Great game of Turkey

Make today's decision First, see the issue and possible actions.

# This code is Op_en7421# on page [[Great game of Turkey]]

library(OpasnetUtils)

objects.latest("Op_en7421", code_name = "initiate")

temp <- EvalOutput(issueofday)
temp <- temp[temp$Date == as.character(Sys.Date()) , ]

cat(
  "Issue #", 
  temp$Issueid[1], 
  ":", 
  as.character(temp$Issue[1]), 
  "\n", 
  as.character(temp$Issuedescription[1]), 
  "(", as.character(temp$issuevoteResult)[1],
  "votes).\n"
)

colnames(temp@output)[colnames(temp@output) == "issueofdayResult"] <- "Votes"
oprint(temp[ , c("Action", "Actiondescription", "Actionid", "Votes")], include.rownames = FALSE)

Then, make the decision about today's issue.

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# This is code Op_en7421/choices on page [[Great game of Turkey]]
# Parameters used:
## option: numeric (1 or 2)

library(OpasnetUtils)

objects.latest("Op_en7421", code_name = "initiate")

temp <- EvalOutput(issueofday)
temp <- temp[temp$Date == as.character(Sys.Date()) , ]

dat <- data.frame(
  Date = temp$Date[option],
  Issue = temp$Issue[option],
  Action = temp$Action[option],
  User = wiki_username, 
  Result = as.numeric(Sys.time())
)

opbase.upload(
	dat, 
	ident = "Op_en7421", 
	name = "Great game of Turkey", 
	subset = "Decisions", 
	act_type = "append", 
	language = "eng", 
	who = wiki_username
)

oprint(dat, include.rownames = FALSE)
cat("Your choice was successfully saved.\n")

Question

What is a good game to crowdsource citizen priorities about daily political decisions in such a way that

it can be done using a mobile app,
it characterises happiness of citizen groups of the decisions,
it characterises progress of important societal values,
it enables crowdsourcing the actual issues and actions asked?

Answer

The idea of the game is to decide from two alternative actions of an issue each day. An action will cause a change in happiness of different population groups (nationalists, conservatives, liberals, kemalists, and minorities) and societally important values (civil rights, women's rights, religion, national values, and democracy). Each player will be scored as decisionmaker based on how they are able to promote happiness and societal values. Players see their own score over time, accompanied by the score of the crowd. The crowd always decides whatever is the most popular action among the other players.

Before issues and actions become available for decisionmaking, they are created by crowdsourcing by the users. All users may suggest one issue for each day, and one action for each issue. Users may also vote for issues and actions they'd like to see played. The most popular issue will be played each day, and the two most popular actions will be available for decision.

There are some opreational rules:

You can suggest an issue for a specific day in the future.
You can suggest actions to an issue as soon as the issue has been suggested.
Values and happiness are attached to actions.
An issue can be suggested again for a later time point (for example, if it is not played on the first day suggested). If this is done, previous related actions and their votes apply.
Actions can be voted as soon as they are in the system, but issues can only be voted on the day of decision. The purpose of this is to promote discussion about actions and hence critical evaluation which actions should be upvoted to be played.
Also, the evaluation of happiness and values related to actions is possible as soon as an actions has been suggested.
A single person can only suggest and vote for
- one issue per day;
- one action per issue;
- one progress measure per action and value;
- and one happiness measure per action for their own group;
- and a player can only belong to one group.

Game results

See the top of the page for the main questionnaire of the game. Here we present results from the game.

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#This is code Op_en7421/ on page [[Great game of Turkey]]

library(OpasnetUtils)
library(ggplot2)

objects.latest("Op_en7421", code_name = "initiate")
objects.latest("Op_en6007", code_name = "answer") # oggplot etc

BS <- 24

happindex <- EvalOutput(happindex)
valindex <- EvalOutput(valindex)

ggplot(happindex@output, aes(x = Date, y = happinessResult, colour = Group, group = Group)) + geom_point() + facet_grid(Decisionmaker ~ .) + theme_gray(base_size = BS)

ggplot(valindex@output, aes(x = Date, y = valuesResult, colour = Value, group = Value)) + geom_point() + facet_grid(Decisionmaker ~ .) + theme_gray(base_size = BS)

oggplot(happindex, x = "Date", fill = "Group") + facet_wrap(~ User) + labs(title = "Happiness per day") +
	theme(axis.text.x = element_text(angle = 90, hjust = 1)) # Turn text and adjust to right

