Dungeons and Genders
Analysis of survey data concerning gender identity within the TTRPG community
Anyone that has been around the tabletop RPG community online will very quickly notice that there are a lot of trans people around. Today I’d like to share some survey statistics I’ve collected on how many trans people there are, why they gravitate to this hobby, as well as some other notes on various issues of representation.
1. Abstract
Among the population surveyed (several mostly online TTRPG communities), 69 ± 3% identify as cis men, 6.6±1.6% as cis women, 14.8±2.3% as trans women, 1.7±0.9% as trans men, and 9.2±1.9% as nonbinary.
Gender identification did not significantly affect the interests of the respondents in the various aspects of the hobby. This has implications on several theories from other research attempting to explain relative underrepresentation of women in the hobby.
Most popular interest and the most popular reason for getting into the hobby was friends. 88±2% of the population seems to share this interest, and 39±3% indicate it as the main original reason for getting into the hobby. This heavily implies a presence of strong network effects within the TTRPG community.
TTRPG community appears to have a lower incidence of gender-based discrimination than the overall society. This effect is very likely present for cis women (probability 0.954) and trans women (probability 0.9991), and fairly likely present for non-binary people (probability 0.84)
Amenability to playing trans characters seems to be highest in non-binary people (82±8%), followed by trans people and cis women (49±8% and 56±12% respectively), followed by cis men (27±3%). Most common reasons for not wanting to play a trans character were lack of interest in gender topics and not knowing enough to portray something other than a harmful stereotype, though the reasons were not analyzed statistically.
Artifacts of representation can be best explained by a combination of network effects and a desire for escapism and/or exploration of gender topics among trans people.
Using a binary question (male/female) for the gender identification of respondents on surveys is bad because it can conceal important trends within the dataset
2. Structure
This article is broadly structured as a scientific paper, with some changes that I believe significantly improve the readability of the format:
Methodology was moved into Appendix A (survey details) and B (data analysis), instead of being stuck in the middle of the text; It is a rather boring read, and would probably be only of interest to statistics nerds, actual sociology scientists, and people trying to work with this data in the future.
There is no section discussing prior research in the field; Instead, I discuss various sources when they become relevant to discussing some section of the analyzed data. This way relevancy of those sources is immediately contextualized, and we skip on unneeded page count.
Similarly, there will be no section explicitly discussing the scientific relevancy or historic background of this study; I consider such things to be a waste of everyone’s time, as pretty much anyone who cares enough about the subject to read this paper would already know why the data presented here is interesting. Failing that, my comments on some of the commonly cited theories attempting to explain the underrepresentation of women should serve the same purpose.
3. Basic terminology
Before we get into the thick of it, let’s clear up some basic terminology, and define the core concepts from the ground up. There are many ways to do this; I will define them in a way that I consider to be the most widely used, and do my best to consistently refer to the corresponding concepts by their assigned terms within the text of the paper.
Sex is a set of biological characteristics (most notably reproductive organs, but also the type of produced gametes, chromosomes, secondary sexual characteristics and so on) belonging to a given individual in a species. In common parlance, sex is treated as binary (female / male), but this is not so. Instead, it is a bimodal spectrum: there are two categories, with the majority of people falling into one of them, but every individual characteristic having exceptions that can be more or less common. People can lack secondary sexual characteristics, be sterile, have more or fewer chromosomes, and even have both ovarian and testicular tissue; there is, in fact, a theoretical possibility for self-fertilisation in humans, though best as I know no cases have ever been recorded.
Gender is a set of social characteristics - such as the style of dress, mannerisms, social roles, and so on - being expressed by a given individual in human society. Gender is associated with sex, and is in common parlance often treated as synonymous, but it is not the same thing. There is no biological reason why men have to wear pants and women have to wear dresses. Just like sex, gender is composed of several fuzzy clusters, which are in turn composed of many logically independent properties. In the modern anglophone culture, this results in two genders (also typically labeled male and female), though other cultures have historically had additional clearly distinguishable clusters, aka more genders. The concept of gender can be split into several parts - gender expression, gender identity, and gender roles.
Gender expression refers to all the gender-coded characteristics which are outwardly expressed by an individual - i.e. everything that observers can see. This includes style of dress, hairstyle, manner of speech, body language, posture, walking manner, and even more “biological” properties - such as breast size, visible musculature, height, facial structure, bodily proportions, and so on.
Gender identity is a given person’s internal understanding of their own gender, specifically what label they assign to themselves, as well as what gender expression they desire to have. Distinction is critical in this case: someone can identify as gender A but express as gender B, due to it being easier, wanting to avoid societal backlash, or other reasons. You can analogize this to a name: gender expression is how other people call you, while gender identity is the name you use inside of your own head.
