It’s been a while since I’ve got my teeth into a close reading of a paper, and this week has gifted me with a doozy: Pornography actresses: An assessment of the damaged goods hypothesis. The study was authored by psychology academics and former porn performer turned founder of a healthcare programme for porn performers.
The paper aimed to test the veracity of a set of beliefs surrounding women in porn. These attitudes were gleaned from a studies into attitudes towards porngraphy, finding that those with a negative attitude towards porn tended to believe that porn performers had low self-esteem, were drug addicts and had experienced sexual abuse in childhood. These attitudes, the authors point out, are also apparent in anti-porn feminist writing, which is backed up with little evidence. The authors also point out the distinct lack of quantitative research into the women in porn themselves, drawing attention to the fact that while there’s a couple of qualitative studies about why women get into acting in porn, there’s nothing quantitative.
So they decided to examine quality of life, self-esteem, attitudes towards sex, sexual behaviour and drug use in a sample of porn actresses. The headline findings were rather interesting: it turns out that the stereotypes aren’t true. Comparing porn actresses to a sample of women matched by age, marital status and ethnicity, they found that the porn actresses actually had higher self-esteem than comparable women, were more likely to feel positive, felt they had better social support and were more spiritual. There was no difference in current drug use, apart from marijuana (porn actresses were more likely to get high), although the porn actresses reported more drug use in the past. There was also no difference in incidence of sexual abuse in childhood. And finally, the porn actresses reported greater levels of sexual satisfaction, were more likely to identify as bisexual, enjoyed sex more, were having more sex than the women who weren’t in porn (sex as part of their work was not counted: this was entirely extracurricular sex), were more likely to be concerned about catching an STI, and had started having sex a little earlier.
Does this mean that the stereotypes about women in porn coming from some feminists and the general population can finally be put to bed? I’ll get back to that after we’ve had a little look through a few criticisms of the paper.
The study used a clever sampling method for accessing porn actresses–a task which is usually rather difficult and goes some way to explaining why there is little, if any, quantitative examination of porn performers’ lives. The porn industry requires that performers have regular STI tests, particularly for HIV, so participants were recruited from a clinic where they were tested. The comparison group were recruited from a college and an airport (annoyingly, it’s not specified whether this airport and university were also in California). While it is not ideal that the porn actresses were all recruited from Los Angeles, which might not be representative and generalisable to the entire population of porn performers, it is not as bad as one might think: the authors were testing whether stereotypes about women in porn were true. The majority of porn distributed in the west comes from southern California, which shapes discussion and thought about porn by western people as about this group of porn actresses. They’re not entirely representative of everyone in porn, but they’re certainly the people about whom the stereotypes are formed, and therefore this is a reasonable sample to draw from.
Since the authors were also concerned about stereotypes about women in porn, it’s also not a problem that men were not included in the study. The “damaged goods” stereotype that was being examined exists only about women!
One commenter on Jezebel (yes, I looked at a Jez discussion thread. Yes, I’m traumatised. No, I don’t ever want to go back to Jez ever again) points out that the sample of porn actresses may differ from average in being slightly older and having worked in the industry for longer. However, this isn’t actually backed up by a link to where she got this information from, and her comment is preceded by “I believe”. This might be true, but I haven’t been able to find this information anywhere, so can’t comment on whether this is a problem for sampling. However, it is important to note that the women included in this study were those who were participating in above-board porn which was compliant with the regulations, and there might be differences in women who are working in grey or black market porn. Unfortunately, these women are even harder to access and study.
Ultimately, this was an impressively large sample for such a difficult-to-access group: data from 177 porn actresses were collected (and, of course, 177 women in the comparison group). Of course, in any quantitative study, no sample is going to be completely representative, but as far as things go, this was reasonably strong.
This study used a matched pair design: data collected from each porn actress was matched with data collected from a woman the same age, ethnicity and marital status. This is a fairly robust design when comparing groups, and means that differences cannot be attributed to these variables. I am even more impressed at the sample size with the researchers using this type of design, as it’s notoriously difficult to collect data for these designs, being massively time- and resource-intensive.
I have beef with the matching criteria, though. While the authors were right in selecting these, particularly as their sample of porn actresses were far more likely to be single than the general population, there’s an important thing missing that wasn’t measured at all and probably should have been controlled for. Socioeconomic status–class–was never measured, so we don’t know at all whether the porn actresses were better-off or worse-off than the comparison group, and if so, whether it was this that was the cause of their general feeling a bit better about life. Perhaps a way of establishing a better comparison group would be to compare porn actresses with TV or film actresses of the same age, ethnicity and marital status. This would likely control for a lot of the noise, although it would be an absolute arse to research.
Rather irritatingly, the authors never mentioned if they asked the women in the comparison group if they had ever worked in porn (or, indeed, if they were currently porn actresses who happened to be at college or at an airport that day). Since the likelihood of them being porn actresses is fairly low, this probably doesn’t pose much of a problem, I’m just a pedant.
Feel free to skip this bit, as it will get a little technical, and is mostly minor statistical nitpicking. The biggest statistical elephant in the room is that this study ran a lot of statistical tests. A metric fuckton, to use the accepted statistical term. The researchers conducted an awful lot of T-tests, which is a statistical test used to check if one thing significantly differs from another: in this case, whether porn actresses differed significantly from women who weren’t porn actresses on number of sexual partners, or alcohol use, or any of the other eleventy bazillion variables which were being measured.
When one conducts a metric fuckton of statistical tests, one increases the likelihood of encountering a Type I error: a “false positive”. Purely by chance, one of the tests came up as significant, when in fact there isn’t really a difference there. This can be controlled for, although the authors didn’t. Luckily, there was enough data present for me to do this task for them. I did a Bonferroni correction, where the threshold for significance is revised based on how many tests are being performed. It’s pretty easy to do. You take the generally-accepted significance threshold, which is p=0.05 (or, a 5% probability that the results are entirely down to chance and you’re seeing an effect that isn’t really there), and divide it by the number of tests performed (in this study, 19 t-tests were performed). So, the significance threshold for the tests should actually be p=0.0026.
All of the p-values reported came up as less than 0.001, which means they’re still significant even with the Bonferroni correction, with the exception of sexual satisfaction, positive feelings and social support. However, enjoyment of sex was still significant, so it looks like our porn actress sample were enjoying sex significantly more than the non-porn actress sample anyway.
What wasn’t examined (and I wish it had been)
I’ve already mentioned how I wished the authors had controlled for class, but there’s a few more things I’d love to have seen addressed in this paper. Firstly, how the variables related to each other. Given that the porn actresses had had a lot more sex than those who weren’t in porn, could this be the reason they seem generally happier and with higher self-esteem? I have no idea, because the authors didn’t check this, and it would certainly be interesting to find out if this was the driving factor, or even just mediated the relationship.
The other thing missing, I feel, was the type of porn the women were performing in, and how that related to the variables. Were the participants who identified as bisexual more likely to be appearing in lesbian or bisexual porn? Do certain types of porn affect the self-esteem of the performers? Again, no fucking idea, I wish it had been measured, and I seriously hope future research addresses such questions.
Feel free to add more interesting questions you’d like to see addressed in the comments!
So what does it all mean?
Ultimately, from a single study, we can never conclude anything concrete, but it is a good thing to see these questions being addressed systematically, and I hope that it leads to future research. Too often, the experiences of those involved in porn or sex work are ignored, and it is genuinely refreshing to see research attempting to examine their experiences and feelings. This study provides a foundation for further examination and to build upon its flaws so we can better understand what it’s like for women in porn and replace the stereotypes with solid evidence.