happmean <- oapply(happindex, cols = c("Date", "Issue", "Action"), FUN = mean)
happequity <- oapply(happmean, cols = "Group", FUN = sd)

oggplot(mergeusers(happmean), x = "Decisionmaker", fill = "Group") + labs(title = "Mean happiness during the whole period")
oggplot(mergeusers(happequity), x = "Decisionmaker") + labs(title = "Deviation from the equity")

valmean <- oapply(valindex, cols = c("Date", "Issue", "Action"), FUN = mean)
valequity <- oapply(valmean, cols = "Issue", FUN = sd)

oggplot(mergeusers(valmean), x = "Decisionmaker", fill = "Issue") + labs(title = "Mean values over time")
oggplot(mergeusers(progequity), x = "Decisionmaker") + labs(title = "Deviation from the policy balance")

Setup profile

Setup your profile. Do this before you start. You may change your preferences later.

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# This is code Op_en7421/choices on page [[Great game of Turkey]]
# Paramters:
## group: selection (text string)

library(OpasnetUtils)

dat <- data.frame(
	User = wiki_username, 
	Group = group,
	Result = as.numeric(Sys.time())
)

opbase.upload(
	dat, 
	ident = "Op_en7421", 
	name = "Great game of Turkey", 
	subset = "User", 
	act_type = "append", 
	language = "eng", 
	who = wiki_username
)

oprint(dat, include.rownames = FALSE)

cat("Your group was successfully saved.\n")

test <- opbase.data("Op_en7421", subset = "Bonuses")$User
if(!wiki_username %in% test) {
	dat <- data.frame(
		User = wiki_username, 
		Reason = "Seed",
		Bonus = 1,
		Result = as.numeric(Sys.time())
	)

	opbase.upload(
		dat, 
		ident = "Op_en7421", 
		name = "Great game of Turkey", 
		subset = "Bonuses", 
		act_type = "append", 
		language = "eng", 
		who = wiki_username
	)

	oprint(dat, include.rownames = FALSE)

	cat("Your seed bonus was successfully saved.\n")
}

Suggest issues and actions

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# This code is Op_en7421# on page [[Great game of Turkey]]
# Parameters:
## date: date type
## all: logical (if TRUE, show all days)

library(OpasnetUtils)

objects.latest("Op_en7421", code_name = "initiate")

temp <- EvalOutput(allactions)
if(!all) temp <- temp[temp$Date == as.character(date) , ]
colnames(temp@output)[colnames(temp@output) == "allactionsResult"] <- "Votes"

if(nrow(temp@output) == 0) {
	cat("Issues not found for that time.\n")
} else {
for(i in sort(unique(paste(temp$Date, temp$Issueid)))) {
  temp2 <- temp[paste(temp$Date, temp$Issueid) == i , ]
  cat(
    as.character(temp$Date[1]),
    "Issue", 
    as.character(temp2$Issueid[1]), 
    ":", 
    as.character(temp2$Issue[1]), 
    "\n", 
    as.character(temp2$Issuedescription[1]), 
    "(", as.character(temp$issuevoteResult)[1],
    "votes).\n"
  )
  oprint(temp2[ , c("Action", "Actiondescription", "Actionid", "Votes")], include.rownames = FALSE)
}
}

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# This is code Op_en7421/ on page [[Great game of Turkey]]
# Parameters:
## date: date type. Default: today
## issue: textbox (text string)
## description: textbox(text string)

library(OpasnetUtils)

objects.latest("Op_en7421", code_name = "initiate")

bonus <- EvalOutput(bonuses)
bonus <- result(bonus)[bonus$User == wiki_username]

dat <- data.frame(
	Date = as.character(date),
	Issue = issue,
	Issuedescription = description,
	User = wiki_username, 
	Result = as.numeric(Sys.time())
)

opbase.upload(
	dat, 
	ident = "Op_en7421", 
	name = "Great game of Turkey", 
	subset = "Issues", 
	act_type = "append", 
	language = "eng", 
	who = wiki_username
)

oprint(dat, include.rownames = FALSE)

cat("Your issue was successfully saved.\n")

dat <- data.frame(
	Date = as.character(date),
	Issue = issue,
	User = wiki_username, 
	Ivotes = bonus,
	Result = as.numeric(Sys.time())
)

opbase.upload(
	dat, 
	ident = "Op_en7421", 
	name = "Great game of Turkey", 
	subset = "Issuevote", 
	act_type = "append", 
	language = "eng", 
	who = wiki_username
)

oprint(dat, include.rownames = FALSE)

cat("The issue was also voted for with your bonuses.\n")