Gender role is a set of societal expectations and limitations placed upon people of a given gender expression or identity. For example, when your family asks you why you are not yet married, they are asking why you do not fit the typical gender role of your society, which involves being married.
Of course, these concepts are “leaky” - in many situations it is impossible to cleanly separate them from one another. For example, when you fill out a form with a gender option, that action happens at an intersection of gender expression and gender identity; when your family asks you about having children, that is an intersection of gender roles and sex. Imagine it as two pieces of candy glued together: they are clearly individual objects, but it is hard to separate them at the boundary.
People do not come up with their gender in a vacuum. Instead, this is an ongoing process throughout their entire lives. For analysis purposes, we can split it into several stages:
After birth, parents of the child look at the kid, and, based on what they see, mentally assign them into one of two categories - “boy” or “girl”. This is what is somewhat confusingly termed “gender assignment”; it is sometimes followed by genital surgery to more closely match their assigned sex (due to the aforementioned links between sex and gender). This practice is controversial.
Parents raise and socialize the child as their assigned gender. This includes different decisions made on their clothing, education, suggested hobbies, toys, activities, discipline, and so on.
As the child grows up, they absorb this socialization. This naturally does two things: first of all, it shapes their identity in accordance with the gender roles of the surrounding society, and secondly, it implicitly teaches them what those gender roles are. When that child grows up and gets children of their own, they will naturally pass this on to the next generation. In this way, gender roles can perpetuate themselves over a long time.
Some people chafe against the ideas of gender imposed on them by the wider society, and, for whatever reason, have a preference towards either non-binary (as in: third choice) gender expression, or towards the gender expression of the gender they were not assigned at birth. In the former case, I would call them “non-binary”; in the latter case, trans. Trans men desire a male gender expression, while trans women a female one.
Some people additionally wish to perform some amount of bodily modification. This is more common in trans people than in non-binary people; exact frequencies are not relevant to this paper.
Transition or “gender transition” is the process of either changing one’s gender expression, or performing bodily modifications . When it comes to changing one’s gender expression, this is generally termed “social transition”, whereas more direct modifications are commonly referred to as “medical transition”. Telling other people you are trans as part of a social transition is generally called “coming out”; afterwards, you “are out”. Trans people almost ubiquitously report wanting to transition, and it’s common among non-binary people (page 51, figure 4.8; see also Image 1 below)
Transition is generally associated with medical and social difficulties.
People who are fine with the gender identity assigned to them at birth will be called cis. We thus have five categories that will be used in this paper: cis men, cis women, trans men, trans women, and non-binary people.
4. Survey deficiencies
To answer the various questions around gender identity representation I used a series of surveys sent to various TTRPG-adjacent communities. Methodology of these surveys is described in Appendix A. Before we can get to the data, one important caveat has to be discussed. This study is predicated on the premise that I am analyzing the demographics of the tabletop community as a whole, but, in fact, there are several glaring problems with my surveying approach.
The first and most obvious problem is that all of the surveys were done online. This introduces an obvious sampling bias: only people who are online would be able to respond to the surveys. It is possible - in fact, likely - that offline TTRPG communities are quite different from online TTRPG communities. This is, sadly, unavoidable: I have neither the resources nor the motivation to survey offline. Later in the paper, I will refer to the surveyed population as “the TTRPG community” for simplicity, even though that’s strictly speaking inaccurate.
Second problem has to do with how I have discovered these communities: most of them were suggested by my friends and acquaintances when I asked if they knew any large TTRPG groups. This means it is likely that there is a degree of correlation between the views, beliefs and culture of all these communities, simply due to how acquaintance bubbles work. This problem could have potentially been mitigated by putting more effort into community discovery, but I did not have the motivation to do so. It is hard to estimate to which degree this effect affects the results.
Third problem is related to the very fact that I collect data using surveys. Obviously, only the sorts of people who would want to answer a “gender identity survey” would actually answer it. This can mean that I am introducing an additional bias - respondents may or may not think more about gender identity than the overall TTRPG community, and may or may not be more likely to have non-cis gender identities. I do not see a good way to avoid this problem either.
Fourth potential problem lies in the data analysis - it has been done by me in my free time, and it’s very possible that mistakes were made during the coding or analysis stages. I consider this relatively unlikely, but the possibility must not be discounted altogether.
