But here I’m going suggest something a bit different by setting up a spectrum of computational journalism artifacts along the dimension of content specificity. On one end you have the things I just talked about: tools that help journalists uncover stories and make sense of information. These tools are practically independent of any semantics associated with information but can be customized for different data types (e.g. geographic, time, network etc.). They’re also geared toward insight generation and designed for the kinds of work processes and tasks that journalists engage in on a daily basis.

On the other end of the spectrum there are computationally infused presentations of  stories. A computational journalist might use computation in such a story by making models or data interactive. For example one interactive graphic I worked on for SacBee.com is based on an evaporative water model together with scraped hourly Sacramento weather conditions. The goal was to paint a picture of the model and help people understand when best to water their lawns.

Another example comes from editorial simulations such as September 12^th. In that interactive, an editorial model describes the relationship between terrorists and anti-terrorist bombing in the Middle East. But while the model and mechanic are of course described abstractly, the semantics of the graphics and interactions are what is essential to the presentation.

Content specific presentations rely heavily on the semantics of the information to convey meaning. Rather than being generic information tools, they intertwine computation with the story itself. Interaction, information, and visual design become essential to communicating a semantically laden model. And in comparison to generic tools, content specific CJ needs to be designed with a “reader” in mind; to disseminate insights (or opinions) with the public in mind.

There’s value to both kinds of computational journalism: tools to help uncover stories and develop models, and specific presentations to effectively communicate those models.

Since the laws changed back in 1997 in the US opening the floodgates for big pharma to peddle their wares directly to patients, there has been a debate about the efficacy and value of DTC advertising. Even today the FDA lists several ongoing studies evaluating the understandability and effects of DTC advertising. But the debate is political too. Congress has recently started floating proposals to limit the marketing powers of pharmaceutical companies for the first 2 years after a drug has been approved by the FDA. This would give regulators additional time to evaluate a new drug’s broader risks once it were available on the market.

Drugs aren’t the only DTC advertising issue generating controversy either. DTC medical device advertising is already generating a debate about the ethics of advertising products to people that can’t possibly understand the medical risks and decisions necessary for a medical device implant.

This is not to mention that DTC could be pushing up the overall costs of health care by directing people toward brand name “designer” drugs that may not be any more effective than alternative treatments. Obama’s $1 billion stimulus funding for Comparative Effectiveness Research (CER) should help with this somewhat by doing real comparisons of which treatments are “worth it” both in $$$ and patient value.

But big pharma is big business. Huge sums of money are invested in pharameutical advertising ($5.2 Billion in 2007), with spending growing at an annual rate of about 20% from 1997 to 2005. And with huge returns on investment, who can blame big pharma for wanted to drive traffic for new drugs by going straight to the people who would need treatment. The birth-control pill, Yaz, increased its sales from $262 million in 2007 to  $616 million in 2008, utilizing a few high profile (and misleading) broadcast ads.

Misleading or inaccurate information could lead consumers to make poor health decisions, or take risks that they may not fully understand. So how does the government keep consumers safe and pharmaceutical advertisers honest? Right now the process is managed by the FDA Division of Drug Marketing, Advertising, and Communications (DDMAC). Advertisers are required to submit promotional materials to the DDMAC when they are first used or published, but not before. This means the FDA’s role is purely to “check up on” what advertisers publish, ex post facto. Ads can be circulating for months before they are critiqued and evaluated. And if an ad is found to be misleading, the FDA sends a warning letter to the offender asking them to retract the ad. That’s it most of the time.

What does the FDA check? According to their website, “advertisements cannot be false or misleading or omit material facts. They also must present a fair balance between effectiveness and risk information. FDA has consistently required that appropriate communication of effectiveness information includes any significant limitations to product use.” They require that all drug advertisements contain information as a brief summary relating to side effects, contraindications, and effectiveness. For instance, the law states that, “an advertisement may be false, lacking in fair balance, or otherwise misleading if it: “Fails to present information relating to side effects and contraindications with a prominence and readability reasonably comparable with the presentation of information relating to effectiveness of the drug, taking into account all implementing factors such as typography, layout, contrast, headlines, paragraphing, white space, and any other techniques apt to achieve emphasis.” The FDA has a very specific set of guidlines for how ads can be used in the video domain as well; including different categories of ads such as “product-claim ads”, “reminder ads” and “information seeking” ads.