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# This is code Op_en7421/ on page [[Great game of Turkey]]
# Parameters:
## issue: numeric (Issueid)
## action: textbox (text string)
## description: textbox (text string)

library(OpasnetUtils)

objects.latest("Op_en7421", code_name = "initiate")

bonus <- EvalOutput(bonuses)
bonus <- result(bonus)[bonus$User == wiki_username]

temp <- EvalOutput(allactions)
temp <- temp[temp$Issueid == issue , ] 

#if(!issue %in% issueofday$Issueid) stop("Issue not found")

dat <- data.frame(
	Issue = temp$Issue,
	Action = action,
	Actiondescription = description,
	User = wiki_username, 
	Result = as.numeric(Sys.time())
)

opbase.upload(
	dat, 
	ident = "Op_en7421", 
	name = "Great game of Turkey", 
	subset = "Actions", 
	act_type = "append", 
	language = "eng", 
	who = wiki_username
)

oprint(dat, include.rownames = FALSE)

cat("Your action was successfully saved.\n")

dat <- data.frame(
	Issue = temp$Issue,
	Action = action,
	User = wiki_username, 
	Avotes = bonus,
	Result = as.numeric(Sys.time())
)

opbase.upload(
	dat, 
	ident = "Op_en7421", 
	name = "Great game of Turkey", 
	subset = "Actionvote", 
	act_type = "append", 
	language = "eng", 
	who = wiki_username
)

oprint(dat, include.rownames = FALSE)

cat("The action was also voted for with your bonuses.\n")

Vote for issues and actions

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# This is code Op_en7421/ on page [[Great game of Turkey]]
# Paramters:
## issue: numeric (Issueid)

library(OpasnetUtils)

objects.latest("Op_en7421", code_name = "initiate")

bonus <- EvalOutput(bonuses)
bonus <- result(bonus)[bonus$User == wiki_username]

temp <- EvalOutput(allactions)
temp <- temp[temp$Date == as.character(Sys.Date()) & temp$Issueid == issue , ]

dat <- data.frame(
	Date = temp$Date[1],
	Issue = temp$Issue[1],
	User = wiki_username, 
	Ivotes = bonus,
	Result = as.numeric(Sys.time())
)

opbase.upload(
	dat, 
	ident = "Op_en7421", 
	name = "Great game of Turkey", 
	subset = "Issuevote", 
	act_type = "append", 
	language = "eng", 
	who = wiki_username
)

oprint(dat, include.rownames = FALSE)

cat("Your issue vote was successfully saved.\n")

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# This is code Op_en7421/ on page [[Great game of Turkey]]
# Parameters:
## action: numeric (Actionid)

library(OpasnetUtils)

objects.latest("Op_en7421", code_name = "initiate")

bonus <- EvalOutput(bonuses)
bonus <- result(bonus)[bonus$User == wiki_username]

temp <- EvalOutput(allactions)
temp <- temp[temp$Date == as.character(Sys.Date()) & temp$Actionid == action , ]

dat <- data.frame(
	Issue = temp$Issue,
	Action = temp$Action,
	User = wiki_username, 
	Avotes = bonus,
	Result = as.numeric(Sys.time())
)

opbase.upload(
	dat, 
	ident = "Op_en7421", 
	name = "Great game of Turkey", 
	subset = "Actionvote", 
	act_type = "append", 
	language = "eng", 
	who = wiki_username
)

oprint(dat, include.rownames = FALSE)

cat("Your action vote was successfully saved.\n")

Evaluate happiness and values

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# This is code Op_en7421/happiness on page [[Great game of Turkey]]
# Parameters:
## action: numeric (Actionid)
## hscore: numeric (integer from -2 to 2)

library(OpasnetUtils)

objects.latest("Op_en7421", code_name = "initiate")

temp <- EvalOutput(allactions)
temp <- temp[temp$Actionid == action , ]
cat(as.character(temp$Issue), ":", as.character(temp$Action), "\n")

user1 <- EvalOutput(user)
user1 <- user1[user1@output$User == wiki_username , ]

dat <- data.frame(
	Issue = temp$Issue,
	Action = temp$Action,
	Group = user1$Group,
	User = user1$User, 
	Hscore = hscore, # Happiness score
	Result = as.numeric(Sys.time())
)

opbase.upload(
	dat, 
	ident = "Op_en7421", 
	name = "Great game of Turkey", 
	subset = "Happiness", 
	act_type = "append", 
	language = "eng", 
	who = wiki_username
)

oprint(dat, include.rownames = FALSE)
cat("Your happiness score was successfully saved.\n")