Fifth problem has to do with me: I am not a trained sociologist. I know a decent amount about statistics, and I think I know a thing or two about surveys, but it is entirely possible that there are unknown unknowns which either harm the plausibility of these results, or that could have improved the quality of the collected data, or have done something else. Additionally, as I am the one doing the study and the one doing the data analysis, this study isn’t double blind: it is possible that I have introduced some personal biases during the analysis or the coding stage. Appendix B has some information on the methods I used to mitigate this effect.
Despite all these problems, I think that this data is well worth reading, though with some amount of healthy skepticism added in.
5. Overall demographics
First of all, let’s discuss key demographic statistics from the population outside of the TTRPG communities.
Majority of people identify as either cis men or cis women; exact proportion differs by country, but hovers around 50/50. Percentage of trans people is similarly inexact, as different surveys with different methodologies report somewhat different numbers; overall, it seems to be somewhere around 0.5% [1], [2], [3]. Out of that, about 2/3 are trans women and 1/3 are trans men; however, some recent evidence may indicate that the underlying proportions are more equal and the unequal ratio reported by other studies was caused by social factors. Non-binary people seem to hover somewhere around 1%.
The TTRPG community appears to be quite different. Based on my data, it is composed of around 69% cis men, 6% cis women, 1.5% trans men, 15% trans women, and 9% non-binary people (see Image 3).
This is a significant difference from the overall population. Let’s make sure this difference could not be caused by sampling size errors. For this, I use Bayesian probability theory to directly analyze our confidence in these results; a quick summary of my statistical methods is presented in Appendix C.
Based on this, we can be very confident that these results are not caused by random chance: we are observing a real effect. Percentage of trans men could plausibly be the same as in the general population, but all other statistics are quite different.
We can thus see that non-binary people are more common in the TTRPG community than the overall population by a factor of 6 to 14, and trans women by a factor of 35 to 60. Cis women, on the other hand, are less common by a factor of ~7. Such a massive difference naturally demands an explanation. In fact, intuitive perception of this statistical irregularity was the original motivation behind this research.
How do other sources of demographic data reflect on this finding? The truth is that it’s very hard to say. Prior research in this field almost always presents a binary male/female question on surveys, thus lumping cis women together with trans women into the same group: this mathematically reduces the perceived difference in representation.
Wizards of the Coast market survey from 2000 reported approximately 20% women.
Survey by James Kittock in 2001 gives 9% women.
Convention data from the same source gives ~20% women.
The Mary Sue, without a source, claims 40% of DnD players are now women.
And so on. Of course, it is impossible to divine wherever 20% women means 18% cis women and 2% trans women, or the reverse.
I will discuss the potential reasons for over-representation of trans and non-binary people and for under-representation of cis women in section 9.
When it comes to the age at which respondents first became interested in TTRPGs, there seems to be a fairly broad distribution between 8 and 25 years, with a mean of 16 years.
For trans people, an additional question was asked regarding the age at which they figured out they were trans; on average this was 20 years (mean 20.3, median 20), or 19 if ignoring data points below 6 or above 30 years of age (mean 19.2, median 19). Age at which trans people became interested in TTRPGs was statistically indistinguishable from that of everyone else (16.08 mean). Among trans people, 75% of them became interested in TTRPGs before finding out they were trans (72% strictly before, 76% before or in the same year).
It is important to contextualize these numbers. In The Report of the 2015 U.S. Transgender Survey we can see two different distributions regarding age of identity discovery (see Image 8). In one of them, question refers specifically to the term “transgender”; in another, to feeling your identity is different from what it is on the birth certificate. We can thus see that even fairly minor differences in how the question is asked can produce very different results when it comes to the exact age of identity discovery. Based on this supplemental data, it seems likely that trans people feel something different quite early on, but the process of finalizing their identity and discovering the terminology necessary to describe it takes longer. Their interest in TTRPGs, chronologically, materializes at some time between these two endpoints.
6. Initial hook & interests
Two of the central questions of the survey had to do with the reasons why the respondents initially became interested in TTRPGs (hereafter “play reasons”) and what aspects of the hobby they enjoy (“interests”). These questions were intended to find regularities in the reasons people get into the hobby.
By looking at the assembled data, a few things become immediately apparent:
Interests and reasons for getting into the hobby are very similar across the board, with only a couple notable deviations.
Friends are the most common reason people get into the hobby by far, followed by liking fantasy and roleplaying.
Friends are also one of the most common reasons people enjoy the hobby, easily competing with storytelling for first place. In comparison, interest in achieving specific objectives hovers around only 40%.
Trans people are significantly more likely than average to come to the hobby due to escapism desires; the mean of the overall distribution is outside of their 95% confidence interval. This separation allows us to be confident this effect is real. Interestingly, they do not seem to stay due to escapism: here, everyone hovers around 50%.
