
Oh and don’t worry about asking questions, I’m happy to answer stats questions. I spent ages offering to teach MRAs how not to kill math, with no takers, so people who actually want to learn? Ask away!
1) I’m assuming you’re referring to these quotes —
“‘Nearly a quarter of men interviewed reported perpetrating rape against a woman or girl.'”
“”One in four men across Asia admit to having committed rape.” This statistic was widely reported around the world, following the publication of a UN study. Could that possibly be the case?”
The issue isn’t 1 in 4 versus 25%, it’s “in Asia” versus “of men interviewed”. So you’re riht that the sample size is the issue — it just isn’t representative enough to say it applies to all of Asia, just the interviewed men.
2) Yes. Areas experiencing civil conflict or war almost always have higher rape rates than though in a (relative) peacetime.
3) The issue isn’t about whether they’d admit to it, the issue is that the women may’ve “consented” because they also felt that having sex was their wifely duty. That is, it may reflect oppressive gender roles better than rapists. In the US, Canada, UK, etc, that would be called rape now, but in the US, until a few decades ago, you couldn’t rape your wife — you were legally entitled to sex from her whenever you wanted. If that’s the case in the areas studied, that question doesn’t tease out men who coerced her from men who simply went along with the gender roles they’d been raised wih. The latter is still wrong, but reflects on gender roles, not rape, and that question conflates the two.
I’d need to see the video on the US studies to comment on that though, sorry.
Also, could you capitalize at least the beginning of your sentences? It’d make it a bit easier to follow what you’re asking 🙂
@Argenti, im sorry, the caps lock key on my computer hasn’t been working. but now it’s been more like a bad habit.
I have some questions about schaka’s post? do you know how we go from 1.3 million male rape victims in a year to just 5.5 million in a lifetime? Are adult men at much higher risk of being raped and/or raping men has become much more common in the past years?
this part also stuck out to me; “16% of men with documented cases of sexual abuse considered their early childhood experiences sexual abuse, compared with 64% of women with documented cases of sexual abuse. These gender differences may reflect inadequate measurement techniques or an unwillingness on the part of men to disclose this information (Widom and Morris 1997).”
Less than 20% w/ documented history of abuse considered themselves to be abused anymore. According to schaka, it doesnt make sense to look at lifetime figures; even if you consider that the participants weren’t directly asked for their “opinion” on what happened to them, but the decision was made based on questions found towards the end of the study’s document. Do you think this means men rationalize/justify abuse which happend to them to a much greater extend than women, since they just said no to questions that would’ve been a clear yes 5/10/15/20 years ago?
also, I don’t mean to send you on a wild goose chase (I don’t know if I used that phrase right) but adiabat also responded to your stat assessment. It had something to do with whether Mras can bully anonymous participants, which I don’t have an informed opinion on.
i forgot the video – youtube.com/watch?v=P91QJWIT8DI this sounds very antagonist towards feminism so you wont like it.
Typhonblue just called me a bully: http://www.genderratic.com/p/836/manufacturing-female-victimhood-and-marginalizing-vulnerable-men/#comment-121710
o_O
“I have some questions about schaka’s post? do you know how we go from 1.3 million male rape victims in a year to just 5.5 million in a lifetime? Are adult men at much higher risk of being raped and/or raping men has become much more common in the past years?”
You might want to reread the last couple of pages, there was lots of speculation on wtf’s going in there. Could be age, could be that the year in question just saw a lot more rape than average, there were a few more options, but you’do do better to go read that in context.
“this part also stuck out to me; “16% of men with documented cases of sexual abuse considered their early childhood experiences sexual abuse, compared with 64% of women with documented cases of sexual abuse. These gender differences may reflect inadequate measurement techniques or an unwillingness on the part of men to disclose this information (Widom and Morris 1997).””
That’s the other study, the one TyhponBlue loves so much (which, in a fucked up way, could explain the first question since one of the theories is that men forgot the earlier abuse)
“Less than 20% w/ documented history of abuse considered themselves to be abused anymore. According to schaka, it doesnt make sense to look at lifetime figures; even if you consider that the participants weren’t directly asked for their “opinion” on what happened to them, but the decision was made based on questions found towards the end of the study’s document. Do you think this means men rationalize/justify abuse which happend to them to a much greater extend than women, since they just said no to questions that would’ve been a clear yes 5/10/15/20 years ago?”
Possibly, possible some did forget, possible some weren’t comfortable disclosing their abuse, and I’m curious what sort of documented history they mean, because I found out I had a social services file years after the fact — if it hadn’t slipped cuz the school thought I knew, and that was the “documented history” they meant, I’d have said no and thought the answer correct. That is, depending how the worded the questions, they may not have been asking what they thought they were.
And yep, you’re using the phrase “wild goose chase” correctly. As for the video, and adiabat, I’m going to have to get back to it later, my sleep is all off and I haven’t the brain cells for it right now.
Ally: That seems to be an indication TB has no real response. It’s fundamentally a concession of defeat.
Congratulations, 1: you won, 2: you have made “the big time”.
Oooh, Ally, you big nasty bully you, scaring poor little Typhoid Blue like that!
::applauds::
Ally — oh that’s just special.
As for wanting the raw data, someone has clearly never tried analyzing large samples. My hurts just thinking about working with that many data points!
And all over my preferred pronouns!
I must say that I’m glad to see everyone but her taking your correction relatively gracefully. FTR, part of why I like “ze” is because z is a poor neglected letter in English.
Wait, what about Ally’s FREEZE PEACH!!!
Freeze Peach is only for dudes, cloudiah, you know that. Or rather, MRAs and (on sufferance) feMRAs.
I should have told them I’m a trans girl. Then they would extend their solidarity to me and apologize for taking my freeze peach! Compassion for “men” and “boys” indeed.