The current FDA procedures for the evaluation of DTC video (broadcast) ads are wholly unwieldy. They include the submission of TEN (!!!!) copies of an annotated storyboard with each sequentially numbered frame and associated annotated references and precribing information (PI) supporting claims. Isn’t there a better way to do this?

This got me thinking about how an application like Videolyzer, that I originally built as a tool for bloggers and journalists to critique and debate online video, could be used by someone like the FDA (or the pharma companies) to streamline and digitize the evaluation and sourcing of video advertisements. This is in addition to exisiting journalism outfits, like Consumer Reports Ad Watch, which could use the tool to add back context to an overly curt video advertisement. Yaz, a birth control pill marketed by Bayer gained notoriety in late 2008 for two ads that were deemed misleading by the FDA and for which they had to run corrective ads in 2009. I’ve added the original version of one of the Yaz ads to Videolyzer for anyone interested in seeing how the tool can be used to critique a pharaceutical ad.

In their 2004 textbook, Behind the Message: Information Strategies for Communicators, Kathleen Hansen and Nora Paul write, “Informal sources include observations about audiences, messages, and the environment in which the communicator operates, as well as networks of supervisors, colleages, clients, neighbors, and friends the communicator deals with every day.”

We would posit that news games (or other forms of interactive multimedia) could function as a valuable addition to the journalist’s toolbelt of information gathering capabilities if they were properly intrumented to gather observations of user behavior. Case in point is American Public Media’s Budget Game, a complex simulation asking users to manage the US federal budget by selecting different policy options ranging from taxation to defense and the environment. In the process of play, the game elicits a set of policy priorities from the user, leading to an understanding of the depth, complexity, and tradeoffs of remaining true to your ideological beliefs while also maintaining a realistic air. After decisions are made, the budget is simulated out to 2028  and you get a sense for the impacts of your decisions over time. You can also see how many other people played the same sets of decisions as you did and if you input some basic demographic data you can even start comparing your decisions to others.

The implications of the APM Budget Game as a journalistic tool, an informal sources, are interesting. On the backend, we can imagine a journalist looking at the aggregate decision data taken from players of the game and looking for trends or correlations between sets of decisions. Do 80% of players decide to roll back Bush’s tax breaks? Are those same players in a middle income tax bracket? Also, what is the ordering of the decisions made in the game? Perhaps this could lead to some insights into how players view the importance of some of the issues at stake. Interesting trend or correlation? The journalist can capitalize on it and write a follow-up story.

It’s well known that online journalism operations (e.g. the NY Times) have analytics departments that do data-mining on pages to understand both demographics and how users flow through news pages. But what about an interactives-analytics group that data-mines on the logged behavioral response to games and other interactive graphics? This type of mentality could also lead to different types of game designs since the goal would be both the user experience as well as the “exhaust”, the data that could be collected, from that user experience. How to design such an interactive experience that also produces something interesting for the reseacher / journalist?

Clearly games as informal sources are not going to replace other forms of sources for journalists. Interviews of scholars or reliance on institutional reports produce different types of insights compared to the observation of online behavior. But this could be yet another way to probe at the audience and understand what is most relevant to them.

I started by reviewing “The Sociology of News” written by Michael Schudon, a sociologist at UCSD. If you haven’t read this book I would recommend it, not only for its concise definitions of terms like “news” and “journalism,” but also for its in depth description of the American culture of journalism.

Schudson claims that one of the distortions in the news that arises out of its culture is that it is “event-centered, action centered, and person-centered.” Event emphasis, for better or worse, is a characteristic I think most of us would agree predominates the news. Here’s where games can provide something more: process-oriented journalism. For instance, how does the process of the electoral college work? The news industry has often failed to provided process-oriented reporting, but games are perfectly suited to process explication. At the same time, Schudson writes, “When things are going well there seems less of a reason for a news story. The news instinct is triggered by things going badly.” Is process just boring? And if so, how can games make process more engaging for consumers? Perhaps the unusual and the “bad” news needs to be incorporated into process games.