Non-binary individuals are massively more likely to report being interested in achieving concrete objectives and changing the world, at 58% compared to the overall average of 36%. In fact, the difference between their rate and that of trans women (28%) is the single largest difference in rates in this entire dataset. This has puzzled me quite significantly, but some discussions with the people form the community have told me that there is a persistent idea of non-binary people being associated with world domination. Take of that what you will; I assume this to be a statistical artifact.
7. Transgender characters
Next key piece of data from the study concerns transgender characters. Specifically, I wanted to find out whether trans people were more or less amenable to play a character that was also trans than people of other gender identities. Here, trans character was understood to be any character that has dealt with any issues associated with transition or an equivalent, be it explicitly in game or as part of their backstory. Amenability is a willingness to play such a character in the future or the fact of having played them in the past.
My original hypothesis was that trans people would be less likely than average to play trans characters, due to wanting to avoid the related issues out of a sense of escapism. In fact, the opposite can be seen: around 50% of them are amenable to playing a trans character. This rate is fairly similar to the rate among cis women, so in a way, we can say that cis men are the real outlier here. In comparison, non-binary people are overwhelmingly likely to be amenable to playing trans characters.
The question did not explicitly request people who didn’t want to play a trans character to submit a response; nonetheless, a decent number of them submitted a reason beyond “No”. In my view, it would not be appropriate to analyze these responses statistically: because most people did not write a detailed reason, we would be introducing a potential selection bias.
It is still instructive to look at the two most common reasons. Broadly, they were:
A lack of interest in the topics of gender identity
Not wanting to fall into harmful stereotypes, or otherwise lacking key knowledge about the issue
First reason is entirely unsurprising: some people are simply not interested in this topic when it comes to exploring it in the game, even in a very minor way (e.g. including it as part of someone’s backstory). In fact, I myself am like this, and don’t have any intentions to play trans characters. I do not think this is bad: interests, to me, are sacrosanct. If someone doesn’t have an interest, they don’t have it, and that’s that.
Second reason, however, is more interesting: it implies that there is a subset of the community that might be interested in exploring these themes, but that lacks key knowledge. I will touch on this more in a later post when discussing conclusions that could be drawn from this research.
8. Discrimination
Final piece of survey data compared the rates of discrimination within the TTRPG community and outside of it. Four survey questions dealt with this topic. Two of them concerned trans people, and wherever they were “out” to their gaming groups. The other two were about general discrimination on the basis of gender.
There are some caveats concerning these numbers. Similarly to the question about trans characters, some people noted important information beyond a simple “yes” or “no”. For example, a decent number of trans people noted that they haven’t experienced discrimination outside of the TTRPG community due to not being out outside of the TTRPG community. These statistics thus should not be taken as a measure of how widespread discrimination is against trans people who are openly trans.
Similarly, not all trans people are out within the TTRPG community: based on the other two questions, only about 75% of trans people are out to their gaming groups. Among the trans people who are out, about 70% come out immediately, and almost everyone else within a year. This means similar problems with counterfactual discrimination may be present in about a quarter of all cases.
Comparing this to NTDS data (Image 15), we can see that this rate of outness is only comparable to “LGBT friends” (with 82% of trans people reporting that all or most of their LGBT friends know they are trans), and outstrips every other category on record. This implies that the TTRPG community is fairly accepting of trans people overall.
On the other hand, a decent number of trans people report playing in groups that are heavily LGBT. This could indicate the presence of self-segregation, with trans people being much more common in some groups and almost absent in others, making average rates of outness and discrimination no longer informative. This survey was not designed to take this into account, so there is not much that can be done to analyze this possibility.
Finally, it is important to note an obvious sampling bias. People experiencing discrimination should be, all else being equal, more likely to leave the hobby, and thus less likely to respond to my survey. This means that the responses would necessarily be biased in favor of lower rates of discrimination, though it is very difficult to say to what extent.
Nonetheless, this data implies - though with multiple caveats - that the TTRPG community is significantly more accepting than the overall population. It also seems likely that the rate of discrimination could be reduced further, though I have no policy suggestions on this topic.
9. Why the trans gamer?
Skye Kychenthal in their paper “Why the trans programmer?” uses survey data to attempt to answer the question of how many trans people go into software engineering, and why they do so. They were moved to do this for similar reasons as me - anecdotally, there is an idea of trans people disproportionately entering the field. In this section I will try to do the same thing, and try to address some theories that could explain all the various artifacts of representation we have uncovered in this data.
To summarize, we are trying to explain the following four facts:
Trans women are overrepresented by a factor of ~50.