By the way, I’m suddenly craving peach ice cream.
Can anyone who goes to those pages recall anything resembling compassion for anyone, ever, from them? I don’t think rageboners about made-up tales of Rongs Dun To Menz count.
I thought that Argenti was simply working with the data on hand as a private citizen, fool that I was. Then I checked out the Genderratic thread and learned from “Adiabat” that Argenti is (somehow) in cahoots with the CDC. Release the raw data! Tear down this wall!
While Argenti’s calculations work with the the available data, would it work with data none of us have? Thanks to the CDC and (somehow) Argenti, we’ll never know. How conVENient!
After an endless number of posts, Adiabat grudgingly admits that Argenti is right, albeit ze is also being a total stickler.
Extra Fun Quote:
Oh, snap!
Is it a vast outlier, or merely an outlier? We at Genderratic have decided that it would be more ideologically correct if it was just a bit of an outlier, so obviously that’s the appropriate conclusion and we should proceed on the assumption that it’s true.
BTW the rest of you lack academic rigor.
So mockery and logic are incompatible? I see.
And Argenti is Dave.
Wow, the logic in that one is… strong?
@Argenti, I’m apologizing for not responding to you sooner, I will be asking you some more tomorrow. also, do you mind being referred to with pronouns “they/them,” as well as “ze/zir”? I usually frequent tumblr a lot often and have never seen ze/zir used ever.
@Argenti, After looking through the speculations on the last comment page it seems that the age was a huge factor here. http://schaka.tumblr.com/post/65820948304/mra-male-rape-statistics-are-wrong I think schaka already pinpointed this problem, i didn’t read too carefully before – “Participants in the study had to be over 18 and we know that kids are unlikely to be made to penetrate.” And regarding how much the 12-month figure differs from the lifetime, would the 12-month figure for male mtp victims be considered an outlier then? also sorry, if you’re more comfortable w/ ze/zir, i will use them.
@Brooked hi, I could be wrong but it sounded adiabat was saying that both they and argenti have different methods in approaching numbers and that without the raw data we’ll never truly know who’s correct? Then they proceeded to explain using Argenti’s original ice-cream sprinkles examples. A lot o that hinged on whether it’s ok to release raw data from anonymous people.
@Argenti again, sorry for the 3 day delay.
hannasoumaki — part of the difference in how adiabat and I are approaching this is that I am…less fond…of Bayesian statistics. Like, that XKCD is cute and all, but betting the machine? Not math. My reasons here are complex and probably confusing, so I won’t confuse you with them, but the difference in mathematical approach to using the lifetime figures to calculate one year data is part of it.
Now, about the post you linked, but given the survey participants are largely middle aged, I don’t think that also could account for the difference between the two numbers being that large. But, yes, something like half of female rape victims are raped before age 25, and most of them before age 18 — people who wouldn’t have been surveyed since they’re minors. However, that could account for the gender disparity of the lifetime data, but not the disparity between lifetime and 12 month MtP data. Because the sample was mostly middle aged people — men who’d been at risk of being made to penetrate (raped) for only a few years less than the women had been at risk of being rape — you’d expect a decent number of them to have been rapid by MtP prior to the 12 months in question.
More ice cream examples!
If girls are allowed to eat ice cream birthday cake, and boys aren’t, then for young adults you’d find that the number of girls who had ever had an ice cream cake, versus those who’d had it in the last year, would be fairly similar percentage wise — if 90% had ever had an ice cream cake, then somewhere around 90% probably had it in the last year. But for boys, you’d find far more young adults who’d had one in the last year than had had one in their lifetime, since they’ve had 18~ less years to be eating ice cream cakes (call it 10~15 for MtP though, since very young girls aren’t raped in large numbers, and older teenage boys are at risk of being made to penetrate).
However, if you ask middle age people, you’d expect to find similar rates for men and women for both lifetime and 12 month ice cream cake consumption — if the rates are actually equal. If women like cake more than men, then you expect to see higher number for women for both lifetime and 12 month data. The middle age men have had plenty of time to eat ice cream cake if they’re going to.
Otoh, if you find that men, in the last year, had way more ice cream cake than in their lifetime, while women have had ice cream cake at about the same rate as ever, and your sample is middle aged adults, then ice cream cake was probably rather popular among men last year.
/strained analogy
What I’m getting at here is that the sample was old enough that you’d expect to see similar rates unless the last year was an outlier. Or, at least, age probably isn’t the main missing variable when it comes to the difference between lifetime and 12 month data for men. Could be part of it, but probably not to the degree they found, not with a sample where approximately half their lifespan is covered in the lifetime data.
More importantly since there is obviously something funky going on with the lifetime versus 12 month data, any assumptions about applying other lifetime data to the 12 month data are rather iffy until you figure out wtf is up with the disparity there.
Ah, a less stretched analogy. It’s like looking at photos of someone from their lifetime and finding most we’re taken by their mothers, then finding that men had had a lot more photos taken in the last year than you’d expect given how many photos they’d had taken in their lifetime thus far…and deciding that mean their mothers took a lot of photos of them in the last year. Just because the mothers took most of the photos over the course of their lifetimes doesn’t mean their mothers took most of the photos taken of them in the last year. Even more so when there’s already obviously weird going on with the number of photos they’ve had taken in the last year. (“Ever had your photo taken?” “Sure, plenty of times” “who took most of them?” “Hm, my mother probably” “had photos taken this year?” “Yeah, a surprising number of them actually” “I assume your mother took most of them?”…sounds a bit less than logical right?)
Damn, that got long. Sorry about that!
No one knows the gotcha game better than David Futrelle. It’s your oeuvre.
David, now you are just backtracking. You could be honest about it but then intellectual integrity has never been your strong suit. Why am I even talking to the gotcha master?