On the other hand, perhaps what people want to know from the news isn’t process and that’s why it’s not prevalent. The brutal truth is that a majority of the useful information in the news consists of things like movie listings, restaurant reviews, weather forecasts, and local sales advertisements. This extends to “news you can use,” like reports about your health and financial investments. These are the topics and types of information that are “important” to people on a daily basis, for which they need a guide.  There’s a whole interesting story to tell here about the history of news and its evolution. Politics didn’t really enter into the news equation until the rise of democracies. The News was appropriated by those seeking democracy in the 18th century, and in the course of time journalism has maintained its rhetoric as the machinery that makes democracy work. But perhaps the bias that “serious” journalism needs to be about politics or public policy is unfounded and was socially constructed in a distant time. All I’m saying here is that games have a chance to go back to basics and give people what they want: the information they (really) need presented in a compelling format.

But whether or not journalists will accept games into their repertoire for telling stories is questionable. Technical and literacy issues aside, there is cultural conflict between journalism and games: News has a “prestige” aura around it. The prestige of the news organization legitimates certain forms of knowledge and amplifies stories. It provides a certification of importance. Just think back to the time when you made “the news” and were in the local paper. Somehow that paper had conferred on you an air of importance. Games may lack this prestige value because of their association with frivolity, playfulness, and general unproductivity. To break this cultural standoff would take leading news organizations accepting games into their news culture and framing them with the same aura of prestige conferred on other media.

The final point I want to make here builds off of Schudon’s observation that oftentimes a journalist’s aim in telling a story is astonishment and moral outrage rather than any deep understanding; the so called “Holy Shit!” stories that make milk come out of your nose at the breakfast table. This may also be an area where games can excel. Sure, images and videos can shock you, but what about a game that puts the player in an uncomfortable situation where their own actions shock them. I’m reminded of the PETA parody of Cooking Mama, where the player had to do all sorts of inhumane things to a Tukey in order to put Thanksgiving dinner on the table. If attention getting is part of the news culture it seems like a no-brainer that games can do this every bit as well as other media, maybe even better, albeit with perhaps more of a time investment on the part of the player.

Specific Why of State. This is a precise explanation for a game element’s attributes including any relationships, the directionality of those relationships, and their valences.

Sim City 4 does this exceedingly well but using a “?” tool which when clicked on an element exposes the state of the attributes of that object relevant to game play. For instance, it will tell you the crime rate and freight trip length for industrial buildings. At any point in the game you get a snapshot of the status of an individual object. Another method used to expose state is by hovering the mouse over an object. This reveals less information than the “?” click, but still shows you “the top three conditions that currently have the most dramatic impact on the desirability of the area” [Sim City 4 manual]. When the state of elements is spatially structured as in a map, overlays are used to show the distribution of a variable across space. Graphs are used to show transparency of state over time, thus aggregations of individual elements’ state are shown as a time series. Sim City 4 manages to achieve a playable simulation in part because the information that is necessary for optimizing the simulation is transparent in the interface. This is done through hovering popups, clickable popups, spatially layered attributes, and temporally graphed attributes.

Another game I looked at, Oil God, adds an additional twist to communicating state transparency by adding an overlay network visual on top of a spatial layout to explicitly show relationships between game elements. Democracy 2 encodes two more variables into its graphical overlays: relationship valence (via red-green coloring) and directionality (via animation direction). Another perhaps simpler method for communicating specific state information is via textual feedback. For instance, in The Garbage Game, where the premise is to keep as much refuse out of landfills, I made a decision in the game to refill and reuse my plastic bottle and it told me: “We figure that a bottle will get refilled about three times on average, so we’ve reduced the volume of water bottle waste in your sorted recycling to 25 percent of the 17,677 tons that New Yorkers currently generate each year, or 4,420 tons.”

Specific Why of State Change. This relates to explicit descriptions of computational state and explanations of why a state has changed. What was the trigger, event, or decision that affected a state change? Was this trigger algorithmic or based on user input? This facet of mechanical transparency is lacking in many of the games I looked at. One game that did have some attempt at an explanation for state change is Energville. At the end of the game, a graph shows the economic, environmental, and security impacts of your decisions. Along the timeline of the graph there are icons of different events that have happened. Clicking on these expands them out with additional textual information. For instance, “2014: wind power fails to deliver. -resulting in a 20% increase in your Wind economic impact.” Since state change is a matter of an attribute over time, annotated graphs and timelines seem to be a natural interface metaphor for explaining state change. Another candidate would be animation. For embedding monikers about state change within an interface itself, something like the afterglow effects in Phosphor might also work.

General Why of State. This is a generic explanation for an element’s attribute or a relationship between attributes, which is not related to the specifics of any particular element.

