Autogynephilia and masochism: A tale of two assessment biases

Conventional wisdom says that autogynephilia and masochism form a particularly closely correlated set of sexual interests. Recently, I’ve been arguing that actually, conventional wisdom seems wrong, and might be an artifact of some assessment biases. However, I’ve now also come to find a bias in the opposite direction in the dataset I’ve usually used to argue against it, so this puts some nuance on things. I still believe that conventional wisdom is wrong, as I will argue here. Let’s take a look.

In what ways does autogynephilia look correlated with masochism?

Autogynephilia supposedly looks correlated with masochism. Let’s take a look at some specifics.

Probably the obvious authority to look to would be Ray Blanchard, who coined the term “autogynephilia”. One paper written by Chivers and Blanchard found that prostitutes who advertise for crossdressers are those who advertise themselves as dominant. In his book on GID, he also referenced a number of lines of evidence, include common findings that men engaging in erotic asphyxiation are crossdressing; other observers finding especially in case studies that there was an overlap between autogynephilia and masochism; and a study of members of various kink societies finding a great deal of overlap between groups.

A lot of autogynephilic erotic material also seems to take on a masochistic form. There are themes such as forced feminization, in which males are made to crossdress and behave femininely against their will. Another stereotypical form of erotic media for AGPs is transgender transformation, and communities for these are often also masochistic or at least submissive.

Autogynephilia in particular pops up in the case of trans women, and so it might be worth considering what trans women are like. Compared to other groups, trans women seem particularly masochistic:

Self-reported masochism in different groups of people. As can be seen, trans women are particularly masochistic, indicating a connection.

The results seem pretty consistent; how might they possibly all be wrong?

The many problems with these methods

If we were merely interested in whether highly-AGP communities also tend to be more masochistic than average, then the above would be pretty definitive. However, we are interested in something more subtle, and the previous associations are completely useless at determining this more subtle thing.

I would claim that what we are really interested in is whether autogynephilic males – i.e. males with a sexual interest in being women – are particularly likely to be masochistic compared to whichever other ways they might be paraphilic. This leads directly to the first problem with the previous findings: All paraphilias correlate; an AGP man isn’t just more likely to be masochistic, he is more likely to be everything.

Correlation between arousal to a variety of paraphilias in a survey run by the admin of /r/AskAGP. Note how AGP correlates with everything from swinging to pee fetish to furryism to incest. (Beware – do not take this data too seriously; see the rest of the post for more details.)

This is called the general factor of paraphilia (GFP), and it complicates any attempts at reading anything into correlations between AGP and masochism; obviously they’re going to correlate, since everything correlates, but that’s not exactly theoretically interesting.

The general factor of paraphilia is one potential bias, but it is not the only potential bias. There may, for instance, also be community-based effects. If you are examining trans women’s masochism to test the relationship between autogynephilia and masochism, you are assuming that masochism is not related to transsexuality except via autogynephilia. Is that assumption true? Do we know that masochism isn’t confounded with transsexuality in some other way? It seems like quite an unfounded assumption to me; before one starts using transsexuality to study it, one should first establish that this assumption is justified. (I’ve tried to see if masochism predicts gender issues after controlling for AGP in my surveys, and I’ve gotten mixed results so far. Needs more research.)

Or consider another option: founder effects. Suppose that some community of AGPs is founded by a masochist. In that case, they might share masochistic AGP material, and this would influence which sorts of other members end up joining. Or how about sociological effects. Suppose that males tend to be embarrassed about their AGP. Generally, that may make them avoid getting associated with it, avoid communities and such – except, if you’re a masochist, the embarrassment is in some ways a plus. So masochistic AGPs might become more likely to join AGP communities. These factors are of course speculative, but the point is, you’re making a lot of assumptions when examining AGP communities.

A direct test of the AGP/masochism relationship

The trouble with the general factor of paraphilia can be solved by looking into not just masochism, but also other paraphilias, and examining whether masochism correlates with AGP above and beyond what one would expect paraphilias to correlate generally. The other biases mentioned are essentially biases due to selection, proxies, stereotypes, and such; they can be straightforwardly solved by changing the recruitment methods. Namely, instead of recruiting an AGP sample and a non-AGP sample and comparing them for masochism, one recruits a single sample that contains both AGPs and non-AGPs and examines them.

This is how we collected the data described in the blog post Controlling for the general factor of paraphilia. We selected some items assessing not-inherently-masochistic autogynephilia (using some of the top fantasies mentioned in the qualitative survey), masochism, masochistic autogynephilia (mainly forced feminization), and a variety of paraphilias for controlling for the GFP. We then posted this on /r/SampleSize using the title “Male Sexuality Survey”, and got a dataset with a large number of responses. I’ve analyzed this dataset in a bunch of ways, and they all tended to yield no real connection between autogynephilia and masochism. The blog post linked before attempts to examine things at the level of individual items, but I’ve also gotten similar results with more abstract models.

Mysterious results

However… there is something fishy about the data. Consider this matrix from the analysis:

Correlations between sexual interest items after subtracting off the GFP. See Controlling for the general factor of paraphilia for details on how this was computed.

Notice how the correlation between autogynephilia and masochism is negative, -0.09. This is a pretty small effect, and so one probably shouldn’t make too much of it on its own, especially since the method gets kind of fiddly. (Some of my other analysis got a statistically insignificant positive effect, 0.05.) But it’s still odd. And before controlling for the general factor, the correlation between autogynephilia and masochism was just 0.1; this too is odd, as usually I get correlations between them of 0.2.

This isn’t the only odd part of the data. Consider for instance the distribution of answers to the autogynephilia item:

Distribution of responses by sexual orientation. Attraction to men/women was dichotomoized based on rating the given gender with 2+ on a 0-4 scale, so some of the monosexual men were monoflexible rather than strictly monosexual.

