City Roots: Final Process Document (P4)
Created by Ben Barnett, Grace Dong, Gilbert Rosal, and Annie Shi.
Thanks to past team member Nick Tantivasadakarn.
Prologue
This process document focuses on the improvements made after P3 for P4. Therefore, earlier development documentation has been removed for brevity, including the Concept Map, Initial Formal Elements and Values, and earlier Playtesting results. The Artist’s Statement has been carried over to give more context for City Roots.
To get up to speed and view the process document for P3, go here:
Goals of P4
At the end of P3, we were confident that our game modeled the system well and were glad that enthusiastic players gained excitement from watching the system change with each turn. However, we noticed that for less enthusiastic players, there were sometimes long gaps between their turns where there was little they could do to plan ahead or prepare for what the city would look like when mayor-ship rotated to them again. Thus, we realized to keep the game engaging at all times, we needed to add user agency and a more immersive strategizing aspect to the game.
To do so, we decided to add predictability so players could better communicate what they wanted to do each turn and create some long-term planning. This came in the form of restructuring our policy mechanism. Whereas before the format was draw cards each round and choose which policy to enact, the new format we decided to test was have “active” policies remain face-up that each player can enact on their turn else spend a turn switching one policy out.
Artist’s Statement:
City Roots is a game that models gentrification as urban areas develop. Although gentrification is typically a negatively charged word, it is an incredibly complex process that often results in city benefits: reduced crime rates, increases in average income, and lots of other statistics that sound pretty nice. But when talking about statistics, it is all too easy to forget about the people.
City Roots moves players to understand and appreciate some of the complexity of urban development while building empathy for the real-world people who are hurt by gentrification — most notably, the lower-income residents who lose their homes and get pushed out of the developing city, who become part of the “displaced.”
Taking on the role of members of a city council, players must choose which policies to enact. They witness the consequences of their choices as the board, visually representing the city, updates with each decision. Players must aim to increase economic prosperity of the city without displacing too many people, and in doing so, players see how the city becomes divided and lower-income residents are pushed to the outskirts of the city or displaced entirely.
P4 Prototyping, Testing, and Iteration History:
All photos are taken by team member Grace.
Version 4.0
Changes Made from P3
- Redid “drawing cards” mechanic: instead of drawing three policies each turn and enacting one policy (thus performing one action) and discarding the other two, players draw three policies and enact one policy, but the other two stay in play and can be enacted later.
- Policy deck still consisted of 60 policy cards, with repeats.
Playtesting
- Team members playtested amongst ourselves.
- We felt “stuck in a loop” and “bored.” We did not finish a full game within 40 minutes and felt like we made very little progress.
Problems & Changes Made
- Duplicate policies were frustrating as it was difficult to get fresh policies in our “hand” to enact. Solution: Introduced option to either enact one of the three or replace all three available policies for a new hand.
Version 4.1
Playtesting
- Team members playtested amongst ourselves, keeping the mechanic of having 3 active policies that remain longer than one round and with the new mechanic of being able to draw 3 more new policies to swap out the current active 3.
- We also playtested this same mechanic with 2 policies at a time instead of 3.
- This game was more engaging than the last, but still slow. We strategized across turns and tried to anticipate what policies were coming next. Again, we did not finish a full game within 40 minutes.
Problems & Changes Made
- The game board did not fill up quickly enough, leading to slow game play. High-income housing properties had no role in the game, but it is important to represent high-income housing in our system. Solution: Added more severe event cards that added high-income housing to the board, forcing players to make more interesting and complex decisions in later turns.
- The current board and scorekeeping was confusing given the increasing complexity of the game and the increase in long-term strategizing. Solution: Redesigned the board by splitting it into two: a game board and a City Stats board. The City Stats board had a much clearer user interface to make it easier to use.
- We switched to having 2 active policies out at a time, instead of 3.
Version 4.2
Playtesting
- Team members playtested amongst ourselves, with the new City Stats board and updated event cards.
- For the first time, we were able to win a game (as expert players) by building all corporations in one corner.
- We realized there was no reason to keep duplicates of policy cards now that cards stay in play until the players decide to swap one out.
