Sexuality and Gender in games

how is this still an issue?

What even is gender?

A person’s sex is what’s in between their legs, while their gender is the characteristics society aligns to the extremes of a spectrum representing masculinity and femininity.

In sociological terms, Ann-Maree Nobelius refers to ‘gender role’ as the characteristics and behaviors that different cultures attribute to the sexes. What it means to be a ‘real man’ in any culture requires male sex plus what our various cultures define as masculine characteristics and behaviors, likewise a ‘real woman’ needs female sex and feminine characteristics. [1]

This is a reasonable description, but is a huge issue in games and in the games industry. Think about the gender roles that are set by the intro to fallout 4. Before you edit your characters, you are a ‘default’ straight white male. After creating your character, you still have to be straight and you have a child. When you leave your house, everyone in your street is in a straight relationship and the plot device to get you to follow the main story is that they took your kid and killed your spouse.
In the previous two titles you edited your character before you got to see them, you weren’t forced to be a straight character at any point in time and ‘I have to save/avenge my family’ wasn’t your primary driving force to get you to follow any of the main story missions.


Sexuality and gender (identities) represented in games

Typically, family and relationships have been used as walking plot devices (Gears of war 2) or mechanics (fallout 4). If you don’t already start off with one, then you make your own by gifting a member of the opposite sex (fable) until you can complete their mini-game or side-quest (mass effect). Now that you have a spouse, you gain a bonus to your XP, or even an achievement for sleeping with them (Dragon Age Origins). [2]

There are only a few examples of gay and transgendered characters that have come from the mainstream games industry, such as:

Examples of Gay, Transgender or Cross Dressing Video Game Characters

These are not the best representations of their respective gender or sexuality though, as they are poorly portrayed, one dimensional characters and the only protagonist/main character examples are found in games with a character creator. They are only non-straight by player choice, not as a crucial part of the plot.

Robert Yang cuts the mainstream industry some slack as the climate is so risk-averse that it’s a miracle when they get to make something compelling, much less invest heavily in writing and narrative design. He speaks of the many industry people he has met who have much more radical design opinions than their stakeholders and customers will allow them to express in their work. However, there are just as many who are totally oblivious.

Yang concedes it is difficult to say whether or not games have succeeded in portraying non-heterosexual figures accurately, as the industry is still learning to tell stories with interaction. “Most game characters are still refrigerators with guns,” he laments. [3]

There have been large strides forward for creating multidimensional non-straight or non-binary characters by Bioware, including gay, asexual and transgendered characters and have been praised for treating them respectfully.



What’s the problem though

the problem is that there has been a history of awful representation, if any at all, which makes people feel unwelcome in the community and in the industry (and they really have been). This then contributes to a lack of diversity in the industry, becoming a recursive problem.

There is still an issue in the industry today, take a look at the promotional material for dead island riptide, tastefully named the ‘zombie bait edition’, which shipped as a limited edition in Europe and Australia. [4]

Much more recently though is the incident where a highly paid developer for Oculus crashed a queer developer party at GDC to get free drinks and mansplain how we are “beyond safe spaces”. [5]


WHY you should care

We are creators of media content. We have learned that there is immense power in media, enough to define and control cultural values. Even just supporting an ideal or creating a dialogue is enough to make a huge difference.

Tracy L. Dietz states that video game characters have the potential to shape players’ perceptions of gender roles. Through social comparison processes, players learn societal expectations of appearances, behaviors and roles.
Girls may expect that they be dependent victims and that their responsibilities include maintaining beauty and sexual appeal, while boys may determine that their role is to protect and defend women.
Thus, Dietz claims, the roles internalized by the child, including gender, become for the child, and later for the adult, a basis for other roles and for action. The gender roles internalized by young individuals have a significant impact upon their perspectives and the additional roles they assume in later life.
Feminine and masculine symbols are supposed to become a part of a child’s identity. [6]

It is proven that media has an effect on society, helping to form the rules of gender ([7] Gendered Marketing). We know that boys and girls colours used to be swapped, Lego was marketed to girls and the whole family before it was sold to just boys.


What you can do

Learn how to identify power structures. Who gains from there being specific gender roles? What about in games? What are the best ways to subvert binary gender roles and hetero sexual values in your medium?

Attempt to create socially responsible media. Don’t rely purely on tropes and binary genders. Most attempts in games to do this are only lacking thoroughly fleshed out character designs and games that do incorporate this like The Last of Us have performed exceedingly well.

Help promote and support diversity in your industry, by helping to create and respect safe spaces. Stand up against poor behavior and views against sexuality and gender.

Do your best to be a decent person and treat everyone equally.