General why of state involves explication of the existence and valence of a relationship rather than the actual mathematical description, which would be included in the specific why of state. Because the explanation is general in terms of being non-specific, external information and sources can be used to buttress the existence and valence of relationships in the model. One of the tensions that this general information brings up is the granularity of its availability. Is it embedded in the interface or simply available as blocks of text elsewhere? What we see in many games is that the general why of state is offloaded to textual explanation on a separate information page, sometimes also outside of the interactive application itself. In Energyville, which has players managing economic, environmental, and security impacts of energy decisions, each of these facets has explanations in plain text. For instance, the environmental facet, when clicked, lists out all the negative impacts on the environment and cites the names of some recent reports which were used to “inform the impact assessments.”

Sim City 4 and Democracy 2 follow a similar strategy of explaining in text generally what the relationships are between variables of interest. For instance, In Sim City 4, clicking a city opinion poll about land value tells you this: “Represents the average land value in your city. To raise land value place parks, schools, hospitals, and other amenities in your residential zones.” In Democracy 2, the textual information comes in the form of “Encyclopedia” articles, which explain and provide context for the variable currently under consideration. The advantage to a textual approach is that we have well understood conventions for citing information in text. Also, it’s unclear whether or not an abstract relationship could be represented well either in an image or in video material. The value of such multimedia assets may however serve as existence proof for some attribute of interest, if such an attribute is not already obvious.

Back in the mid 1990’s there was a flurry of activity in HCI in trying to understand the explainability and transparency of interactive systems. Paul Dourish published extensively in the area and is known for his book, Where the Action Is: The Foundations of Embodied Interaction, which (among other things) connects ideas from ethnomethodology with those of technology and system transparency.

A key concept studied in relation to ethnomethodology is that of accountability, meaning “observable and reportable” or able to be made sense of in the context in which an action arises. It addresses not just the result or outcome of an action but also includes how the result was achieved. Dourish sums it up thus, “Put simply it says that because we know that people don’t just take things at face value but attempt to interrogate them for their meaning, we should provide some facilities so that they can do the same thing with interactive systems. Even more straightforwardly, it’s a good idea to build systems that tell you what they’re doing.”

An account then is something that provides accountability in a software interface. The goal of an account is to provide some explanation for how the sequence of actions up to a moment results in a system’s current configuration. Why did each action in the interface affect the state in the way that it did? This is extremely similar to the notion of the transparency of mechanics that I developed in a previous post. Too bad Dourish beat me by a decade or so.

In his paper, Accounting for System Behavior: Representation, Reflection and Resourceful Action, Dourish posits a compelling definition for an account: “Accounts are causally-connected representations of system action which systems offer as explications of their own activity. They are inherently partial and variable, selectively highlighting and hiding aspects of the inherent structure of the systems they represent.” The notion of partiality of accounts is troubling with respect to journalistic transparency since information exclusion entails a danger of bias. But journalistic transparency can be maintained even in partiality if decisions about inclusion / exclusion are explicated. Decisions about inclusion / exclusion can however also be made algorithmically, which confounds the problem for interactive systems. The classic example is in the (lack of) transparency of ranking algorithms used in online search engines.

Another connection that I see to journalistic notions of transparency is that accounts are context sensitive: more general statements of transparency are less context specific whereas less general statements embedded in the actual context of the running system are highly context specific. “The account that matters is one that is good enough for the needs and purposes at hand, in the circumstances in which it arises and for those who are involved in the activity,” writes Dourish in Where the Action Is. What are the needs of the user in some particular situation? A journalist writing interactive software would need to answer the question: “What states need to be observable?”.

Furthermore, in journalism, transparency happens at varying degrees and levels of granularity and is thought of in a practical light where, for instance, it would not make sense to be transparent about all of a reporter’s notes in a newspaper since there are space constraints. Practicality, efficiency of communication, and usability of an interface, can be subverted if everything must be transparent. What is the appropriate level of transparency, both mechanical and journalistic, for interactive games and info graphics?

Johnson and Johnson have also written about another important facet of transparency that is relevant here. The nature of the knowledge that is being made transparent, whether declarative or procedural knowledge can have an impact on how that transparency is presented. Is it easily citable or does a complex process need to be explicated? I think this gets manifested in journalistic transparency as a difference between transparency of reference and transparency of construction.