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# This is code Op_en7421/value on page [[Great game of Turkey]]
# Parameters:
## action: numeric (Actionid)
## value: selection (text string)
## vscore: numeric (integer from -2 to 2)

library(OpasnetUtils)

objects.latest("Op_en7421", code_name = "initiate")

temp <- EvalOutput(allactions)
temp <- temp[temp$Actionid == action , ]

cat(as.character(temp$Issue), ":", as.character(temp$Action), "\n")

dat <- data.frame(
	Issue = temp$Issue,
	Action = temp$Action,
	Value = value,
	User = wiki_username, 
	Vscore = vscore,
	Result = as.numeric(Sys.time())
)

if(!is.na(vscore)) {
	opbase.upload(
		dat, 
		ident = "Op_en7421", 
		name = "Great game of Turkey", 
		subset = "Values", 
		act_type = "append", 
		language = "eng", 
		who = wiki_username
	)
	oprint(dat, include.rownames = FALSE)
	cat("Your progress score was successfully saved.\n")
} else {
	cat("Choose your score first.\n")
}

There is no need to edit the wiki page. Everything can be written into the text slots and uploaded by pressing the respective buttons. You can also create a full day's simulated activity in tables and copy-paste those directly. There is an example file that I used for uploading today's game at the end of the page.

Rationale

Calculations

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#This is code Op_n7421/ on page [[Great game of Turkey]]
# Parameters:
## subset: text (name of the Opasnet Base table)
## dat: table (automatically onverts to data.frame. Must have the structure of the database table)

library(OpasnetUtils)

colnames(dat) <- as.matrix(dat)[1 , ]
dat <- dat[2:nrow(dat) , ]
oprint(dat)

opbase.upload(
	dat, 
	ident = "Op_en7421", 
	name = "Great game of Turkey", 
	subset = subset, 
	act_type = "append", 
	language = "eng", 
	who = wiki_username
)

cat("Data uploaded successfully.\n")

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# This is code Op_en7421/initiate on page [[Great game of Turkey]]

library(OpasnetUtils)

issueofday <- Ovariable("issueofday",
  dependencies = data.frame(Name = "allactions"),
  formula = function(...) {
    
    for(i in unique(allactions$Date)) {
      test <- allactions[allactions$Date == i , ]
      test <- test[order(-test$issuevoteResult) , c("Date", "Issue")][1 , ] # Choose the 1 row with most votes
      if(exists("issday")) issday <- combine(issday, test) else issday <- test
    }
    
    for(i in unique(allactions$Issueid)) {
      test <- allactions[allactions$Issueid == i , ]
      test <- test[order(-result(test)) , ][1:2 , ] # Action votes are the result column of allactions
      if(exists("actday")) actday <- combine(actday, test) else actday <- test
    }
    return(merge(merge(issday, actday), allactions))
  }
)

# Day is only selected afterwards. Action and issue selection based on votes is done in issueofday.
allactions <- Ovariable("allactions",
  dependencies = data.frame(Name = c("issues", "issuevote", "actions", "actionvote")),
  formula = function(...) {
    
    issues$Issueid <- 1:length(result(issues))
    iss <- oapply(issuevote, cols = "User", FUN = sum) # Sum votes for each issue across users
    iss <- merge(issues, iss)
    iss$User <- NULL

    actions$Actionid <- 1:length(result(actions))
    act <- oapply(actionvote, cols = "User", FUN = sum)
    act <- merge(actions, act)
    act$User <- NULL
    out <- merge(iss, act, all.x = TRUE)
    out@name <- "actionvote"
    return(out)
  }
)

uniques <- function(subset) {
  #Create a temporary ovariable temp and fetch the respective table with ddata.
  #indices that are used to find unique rows: 
  uncolumns <- c("Date", "Issue", "Action", "User", "Value", "Reason")
  #However, take away the index that is being added: 
  #Issue (for Issuevote and Issues); Action (for Actionvote and Actions). None for other tables.
  addindex <- NULL
  if(subset %in% c("Issues", "Issuevote")) addindex <- "Issue"
  if(subset %in% c("Actions", "Actionvote")) addindex <- "Action"
  uncolumns <- uncolumns[!uncolumns %in% addindex]
  #indices that are transformed to Result: 
  rescolumns <- c("Ivotes", "Avotes", "Bonus", "Vscore", "Hscore")

  dat <- opbase.data("Op_en7421", subset = subset)
  temp <- aggregate(dat["Result"], by = dat[colnames(dat) %in% uncolumns], FUN = max) 
  out <- merge(dat, temp)
  out$Result <- NULL
  colnames(out)[colnames(out) %in% rescolumns] <- "Result"
  if(!"Result" %in% colnames(out)) out$Result <- 1
  out$Result <- as.numeric(as.character(out$Result))
  return(out) 
}