This is an incredibly high affirmative response rate compared to the general population, which appears to be more like 3%-15% (see e.g. Lawrence’s review for some general population estimates). Most of this effect is due to reddit being unusually paraphilic; in my experience, reddit and other eccentric internet samples often end up with autogynephilia rates around 40%-50%. But the affirmative responses here are far higher than that, so it seems that something more is going on.

A final piece of fishiness comes in the survey comments. Many people responded that they found the questions weird, overly focused on masochism or on imagining being a woman. It is not very surprising that they felt that way, considering that about half the questions were focused on these themes or on attraction to trans women and crossdressers.

Berkson’s paradox

To understand the problems with this fishiness, let’s switch to an entirely different set of questions: Why are handsome men jerks? Why don’t standardized test scores predict university performance great? Why are movies based on good books usually bad? Why are smart students less athletic? Why do taller NBA players not perform better at basketball?

Stolen slide illustrating Berkson’s paradox. By selecting a subset of the population, you introduce a negative correlation between the variables you select on.

A huge amount of the questions in the survey were based on autogynephilia and/or masochism. Quite plausibly, men who were neither autogynephilic nor masochistic found the survey to be strangely obsessed with these topics, and therefore chose to leave. If this happened, we’d expect to get a negative correlation between autogynephilia and masochism, at least after controlling for the GFP. If this happened sufficiently strongly, we might even have masked a positive correlation between AGP and masochism.

New data, new analysis

I informed the creator of the /r/AskAGP subreddit about this problem, and we went to designing a survey that had few AGP/masochistic items, and plenty of paraphilic and normophilic items, to get rid of these selection effects. We used the same method for collecting the data as before, posting it on /r/SampleSize. You can compare the correlation matrices here to see the overall survey content and results structure.

I proceeded as in my Controlling for the general factor of paraphilia post, and identified a varied set of paraphilias to use for estimating the GFP:

Correlation matrix for paraphilias in the second survey.

I can fit a general factor model to this. The general factor model estimates, for each paraphilia, how much it “generally tends to correlate” with other paraphilias. Using the general factor model, I can then decompose the correlation matrix into the part that is due to the general factor, and the differences in predictions from the general factor:

Decomposition of the correlation matrix.

It is the latter residual correlation matrix that is interesting. It tells us the correlations between paraphilias beyond the general pattern of them all being correlated. To interpret it, let’s zoom in and look at the labels:

Results from subtracting off the general factor of paraphilia.

There was no correlation between the autogynephilia item (“Imagining being a woman and masturbating by rubbing your clitoris”) and the masochism item (“Having your partner call you slurs or insults”). Autogynephilia did seem to have a negative residual correlation with some times related to sexual dominance; this suggests that autogynephiles might be less sexually dominant after taking general paraphilias into account. One might naively take this to mean that there is a connection between autogynephilia and submissiveness/masochism, but this is not so; sexual dominance is not the opposite of sexual submission, but instead often positively correlated.

The autogynephilia item used here is a kind of eccentric item optimized to test a hypothesis I had. This hypothesis has since run into some empirical problems and now I have some theoretical concerns about it. Therefore, I thought I should test the robustness by replacing it with other more-standard autogynephilia items, namely “Imagining being a woman and having sex with another person” or “Wearing sexy panties and a bra”:

Robustness check; I tried experimenting with the full set of items, still controlling for the GFP in similar ways to before. (There was one difference to the way I controlled here in this robustness check; see the end of the post for technical details.)

As you can see, it remains robust to choice of item. Items intended to examine masochistic feminization and emasculation did correlate with masochism, but items intended to examine purer autogynephilia did not, after controlling for the general factor of paraphilia. In fact I was a bit surprised here, I had thought that transvestism would correlate; it might be good to perform more research on this.

But overall, my conclusion is, while the initial investigation had its problems, it still appears to me that autogynephilia is not particularly correlated with masochism/submission. Its apparent negative residual correlation with dominance might perhaps explain perceptions that autogynephilia is correlated with masochism/submission, because autogynephilia is associated with non-dominant paraphilias.

Now for some technical details. The method I used to control for the general factor of paraphilia works by minimizing the size of the residual correlations; see the linked blog post for details. However, this becomes a problem when I use many items with similar content at the same time, such as in my final image that showed all the AGP/MEF items; because then instead of controlling for the GFP, it might end up controlling for the specific items content related to those. To address this problem, in the final image I avoided minimizing the correlations between the AGP/masochism/MEF items, and instead just minimized their correlations with the rest of the items that were selected.

More formally, here is the code for the loss function:

# p x p correlation matrix for the paraphilia data
corrs = np.corrcoef(data.T)
# data is an n x p matrix containing n responses on p variables

# we are concerned that some of the beginning items have excessive content overlap,
# and that their shared variance should therefore not be used to estimate the GFP.
# to avoid this, we skip some of the items. this variable contains the
# number of items to skip; in this case 3 AGP + 3 masochism + 3 MEF = 9 items
head = 9

def loss_fn(loadings):
    # matrix containing the correlation due to the general factor
    gfp = loadings @ loadings.T
    # 'residual' matrix after controlling for the general factor
    residual = corrs - gfp
    # we want to minimize the off-diagonal elements of the residual matrix, i.e. this:
    err = (1 - np.eye(len(items))) * np.abs(residual)
    # I use an L1 loss to favor sparsity, but I also add a bit of L2 to improve convergence
    err = err + 0.01 * err**2
    # we drop the first few associations to avoid the previously mentioned problem of content overlap
    return np.sum(err[head:,:])

I optimize this function to get the general factor loadings.

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