Trans men are either not overrepresented, or only by a factor of 2 or 3.
Cis women are underrepresented by a factor of ~7.
Non-binary people are overrepresented by a factor of ~10.
The primary reason I split cis women and trans women into separate groups is the differing socialization at an early age. Based on our data, trans people do not fully realize they are trans until adolescence: this likely means that at least up until that point, they are undergoing socialization of the gender assigned to them at birth. This, in turn, should be expected to have differing effects on their interests and their social networks.
Many people have previously tried to construct models explaining these facts, especially when it comes to analyzing the underrepresentation of cis women. Here, I will be relying on an overview of the potential reasons why women might be underrepresented in TTRPGs done by John Kim in 2005. He had mentioned five potential causes:
Art & writing: art and writing in TTRPG books can be disparaging to women - e.g. portraying them in skimpily clad clothing, or acting in primarily subordinate and ineffective roles - which might turn women away from the game.
Genre: genre of the popular TTRPGs may appeal more to men than to women, for a variety of reasons.
Social: various social effects can prevent women from joining, such as discrimination or lack of network connections that would pull them into the game.
Rules focus: women, for whatever reason, might prefer less complex rules systems, and thus be turned off from relatively complex TTRPGs.
Violence: similarly, women might be turned off by a heavy focus on violence that most TTRPGs exhibit.
Among these five potential reasons, he considered Art & writing and the focus on violence to be the most significant.
My survey was not designed to analyze the art of TTRPGs, their genres, or the amount of violence: as such, it offers little direct evidence one way or another. We can see that cis women are mildly more likely to be attracted to the hobby via the various media: this is weak evidence that art of the TTRPGs isn’t a turn off. Furthermore, we can see a very large overlap in all interest types between groups, which is weak evidence that everyone more or less wants the same thing; however, crucial differences may be obscured by a very broad interest coding scheme.
Survey does, however, provide crucial data on the question of rules focus. Based on the data, women are, at worst, slightly less interested in the “crunchy” parts of the TTRPGs as everyone else; and it is not unlikely that their interest is pretty much the same. This means that rules focus certainly cannot explain the massive underrepresentation of cis women.
When it comes to interest in violence, we can use data from genre preferences in video games to inform our thinking on this matter. Based on Quantic Foundry data, the percentage of women varies by genre quite significantly. In games most similar to TTRPGs, such as MMORPGs and Japanese RPGs, this percentage hovers around 30%; it only reaches 7% when you go down to first person shooters. While one may quibble over how much violence there is in TTRPGs, I think it is undeniable that there is less of it than in first person shooters. Violence may be a factor in the disparate gender statistics, but it is fairly clear that it cannot explain the disparity alone: there must be some additional factor pushing the representation down from the 30% we see in MMORPGs.
Can the 30% here be confounded by the same error I mentioned before - that cis women and trans women are lumped into the same group? This seems unlikely: for example, this survey of World of Warcraft players reported 36% cis women and 3% trans women among the survey respondents.
How about harassment? John Kim notes that logically, this could not explain the disparity: even if harassment was present and significant, it would not explain how the field initially became male-dominated, or why the natural influx and outflux of players would not equalize the field over time. Furthermore, based on my data, TTRPG community has less discrimination than the overarching society. Rates of discrimination are not zero by any means, but it seems like a stretch to assume that discrimination would push people out of the field if the out has more of it. Of course, it is possible that there are other fields - such as videogames - where discrimination can be even less prevalent, due to, for example, not seeing the faces of other players.
This finally leaves network effects. Based on the survey data, friends are the single biggest hook for getting people into the hobby. Furthermore, they are also the largest interest for people staying within the hobby. I believe that this is sufficient to conclude that network effects are significant within the TTRPG community. This is logical: TTRPGs are a group hobby, and cannot be played alone. This stands in stark contrast to videogames - even MMORPGs - where it is very easy to play alone, and crucially to start playing alone before finding friends within the game.
I believe that these effects are primarily responsible for the weird representation effects we observe here. In the current cultural climate, there is a lot of gender segregation in friendships: men mostly have male friends, and women mostly have female friends, with various sources stating that only around 25-30% of people have best friends of the opposite gender (1, 2). This means that statistically, when inviting friends to play TTRPGs, men will mostly invite other men to play, preserving a gender disparity even if we assume that no other harmful social effects are present. If we imagine that on top of this, men are twice as likely to invite their male friends than female friends (e.g. due to stereotypes about who enjoys this sort of hobby), and women are twice as likely to reject the offer (e.g. due to stereotypes about how much they will enjoy playing, or fears of harassment), this could almost entirely explain the relative underrepresentation of cis women. Of course, I cannot confirm or disconfirm the existence of these hypothetical stereotype effects - but it should be obvious how network effects would push the representation fo cis women down.
