Political Scorecards Canada – How they’re scored
The Scorecard
The scorecard is a tool to help you decide if your elected representative is worthy of your support, stands up and protects our shared natural rights and the principles of a free and open society.
How the Score is Generated
In each province we identify these four critical Key Areas of Measurement that have impact on individual politicians scorecards as a green Star or check mark or a Red X, Pass or Fail. on individual Scorecards and our rights and freedoms:
- Public commitment (Pledge)
- Votes on critical legislation (Current and Past)
- Verifiable Public Statements.
- Questionnaire Responses
If you see a Green Checkmark (pass), a Red X (fail) or a Yellow Caution Sign each indicates a commitment, voting position or public record that either supports or undermines our fundamental rights and inherent freedoms .
The performance scorecards for politicians are calculated using four primary data sources:
1. Pledging to safeguard our rights and freedoms. (20%)
2. Historical voting records – current voting records. (50%)
3.Verifiable positions taken in the public domain. (15%)
4. Responses to periodic Questionnaires. (15%)
Each data point is weighted according to its importance in protecting and upholding our rights and freedoms, with a focus on legislation critical to these principles. This system aggregates the weighted data to generate a percentage score that determines what is presented on a politicians individual “Scorecard” – Perfromance Report.
(BC Legislative Bills referenced below are examples)
# Weighting:
Weight assigned by Severity Index. Votes are either YES, NO or ABSENT.
# Severity level:
/Impact level: Positive or Negative 1 TO 3 Max = *** or ***
( RED * = legislation with negative impacts, GREEN * = legislation with positive impacts.)
(Red/Green Vote can be any combination of vote and colour. Absent always=yellow)
# Record Criteria:
#1.) dtAll %<>% addCriteria (“Pledge Record“, criteriaPledge)
criteriaPledge <- list ( “Pledged”, 3, 0, -3)
#2.) dtAll %<>% addCriteria (“Current Voting Record“, criteriaCurrent)
criteriaCurrent <- list
( “Bill 31”, -3, -1, 3, *** (example: -3 in favour, -1 absent – did not participate, 3 against)
“Bill 36”, -3, -1, 3, ***
“Bill 44”, -1, -1, 2, **
“Bill 46”, -1, -1, 2, **
“Bill 47”, -1, 0, 1) * (example: -1 in favour, 0 absent – unanimous on division, 1 against)
dtAll %<>% addCriteria (“Past Voting Record“, criteriaPast)
dtAll$`Bill 19, 2020` %>% as.ordered %>% summary
criteriaPast <- list
( “Bill 19, 2020”, -3,-1,3, ***
“Motion 3, 2023”, -3,-1,3, ***
“Bill 37, 2008”, -1,-1, 2, **
“Bill 41”, -3,-1,3) ***
#3.) dtAll %<>% addCriteria (“Public Event Record“, criteriaPublic )
criteriaPublic <- list(
“RnF Alignment”, -3, 0, 3
) (Max 5 Events = 100%)
#4.) Responses to questionnaires.
#Final Sort:
dtAll$`Pledge Record (%)` %>% sort
dtAll$`Current Voting Record (%)` %>% sort
dtAll$`Past Voting Record (%)` %>% sort
dtAll$`Public Record (%)` %>% sort