Problems & Changes Made
- Discovering the clustering strategy revealed a flaw in game balance — it was too easy to win. Solution 1: Implemented “City Center.” Players can only add new corporations in the inner square. This reflects how businesses tend to build in downtown areas and more populous areas of cities. Solution 2: Balanced repercussions of event cards by adjusting how many low-income houses get displaced, how many high-income get added, etc.
- There is no point to have duplicates of policy cards. Solution: Narrowed down to only 8 policy cards, one of each.
Version 4.3 (Final Version)
Playtesting
Game Quotes
“I’m ready to boonk somebody. Adios!” [about displacing people. Boonk = Remove]
“This lookin’ like a snacky city!” [on the verge of winning with many corporations]
Player A: “We would displace 2 houses… which is fine? It’s worth it, I think.” Player B: “It means we win.” Player A: “LET’S GOOO!”
Game Quotes
“We don’t need local businesses. Gentrification for the win!”
“It seems to me that the best strategy is pushing the low income houses to the outside.. which is kinda what happens in real life.”
“This feels so real.”
Game Quotes
“So.. we’re creating a ghetto, okay!” [note: this does not reflect the views of the game creators]
“This [low-income house] is a thorn in the side!”
Person A: “Do we care [about displacing this one]?” Person B: “We don’t care that much.”
Interesting Outcomes
See Assessment Results section for more details.
In making the game more strategic and engaging, some players took a different emotional approach — rather than empathizing with the low-income residents represented, they deliberately chose to prioritize capitalism for the sake of winning. Despite this attitude, all of these players acknowledged that they were not taking the humanist approach.
Some players continuously expressed that they “felt bad” about displacing people, though these players tended to be more passive players in the group dynamic. They often took a backseat approach and let other players lead the decision making, regardless of who was mayor at the time.
Problems, Changes Made, and Future Possibilities
- Keeping track of displaced people was confusing, which was also a critique we received in P3. One group forgot to do so entirely, and the two others modified the rules on their own to make it more manageable. Future solution: Instead of adding four resident markers added to the City Stats board each time a house is displaced, the rules will specify that players should only add one resident marker. (This is the solution two groups came up with — they intuitively remembered that 1 resident marker = 400 people.)
- Because of how the two teams modified the rules, the policy “Fund Homeless Shelter,” which brought back displaced people, no longer made sense. Future solution: Remove policy entirely. The game proved itself balanced enough between the winning end state and losing end states to not need this mechanism.
Emergent Player Strategy
The main advantage to adding user agency to our game is that players can strategize and plan out their city each turn to gain city revenue and avoid displacing residents. From our own playtesting (as expert players) as well as observations from playtesting with other users, we were able to see how various strategies played out.
Beginners
Beginners often didn’t have a firm grasp of what kinds of consequences and situations various policies or events would cause. These players often took a while getting a sense of the flow of the game, often resulting in quicker losses. For example, they might place a corporation in the first move and not realize the extent of the effect of the corporation as it can often cause a chain reaction. Or, they may not think about edge cases like trapping a low-income property or have the foresight of where to move various tiles to keep them “safe”. Gameplay often represented a “test and observe” approach, where players did not initially start off with a visualization of what they wanted their city to look like. This resulted in more losses and players expressed feeling frustrated at how helpless they felt in the situation, reflecting how many feel about gentrification. However, they also reported that the game helped them empathize with the topic and that they felt motivated to play again and do better, since they had a better sense of how to approach strategy each time.
Intermediate Players
Intermediate players have a better sense of how to approach the game but are still exploring the different combinations of policies and events. For example, they might know to relocate any adjacent low-income tiles before placing a corporation, but they may not have a plan further than that. Generally, the board tends to take shape organically with new corporations added to the best available location and low-income tiles being pushed towards the edge. While they may try to take better advantage of swapping policies than beginners, they don’t necessarily have an exact vision of their goal in mind besides trying to increase city revenue each time. They may plan better for actions they intend to perform but aren’t quite prepared for the consequences of event cards. Intermediate players win more often than beginners, but sometimes these wins are dependent on luck and come from more damage control than a confident strategy. These players reported actively trying to balance the consequences of gentrification and the urge to know more to better prepare for bad events. They had more “a-ha!” moments where a chain of actions would pan out in their intended fashion, showing a better understanding of how each piece and action were related.