When it comes to trans women, in my mind the most sensible theory explaining their relative overrepresentation consists of four factors:
Initial male socialization, resulting in them not having harmful stereotypes about the hobby being “not for them”.
Childhood male friendship circle making network effects work in their favor.
Desire for escapism, as evidenced by the high and statistically significant reported escapism play reason, as well as a potential desire to explore gender topics.
High overall acceptance of trans people within the TTRPG community, potentially due to LGBT people often playing with other LGBT people. This may also introduce additional LGBT-specific network effects.
It is notable that the former two factors would be present for any stereotypically “male” game, such as MMORPGs. Despite this, if we look at the survey data for World of Warcraft, we can see that only 3% of players are trans, split about equally between trans men and trans women. It is hard to say whether MMORPGs are likewise accepting of LGBT people, but I consider it likely. This would imply that escapism and exploration of gender topics are a very significant source of draw to TTRPGs, increasing the fraction of trans people by more than a factor of magnitude.
Among these four theoretical factors, trans men should share the latter two, but not the former ones: this may explain only mild relative overrepresentation, as the various pressures more or less cancel out.
Non-binary people’s situation is complicated: by definition, they may belong to either of the two primary childhood socialization clusters. It also appears that they are much more interested in exploring gender-associated topics than pretty much anyone else, and TTRPGs provide a safe space for these sorts of experiments. Overall, it is hard to conclude anything with a great degree of confidence.
10. Conclusions
Overall, I believe that this survey data provides a unique look into the gender demographics of the TTRPG community, as well as the various associated topics. Conclusions drawn from this data allow us to discard several common theories attempting to explain the relative underrepresentation of women in the TTRPG community, and provide insight into the relative overrepresentation of trans people. This data should serve to improve decision making when it comes to various topics surrounding gender, such as when planning future content by TTRPG publishers. Furthermore, I believe this data strongly indicates that limiting the questions of gender identity to a binary male/female response on surveys may conceal a lot of very important behaviors in the dataset.
In the future, I may write a post with my own thoughts concerning various lessons that could be drawn from this data. If you are looking for other posts on my blog, check out this list of all other posts, and if you enjoy what I write, you can subscribe to receive updates by email:
Thumbnail art is based on Textured Dungeon Map 005, licensed under Creative Commons Attribution-Noncommercial-Share Alike 2.5 Canada License, as well as Icecat Anime Girl, in public domain, and OSX-tan, licensed under Creative Commons Attribution-Share Alike 3.0 Unported, and is itself licensed out to the general public under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
Appendix A: Survey methodology
Surveys were done via google forms, with each one including a title, an introductory paragraph, and nine questions.
The title of the survey was “Gender identity in the tabletop RPG community”.
Introductory paragraph stated “There is a lack of proper demographic analysis regarding the gender identity of the tabletop RPG community in the openly available sources. This makes it hard to make informed decisions regarding the topic, for example when it comes to representation. This survey aims to correct this data gap, and to analyze both the relative prevalence of trans people in the tabletop RPG community, as well as the common reasons for getting into the hobby.”
Survey questions were, in order:
Pick the closest label to your gender identity; cis means you are not trans
This was a choice question, with options “Cis male”, “Cis female”, “Trans mtf”, “Trans ftm”, and a write-in other choice.
Surveys that were sent out later included a “Non-binary” option, because many write-ins previously wrote something to that effect.
At what age did you get into TTRPGs (Tabletop RPGs)?
If trans, at what approximate age did you figure out you were trans? Leave blank if not trans.
What made you start playing / attracted you to the hobby?
This is referred to as “play reason” within this paper.
(Select all that apply) What are the main things you enjoy in TTRPGs?
This question was designed based on the responses of the /pfg/ community, and so was not included in their survey. During analysis of this question, data from /pfg/ was thus not used, on account of it not existing. The reason this question was necessary was that the majority of answers people provided to the previous question did not provide data regarding their current interests in the hobby, which was the original intention of that question.
This is referred to as “interest” within this paper.
If trans, does your gaming group know you are trans (i.e. are you out to them)?
If trans, how soon did you come out to your gaming group (e.g. immediately, after a month, after X years)? How difficult was this process?
Have you ever played a trans character or intend to play one in the future? Details are appreciated.
Have you experienced any form of discrimination based on your gender identity within the TTRPG community?
Have you experienced any form of discrimination based on your gender identity outside of the TTRPG community?