• Decisions. Explaining how and why relevant editorial decisions are made. This includes explaining any inclusion or exclusion criteria for any controversial decisions as well as explaining why a decision to anonymize a source was made. Selection is at the heart of bias, so to be more transparent about bias, journalists should always support their decisions about selecting or excluding information.

• Lack or Uncertainty of Knowledge. Being upfront about acknowledging what questions stories do not answer (or cannot answer). When information is uncertain or unavailable, what assumptions have been made which affect interpretation?

• Production Process. Providing evidentiary support to a story. News providers can use the Internet to provide primary source material in the form of databases, documents, methodologies, or audio and video of interviews. This can also include information about the nature and quality of the source used for information gathering. For instance, was the source of information a press conference, interview, press release, or quote from another media institution? What is the context and circumstance under which that information was gathered? Why is that source qualified to comment on the issue at hand?  If multiple sources were used, how were they selected? At a different level of granularity process can also involve explaining to the audience how stories are developed, reported, edited, produced, and presented. In Ian’s terminology highly granular process transparency corresponds to the transparency of reference and at a less granular level to the transparency of construction.

• Labeling. Advertisement and opinion needs to be marked as such to avoid confusion by news consumers.

• Correction. Admitting and correcting mistakes and errors in a timely fashion.

Transparency is modulated by features such as:

• Granularity. What is the appropriate scale to address transparency? Sometimes it is addressed at the level of the whole newsroom in the form of an editor’s column or blog about how decisions are made. Other times it should be addressed with more specificity, at the level of providing links to primary source material as well as providing context about the information sources in a particular story.

• Degree. Even in a highly granular instantiation of transparency, not every statement likely needs that much attention to detail. Perhaps there are culturally accepted chunks of information that don’t need explicit citation, or are so widely known as to be considered wasting space if they are included. No one should expect that an article contain a complete list of explanations regarding sourcing or newsgathering, as this would be overwhelming for a consumer and perhaps impossible in print or video where space and time are at a premium.

Ultimately though the granularity and degree of transparency need to be audience centric. “What does my audience need to know to evaluate this information for itself? This includes explaining as much as is practical about how the news organization got its information.” (The Elements of Journalism. 94)

When considering bloggers-as-journalists the concept of transparency shifts a bit. Whereas the predominant notion of the journalist as objective and impartial reporter prevails in mainstream media, bloggers participating in journalistic activity tend to be transparent about their bias and background as well as what they have at stake. Bloggers have the freedom to express transparency in motives as well as transparency in process. For instance, bloggers often link to documents, sources and supporting evidence to buttress their own authority whereas oftentimes press articles are written without links, as if for print.

In a future post I will mix and match this understanding of transparency in journalism with the notions of mechanical transparency and system transparency I’ve talked about before.

While the state of the system is central to the notion of system transparency, what we’re really interested in is an idealization of the system state. What’s important in a user-centric model is the representation of “state required to account for the future external behavior.” In the text Dix refers to this as the “effect” which I think is nasty terminology. I’m going to call it the “User-Relevant State” or URS.

They do arrive at a workable definition of state: “[Transparency] would say that there is nothing in the state of the system that cannot be inferred from the display. If there are any modes, then these must have a visual indication; if there are any differences in behavior between the displayed shapes, then there must be some corresponding visual difference.” This gets at the central usability heuristic of observability and its relation to transparency. Observable states are visually shown in the interface; an invisible component of the URS does not uphold the principle of system transparency. One could make an argument that if the URS is not fully transparent usability problems are likely to ensue since the user does not have adequate feedback on the state of the system relevant to its usage.

Of course, not all of the URS may be observable in one view because of screen real-estate problems and that the display could be unintelligible if there were too much shown. Thus the URS can be progressively observed through interaction (e.g. clicking a marker and an object for state or displaying a layer over objects which explicates state). The usability of a system and its effectiveness may however be increased if more of the URS (such as data dimensions in a model) is visible in the display in one view. A key connection Dix makes is that when the user can observe the complete state of the system they can (in theory) predict what the system will do. This is precisely what many simulation games are all about: predicting how actions taken on the model will impact on future states of the simulation. The question remains: does complete transparency make a game experience too easy? Isn’t there some satisfaction in figuring it out?