Experts
Expert players tended to start off with a 2-pronged approach: relocating low-income residents out of the way and building up a chain of local businesses. Rather than immediately try to up their city revenue by placing corporations, they tried to arrange the board to a pattern that would also lower their risk of losing. It was quite satisfying to watch expert players discuss their plan and delegate tasks for who would relocate housing tiles, where to start the corporation hub, and how to recover from event cards. The strategy would often end with one corporation causing a chain reaction to flip all the local businesses into corporations to jump their city revenue into victory. The process leading up to this, though, was often risky and one unlucky event could cause them to lose before they were able to carry out the flip. Interestingly, the board also accurately reflected how one would imagine a gentrified city: all the low-income housing on one side or by the outskirts of the city with a centralized area of corporations. Expert players reported feeling like they were actually strategizing as a city council and noticed their board slowly taking the shape of their actions. Rather than panicking about each decision, they were better able to discuss and analyze the trade-offs, reflecting on the consequences of their actions at a meta level.
[insert picture of our crazy board from our last playtesting where it was all divided and gentrified]
Assessment Results (n = 12)
To measure emotional engagement of City Roots, we created an assessment form that players took before and after playing. The questions included:
- Rate your understanding of “gentrification.” (1 = little/no understanding, 5 = advanced understanding)
- How empathetic do you feel towards low-income residents in areas affected by gentrification? (1 = little/no empathy, 5 = high empathy)
- How empathetic do you feel towards the city officials who must make decisions that may cause/deter gentrification in their area? (1 = little/no empathy, 5 = high empathy)
- Only applicable AFTER playing: How did this game make you feel? What was your experience playing like? Feel free to say as much or as little as you’d like!
Results
- 8 of 12 reported an increase in understanding of gentrification after playing the game, and 4 reported no change
- 3 of 12 reported an increase in empathy for low-income residents, 3 reported a decrease, and 6 reported no change.
- 10 of 12 reported an increase in empathy for city officials, 1 reported a decrease, and 1 reported no change
Written Responses from Assessment Form
“It definitely made me more sympathetic toward low income housing but it was cool to have the perspective of someone prioritizing making money but still keeping in mind how youre displacing”
“really fun!! I feel like a capitalist more than a humanitarian”
“I feel giddy. It feels like solving a puzzle! I honestly didn’t have much sympathy for gentrification and I feel like now I have less???😬 I’ve always felt like it’s a natural process of growth and prosperity for everyone”
“This game was really fun! I was invested in making the best decisions for the city with my teammates. Great job!”
“Frustrating but also fun!! I was still learning the game so there was a learning curve — but looking forward to playing again!”
Goals of P4 — Were they met?
As stated, one of our main goals was to increase immersive strategizing and engagement. By iterating through various card mechanisms, we were able to achieve this goal for P4. In short, we increased discussion between players as now each turn could build off previous ones, resulting in long-term strategies. This also resulted in players being able to improve their skills in playing our game, providing an interesting spectrum of play-patterns.
As evidenced by the results from our assessment form, the game was very effective at teaching how gentrification works as a system and creating sympathy/understanding towards city officials who have to make difficult decisions. Thus, the game was great at communicating system complexity, and having players step into the role of City Council paid off. However, the game did not effectively increase sympathy/understanding towards the low-income residents displaced by gentrification. This correlates with the competitive and capitalistic attitudes of our playtesters — they deliberately chose to prioritize corporations over low-income residents in order to win. Figuring out how to address this newly found issue is a challenge for our next iteration!
Overall, we succeeded in making City Roots more engaging, while still teaching our players about the system we had set out to represent. In P4, we were able to integrate more system complexity and increase playability by changing how policies were selected, editing the Event Cards, and creating a separate City Stats board. Our playtesters expressed great enthusiasm and joy for City Roots, which we consider a major success and improvement from P3!
Appendix
Print-at-Home Version of City Roots:
Tommy’s Emotional Reaction During Playtesting