Last two questions were meant to gauge the degree of discrimination in the TTRPG community relative to the wider world.
The number of questions was kept low to decrease the mental drain on the respondents when answering the survey; I considered it likely that more questions would lead to people responding with curt uninformative answers, decreasing the quality of the collected data, or would lead to them choosing not to submit a response at all.
In order to have a broad range of data sources, surveys were sent to the following communities:
/pfg/ “After Dark” discord server [/pfg/], aka “The Cabal”, with 108 members. Originally an offshoot of the /tg/ (traditional games) board on 4chan, the server has since distanced itself from the board due to the latter becoming increasingly toxic.
Kuudes Rinki [Oulu], an RPG community from Oulu, Finland, with 521 members.
Helsinki tabletop association [Helsinki] (Helsingin pöytäroolipelaajat, literally “Helsinki table role players”) from Helsinki, Finland, with 341 members.
Vaush’s Praxis Emporium [Vaush], a left-wing political discord, with circa 10000 members. Survey was submitted to a dedicated tabletop channel.
r/Rpg [/r/rpg], a subreddit dedicated to tabletop roleplaying games, with circa 1.5 million subscribers.
5th edition DnD discord server [/r/dndnext], associated with /r/dndnext subreddit, with 3460 members, out of whom about 1/10th are active.
Quests and Stuff, a discord server made to discuss quests on sufficient velocity, with 151 members.
Rat Catchers [Rat Catchers], central discord for Warhammer Fantasy Roleplay tabletop RPG, with several thousand members.
Square brackets denote the label used for data from this community on the various graphs.
Each of the submissions was accompanied by a text message inviting people from the relevant community to fill out the survey. Number of responses to each survey was checked each day, and the data was analyzed once new responses from all communities had stopped coming in.
Two of the responses - one from /pfg/ and one from Rat Catchers - have been removed from the dataset due to failing to meaningfully address the questions presented on the form.
Because this survey data was meant to analyze the TTRPG community as a whole, it would be valid to ask wherever the survey should have included an additional question to separate the responses of people who mainly play online from those who mainly play “in real life”. For example, Skye Kychenthal in their paper “Why the trans programmer?” used the following method:
To gauge the respondent’s preference for online trans communities, the question “how experienced are you with catgirls?” was posed to which 80.5% of respondents were “kinda” or “very” experienced with cat-girls.
Ultimately, I have decided that the data would be heavily biased towards online communities simply due to how I conducted the surveying. Such a question would thus not provide a lot of information, and I decided to err on the side of making the survey shorter.
Appendix B: Data analysis
Google forms automatically collects survey data on separate google sheets. Once the data collection stage was over, I copy-pasted this data onto a new, central sheet, in order to code it and perform data analysis. Coding mostly involved converting the data into a binary form (1 for belonging to a category, 0 for not) or a numeric form (e.g. ages).
Question of gender identity was coded into five mutually exclusive categories: cis male, cis female, trans mtf, trans ftm, and non-binary. Responses were classified according to the category they were most similar to; this meant that most unconventional identities (genderqueer, agender, etc) were classified as non-binary. To facilitate mathematical analysis, five new columns were added to the sheet (one for each gender identity class), with responses being assigned 1 in the column if they fit that category and 0 if they did not.
Questions of age were converted to a numeric form and rounded down: e.g. “in my 30s” was converted to 30, and “25-28” was converted to 25.
Question of play reason was split into 8 different categories, using the same coding method as the question of gender identity. These categories were labeled “Friends”, “Family”, “Escapism”, “Roleplaying”, “Fantasy”, “Media”, “Mechanics” and ”Other”. Categories were not treated as mutually exclusive, though in practice most responses only provided enough information for a single category.
Categories of “friends” and “family” are self-explanatory: they refer to cases where someone is brought into the hobby via their friend circle or family connections. Friends of the family (e.g. “my mom’s friends”) were classified as both.
“Escapism” refers to the cases where the person entered the hobby as a deliberate attempt at escapism: to distract themselves from various unpleasant things in their life. Mostly, people were classified into this category if they mentioned escapism by name.
“Roleplaying” was a category for all play reasons that seemed related to a desire to roleplay.
“Fantasy” was a fairly broad category related to various types of fantasizing, such as explicit mentions of wanting to be a part of a fantasy world.
“Media” category was for books, films, podcasts, webnovels or other media sources which could introduce someone to TTRPGs.
“Mechanics” referred to any kind of interest in the more mechanical, game-y side of TTRPGs.
“Other” was for everything else. Ultimately, this category was discarded due to having too few responses to be informative.