In Ian’s prior post on transparency and games he mentions three types of transparency: transparency of influence, transparency of construction, and transparency of reference. Cutting across these facets of transparency I’d like to add the transparency of mechanics which is particularly applicable to any consumer-facing journalistic software, of which games are one instance. To get a better understanding of (1) what the transparency of mechanics involves in journalistic software and (2) how mechanics are currently communication in software I analyzed a number of examples of serious games and info graphics including: SimCity 4, Democracy 2, Oil God, The Garbage Game, Energyville, Stop Disasters Game, The Chevron Energy Generator, Better to Buy or Rent, and Boston.com’s 2008 what ifs. In this post I will mainly address the definitions and in future posts I will consider how the model of the transparency of mechanics presented here has been and can be reified in interfaces.

What I mean when I say “mechanics” is essentially the internal and external state of elements and relationships between elements of a computer program, including the values or attributes and categorizations of elements in the software with respect to their circumstances (e.g. time, place, etc.). A state within a game is the instantaneous value of all elements and relationships between elements. For example, in Sim City the state of the game at any one time slice is the set of all values (e.g. low, med, high) of all attributes (e.g. pollution, education, fire protection etc.) for all games objects (e.g. power plants, residential areas etc.) including how those objects are interacting and influencing each other at that moment.

Transparency of mechanics can be broken out into different facets including:

• State. What are the attributes and relationships of game elements?
  • The specific WHY of state: a precise explanation for an element’s attribute.
    • This gets at the notion of what the relationships are between elements and what their valence and effect on each other is. For instance, what attributes at the current time-slice contributed to the attribute of the object of interest?
  • The general WHY of state: a generic explanation for an element’s attribute
    • What are the general attributes which affect a given attribute of interest, i.e. what are the relationships and weights to other entities? How do you know the strength and directionality of those relationships?
• Computation of State (How). How are changes of state computed? How does probability factor into the computation? What is the method of inference or equation governing state change?
• Explanation for State Change (Why). What was the trigger, event, or decision that affected a state change?
• Assumptions and Limitations of the Model. How is the model grounded and where does it fail to accurately portray the phenomenon of interest?

Being fully transparent about all mechanics in a game may turn out to be a daunting and in fact unproductive enterprise. This is because of the granularity of transparency that would need to be supported to show the attributes and relationships between all game elements at all time-slices. Do users really need to know about every little state change? The answer is clearly no, but the job is then up to the journalist / programmer to make decisions about which aspects of the model should be most saliently transparent in the final presentation. Another question to ponder here is whether too much transparency in games can ruin the fun of it? And if perhaps by explicating too much you undermine the medium’s abilities to get people to comprehend models via interaction?

It’s useful to draw a distinction between data and information here, data being raw sensor readings or direct observations and information being additional context and interpretation based on data. There’s a difference in what needs to be done in terms of transparency of data (which the Time did magnificently for the interactive polling piece) and transparency of information. This is because there is a layer of contextualization and interpretation that also needs to be explicated in order to be transparent about information. This touches on issues of individual and organizational biases since interpretation itself is influenced by these outside sources. Moreover interpretation can be something encoded into mathematical equations that produce information (derived values) from the actual raw data. Consider the mean of all polls for each candidate. This is a derived value, albeit one that most people understand readily, but nonetheless which takes an interpretive stance that a mean of polling data collected under different circumstances is meaningful. As we move from simple means to more complexity, a data driven model is really nothing more than a series of complex mathematical manipulations which interpret the data into a manageable form of information.

Here’s the crux: to be transparent about information (interpretation from data), journalists need a way to be express interpretations or manipulations, mathematical though they may be, in a way that is easily understood. This has direct bearing on games for journalism since the models on which games interpret the world will be important to explicate to consumers in the spirit of transparency. The problem alas is that math is inpenetrable to many. Imagine the Times providing a 3rd link for transparency, one which shows a nasty equation on top of which a simulation is built. This is important, because even though many people won’t take the time to understand it, the people that take the time to will be able to verify or understand the model. But what about the other people? They need Usable Transparency. I like to think that a simulation game like SimCity follows the principle of usable transparency – you don’t need to understand the simulation model to be able to make decisions in the game. The manual describes in prose what to do to alleviate trash problems, create more jobs, or reduce rush hour traffic jams. I think this is a useful paradigm that would serve journalists well in thinking about transparency as it relates to games. The collection of the data is important, check. The data itself is important, check. But the mathematical model which drives a simulation is important too. I would argue for a prose description of that model which itself is footnoted with grounding equations.