# dummy is needed to get correct marginals in downstream ovariables.
dummy <- Ovariable("dummy", 
  data = data.frame(Date=1, Issue=1, Action=1, User=1, Value=1, Group=1, Reason=1, Result=1)
)

issues <- Ovariable("issues", 
  dependencies = data.frame(Name = c("dummy")),
  formula = function(...) {
    return(uniques("Issues"))
  }
)

actions <- Ovariable("actions", 
  dependencies = data.frame(Name = c("dummy")),
  formula = function(...) {
    return(uniques("Actions"))
  }
)

issuevote <- Ovariable("issuevote", 
  dependencies = data.frame(Name = c("dummy")),
  formula = function(...) {
    return(uniques("Issuevote"))
  }
)

actionvote <- Ovariable("actionvote", 
  dependencies = data.frame(Name = c("dummy")),
  formula = function(...) {
    return(uniques("Actionvote"))
  }
)

decisions <- Ovariable("decisions", 
  dependencies = data.frame(Name = c("dummy")),
  formula = function(...) {
    return(uniques("Decisions"))
  }
)

values <- Ovariable("values", 
  dependencies = data.frame(Name = c("dummy")),
  formula = function(...) {
    return(uniques("Values"))
  }
)

happiness <- Ovariable("happiness", 
  dependencies = data.frame(Name = c("dummy")),
  formula = function(...) {
    return(uniques("Happiness"))
  }
)

bonuses <- Ovariable("bonuses", 
  dependencies = data.frame(Name = c("dummy")),
  formula = function(...) {
    dat <- opbase.data("Op_en7421", subset = "Bonuses")
    dat$Bonus <- as.numeric(as.character(dat$Bonus))
    dat <- aggregate(dat["Bonus"], by = dat["User"], FUN = sum)
    colnames(dat)[colnames(dat) == "Bonus"] <- "Result"
    return(dat)
  }
)

user <- Ovariable("user", 
  dependencies = data.frame(Name = c("dummy")),
  formula = function(...) {
    return(uniques("User"))
  }
)

mergeusers <- function(happ) {
  if(length(happ$User) != length(happ$User[happ$User == wiki_username])) {
    happ$Decisionmaker <- ifelse(happ$User == wiki_username, "You", "Crowd")
  }
  return(happ)
}

deci <- Ovariable("deci",
  dependencies = data.frame(Name = "decisions"),
  formula = function(...) {
    deci <- mergeusers(decisions)
    deci <- oapply(deci, cols = "User", FUN = length)
    for(i in unique(paste(deci$Date, deci$Issue))) {
      test <- deci[paste(deci$Date, deci$Issue) == i , ]
      test <- test[order(-test$decisionsResult) , ][1 , ] # Choose the 1 row with most decisions
      if(exists("out365")) out365 <- combine(out365, test) else out365 <- test
    }
    return(out365)
  }
)

happindex <- Ovariable("happindex", 
   dependencies = data.frame(Name = c(
     "happiness",
     "deci",
     "actions"
   )),
   formula = function(...) {
     actions$User <- NULL
     happindex <- oapply(happiness, cols = "User", FUN = mean)
     happindex <- deci * happindex * actions
     return(happindex)
   }
)

valindex <- Ovariable("valindex", 
  dependencies = data.frame(Name = c(
    "values",
    "deci",
    "actions"
  )),
  formula = function(...) {
    actions$Result <- NULL
    valindex <- oapply(values, cols = "User", FUN = mean)
    valindex <- deci * valindex * actions
    return(valindex)
  }
)

objects.store(list = ls())
cat("Objects", ls(), "stored successfully.\n")

Structure and functionalities

The content of and use of the data tables is the following:

Issues: List of decisions to be made. A user can suggest only one issue per day. For each day, the most popular issue is taken to the game.
Actions: List of decision options to be made. A user can suggest only one action per issue. For each time point, two most popular actions are taken to the game. However, the actions in the game may change during the day, if the rank of the issues changes.
Issue vote: List of votes for each issue. Each user can cast a single vote either for or against an issue. The number of votes a user has equals their bonuses.
Action vote: List of votes for each action under issues. The voting system is the same as for issues.
Decisions: List of decisions each user makes from the actions and issues on the game.
Bonuses: List of bonuses the users have earned during the game. In the beginning, each user has 1 bonus. You can earn bonuses if your actions suggestions gets to be played (+1) or if your issues gets to be played (+5). Every time a user makes a decision, they get +0.1 bonus.
Happiness: Users' opinions about how much happiness an action brings to their own group.
Values: Users' opinions about how much value an action brings to a selected group.
Users: List of users' groups (i.e. to which group each user identifies themselves).

The functions needed are the following.

Upload data: Take the data provided by the user or calculated. Add automatic fields, e.g. ts, user and date. Upload data to the respective table.
Create ovariable: Download data from a table. From the data, find the unique rows with a given condition (e.g. discard previous decisions made by a user previously on the same day). Then create an ovariable with the structure needed.
Firstuser: Check's whether user's wiki_username is found from Bonuses. If not, it is added there and 1 bonus given.

The interface codes used are the following:

Suggest issues: Ask date, issue and description from user. Date means the date when this issue will be played. Default is today, but user can change that and suggest future issues. Timestamp (ts) come automatically. User is the wiki_username. Upload data to Issues table. No need to check previous entries. Upload user's bonus to Issue vote as number of votes.
Show issues: Ask date (today by default) and show all issues and each one's actions listed from the most to least popular. This is necessary for suggesting actions.
Show today's issue: Ask nothing. Show today's top-ranked issue and its two top-ranked actions. [Calculate the sum of results over all users. Show these popularity sums as the result of object popularity? Select the most popular row among a group defined by an index; use oapply to integrate over the index using which.max and pick that row only. Should this be a function or ovariable?]
Suggest actions: Ask date, issue, action and description from user. Date is today by default. Ts and user come as previously. If the date-issue pair does not exist in Issues table, give error message. Upload data to Actions and user's bonus to Action vote.
Vote for issue: Ask the rank number of the issue as a number. The user can check the numbers with Show issues. Date, user, and ts come automatically. Do firstuser. Votes is the number of user's bonuses and comes from Bonuses. Upload data to Issue vote. Store information about the rank before voting somewhere (as an ovariable or a technical data table?). If the information has changed from the last time, give bonus to the user whose information is now on the top.
Vote for action: Similar to vote for issue, except that the action number is asked and data is uploaded to Action vote.
Make decision: Ask the action from the two top choices of the most popular issue using a drop-down list. The options can be seen with show today's issue. Upload data to Decisions. However, if an issue was the most popular at some point during the day, it is still kept in the issue list. ----#: . Is it? How? --Jouni (talk) 17:21, 7 February 2016 (UTC) (type: truth; paradigms: science: comment)
Evaluate happiness: Ask date (today is the default), action number from show issues for that date, and hscore for happiness score in the user's own group. Ts, user as previously. Check if user has a group in Users and if not, give an error message to sign up to a group first. Upload data to Happiness.
Evaluate values: As evaluate happiness, except that unlike group, the value is asked from the user and nothing is checked. Upload data to Values.
Manage profile: Ask the group to which user identifies themselves. Take user and ts as previously. Add data to Users.
Show results: This code is divided into several parts:
- Show happiness performance: Ask nothing. From Decisions, take the action of each day; do this separately for You, the user's own decisions, and Crowd, i.e. the most popular action of each day. Combine that with the happiness scores from Happiness. Show cumulative happiness across time for both decision makers.
- Show value performance: Similar to show happiness performance, but for values from Values. It is imprtant to notice that value scores for each action are only partly a matter of opinion and partly a matter of research. Therefore, ideas should be developed how this research is gathered and used.
- Show situation': Show the situation of the current issue: the issue and description, and the two actions and their votes.
- Show all issues: Show all issues and actions and their votes for today.

**Important categories**
Groups for Turkey	Value categories
Nationalists Conservatives Minorities Liberals Kemalists	Civil Rights Women's Rights Religion National Values Democracy

Keywords

References

Related files

Great game of Turkey seed data Example data to be copied in for a new day.

Great game of Turkey

Contents

Question

Answer

Game results

Setup profile

Suggest issues and actions

Vote for issues and actions

Evaluate happiness and values

Rationale

Calculations

Structure and functionalities

See also

Keywords

References

Related files

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