Thankyou for your time.



















never gonna be A*


A* is a computer algorithm that is widely used in pathfinding and graph traversal, the process of plotting an efficiently traversable path between multiple points, called nodes. It is noted for its high performance and accuracy.

How does it work?

This video tutorial goes through each step of setting up an A* algorithm, which will then need to be implemented into your project (for example, how do you use the list of nodes once it is returned or how do you identify impassable areas of terrain).

I am still working on implementing this pathfinding into my killbot, I have run into a lot of issues and am currently stuck on this:

The path that is returned seems to enjoy moving through walls, or the selected nodes to travel along are spaced very far apart (moving across wall sections as well).

I’m not sure this will be ready for the bot tournament, not unless I go without sleep, but I can’t afford that as I have 2 other projects due this week, and I’m leading a side project.

However, the side project is off to a great start. It is an endless runner designed to show off the capabilities of a whole bunch of animators at once. It is set up to have each team member working as much in parallel to one another as possible, and will have the capability to give credit to each artist as their work comes up, as well as allow control over things like the flow of time and camera positions. This week, I started recruiting animators, there are about 17 working on the project right now. We also chose the main themes that everyone will be working in, as shown here:


Those were chosen through voting, from a list of 20 mood boards, each submitted by a member of the animation team. Each member then got to vote for 5 different themes, meaning that everyone voted for their own board and then 4 other boards. These five were the most popular, so everyone got to have their say. Now they each get to choose one of these 5 themes to create from. The whole point of this is so that we can have background music and skyboxes that fit the models specifically (and I don’t have 20 audio guys to do 20 music tracks). I am extremely happy with the work that has been put in just to make up some nice mood boards and I am excited to see the work in its completion!



Surprisingly enough this week, I focussed my work on the killbot, as there is a Killbot Tournament tomorrow. Over the last couple of weeks, I drank heavily while coding this thing and then stopped drinking while I untangled all of its code. I was running into constant conflicts where whatever thing I was trying to implement was being overridden by some other section of code that I had forgotten about, or was made impossible to implement as there was no safe place to push it in. I devised a new way to run the code with Adrian White, which is just three steps that the killbot moves through, with different behaviours that run based on that. This mainly makes it a lot easier to figure out what needs to happen when, and really cleans up my code, comparatively.

3 Step plan:
Killbot stepsSo as you can see in the extremely easy to follow diagram above, there are three steps to my killbots behaviour cycle.
Step 1 is a rotational scan of the battlefield, trying to spot its target. It can pick up an enemy, bullet or nothing. If it spots nothing or a bullet, it stays in this step, otherwise it moves on to
Step 2, where it scans again, except aimed at the same position where it saw the enemy last round. If doesn’t see anything, or only spots a bullet, it will move back into Step 1 again, otherwise, it will move forward into
Step 3, where it will predict the enemies movement and fire at the enemies’ estimated position.

The current pattern for my killbot is to rotate around by the FOV amount each turn, but flipping the angle to negative every second scan. I set this up to help avoid an enemy sitting inside its blind spot as easily (the first pattern we learn is just a clockwise rotation. it is very easy to place a bots movement pattern inside that huge blind spot based on their position and how much time has passed). The next thing my bot does is, once it fires at an enemy, it scans in the enemies last predicted position. If the enemy is not there, instead of resetting the viewing angle, it starts searching from that position. On average, this heavily reduces the time it takes to reacquire the target.

As previously stated, this bot uses the ‘ded reckon’ model of prediction (or something close to)prediction

The way this works is the killbot captures its targets position over 2 turns. Using this we can find the enemies’ distance traveled and movement direction per turn. by adding this to its current position, you can get a good idea of where the target will be next turn, easy! The problem lies in the time it will take our bullet to reach the target. if it will take two turns for the bullet to reach the predicted target, the we have to aim two turns ahead. Now we have even further to travel to reach the predicted target, though, and so this starts to get very messy. The best way to do this is to predict a whole bunch of angles, and the respective targets position when our bullet intersects its path until we find one where the distance between the two converges to a point (or actually collides). If the enemy continues on this path then we actually have an almost flawless accuracy.


Moves just like a snake…

Currently, my killbot isn’t doing very much to trick the enemies prediction, it picks a random spot on the map and snakes its way towards that spot by applying an alternating
cosine and sine offset to its movement direction. This offset was amplified by its behaviour step counter, so it turned much harder as it was firing, but in writing this I just realised that this would lower its velocity and make it, on average, much easier to hit.



Anyways, wish me luck for the tournament, if I come last I will eat a whole bag of chewable cyanide tablets.