Videogames were scored as 1 in Fantasy and 1 in Mechanics. Finding TTRPG material in a store was rated as 1 in Media and 1 in Mechanics. Mentions of writing or worldbuilding were scored as 1 in Roleplaying and 1 in Fantasy. Everything else was classified into the best fitting categories.
Question of interests was also split into 8 categories, labeled “Friends”, “Escapism”, “Novelty”, “Roleplaying”, “Mechanics”, “Objectives”, “Storytelling” and “Other”, with a fairly obvious correspondence to the question answers.
Question of trans outness was coded as 1 for unequivocal agreement (Answers such as “Yes”, “Yup”, “I am open about it”), as 0 for unequivocal disagreement (“No”, “Hell no”, “Not yet”), and as 0.5 for partial answers (“Some of them”, “One group knows, other doesn’t”). It was left blank for people who have provided no answer: this allowed those data points to be filtered out during the analysis.
Question of how quickly trans people were out was split into two categories: immediately and within 1 year. If a trans individual seemed to indicate they weren’t out within 1 year, they were coded as 0 in both columns; those who were out within a year but not immediately were coded as 1 in the year column and 0 in the immediately column, and those who were out immediately were coded as 1 in both columns.
Question of trans characters was coded as 1 if the respondent mentioned playing a trans character or indicated a solid desire to play one in the future. If they indicated they haven’t played a trans character and had no interest in this topic, for whatever reason, their response was coded as 0. A few responses were on the edge between these two categories, and were coded as 0.3, 0.5 or 0.7, depending on the strength of the exhibited sentiment.
Questions of prejudice were coded as 1 if the respondent indicated agreement (“Yes”, “Ya”, “Yuup”), as 0 if they indicated disagreement (“No”, “Not directly”, “nope”), and as 0.3 if they indicated a very minor level of prejudice (“Very little”, “For the most part no”). If the respondent indicated prejudice was not directed at them (“I haven’t received any, but I have seen it aimed at others”) then this was not counted: this is done to avoid potential double-counting of incidents (e.g. if 10 people see 1 incidence of prejudice this would inflate the rate by a factor of 10).
Because coding was performed by me, the same person who collected the data and performed the rest of the study, there is an obvious concern that coding of answers into groups may have been biased by my own thinking. In order to mitigate this problem, I used an imperfect blinding method. Coding was performed one question after another, instead of on a per-person basis, with previous questions kept scrolled well outside of the screen. By the time I was back to coding the answers of the first respondent, I would have forgotten what they had answered on any of the previous questions, thus mitigating the potential bias.
Once coding was finished, I used a python script to pull data from Google Sheets and to draw the statistical plots seen in this paper.
Appendix C: Bayesian statistics
In this paper I utilize Bayesian statistics to derive many crucial parameters of interest - such as the percentage representations of the various groups, their relative interests in various aspects of the hobby, and so on - based on the survey data. Unfortunately, many people don’t know what Bayesian statistics are, so the graphs might seem somewhat arcane.
The core idea of Bayesian probability theory is to see probability as a measure of our confidence that some belief is true, as opposed to a measure of some kind of frequency of dice rolls. This allows us to use the tools of probability theory to talk about very abstract things, such as, for example, how confident we can be that the survey data we have gathered is representative of the overall population we are sampling.
Of course, I cannot possibly give a full introduction into the field of Bayesian probability theory here: that would take far too long. If you are looking for a proper introduction, you can look here or here. For a more mathematical treatment of the subject, consult E.T. Jaynes “Probability Theory: The Logic of Science”.
Now for the nitty-gritty stuff. All parameters that are estimated in this paper can be seen as the averages of a Bernoulli process. Conjugate prior for a bernoulli distribution is the beta distribution; prior distribution for all of them is a beta distribution with alpha and beta equal to 1, which produces maximum entropy flat distribution. Actual observations then simply increase the values of alpha (for positive observations) or beta (for negative observations) by 1 each.
This paper uses the term “95% confidence interval” to get a range for the values of many variables. This is strictly speaking false, and in actuality these are 2 sigma confidence intervals around the mean value of the distribution, up to the minimum of 0 and maximum of 1. The incorrect label is used to simplify the comprehension of people less familiar with statistics. In fairness, the difference between a 2 sigma and a 95% confidence interval for a beta distribution is fairly small, especially for the cases where the distributions are very sharply peaked.
Would it be possible to use this in my research paper? How would you like to be cited if so?
This is fabulous! Beautiful caveats.
I didn't see it in your summary, but did you collection location info? If your sample size permits I'd be really interested in seeing if there are any differences. My consumption of media leads me to believe my gaming community is less gender-segregated than the USA one, but I don't have any hard data.