We have looked at both the CIPS data, as we did in 2002 and 2010 and 2012, and the contact card or street check data, as we did in 2010 and 2012.

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1 August 7, 2013 Dear Chief Blair, We have had another look at updated contact card and arrest data Through an FOI, we requested the updated data, which covers 2008 to end of As we did the last time, we have prepared a summary (attached) of our preliminary findings. We hope to meet with you to discuss the findings sometime soon. We have looked at both the CIPS data, as we did in 2002 and 2010 and 2012, and the contact card or street check data, as we did in 2010 and New this time: By officer: A look at contact cards by officer, unit, platoon and area. Due to data limitations, it was not previously possible to look at this over time. A standard deviation analysis of street checks by officer controlling for unit, platoon and patrol area shows there are more than 500 officers with proportionately higher ratios of contacts cards, by particular skin colours, when compared to peer benchmarks. Interestingly, there are officers with higher ratios in each of the four skin colour categories, and some with higher ratios in more than one skin colour category. Internal benchmarking is a tool used by other services in flagging potential problems. We would like to hear from you on why groups of officers card at significantly higher rates for people with a certain skin colour than their peers. We d also like to know if the service looks at carding by skin colour for individual officers, and, if not, would the service have any interest in doing so. Where people live: An analysis of where people who are carded live, versus where they were carded. Police analysts, as per our request, added data fields that indicate home city, and where the home city is Toronto, also a home patrol zone. We have found that half of the people documented between 2008 and 2012 were stopped and questioned in their home patrol zone or in a zone that was close (within 5 kms) to their home patrol zone. We d like to re-visit the question of whether you believe it may be possible that police in certain areas have documented every young person of colour who lives there. No skin colour noted: We re noticing that the number of street checks where no skin colour is noted is rising. We d like to hear your thoughts on why this is happening. Carding on the rise: Between 2008 and end of 2012, the number of street checks has increased 23 per cent. Given all of the critical attention the practice has received and with an internal review of police operations underway and changes coming, we would like to hear your thoughts on what will change with regards to carding, or street checks, now known as community inquiry reports. An officer s take: A former Toronto police officer who recently left the service has provided us with his views on street checks and how and why they are conducted. To summarize, he sees them as both necessary in some circumstances,

2 and as a form of harassment in other circumstances. He describes a system that encourages high card counts and rewards officers with timely access to training opportunities, which lead to scheduled promotions. In short, he describes an unofficial quota system, which we know is official in some divisions, such as 53 Division. The officer, in part, describes the carding process like this: It s a situation where we judge without knowing and to basically find out, we have to go and stop them. But we don t have a reason. So, hopefully, once we run them, we ll see that there have been contacts with police before. And that becomes our justification. But the truth of the matter is that we re pre-judging them, because we really don t know. The officer describes day shifts where officers are expected to keep contact card counts high, and as a result, we ll actually go out in the parks and whatever and we ll look for guys who fit a certain description, who may not be wearing fancy clothes, and we ll harass them, like literally. And we call it shakedown. We would like to hear your thoughts on this. Multiple credits: Our analysis has found that solo officers are receiving multiple credits on single street checks. We would like to know if this is a data glitch or if there are other reasons we are seeing this. Once again, we have done an analysis that looks at the number of young males aged 15 to 24 who have been documented by patrol zone between 2008 and end of 2012 and the populations of young males, aged 15 to 24, who live in those patrol zones. Ratios of black and brown over-representation remain consistent with our last analysis. As with our last analysis, it is the case that in every patrol zone in the city, the number of young black males documented over a period of several years (this is complicated in several instances by changes in patrol zone boundaries) outnumbers the population of young black males living there. While we again note that this does not mean that every young man of colour living in certain areas has been documented by police, the new home patrol zone data suggests 53 per cent of the people stopped and documented in Toronto live in or near (within 5 kms) of the patrol zone where they were stopped. The overall ratios of over-representation in carding data for blacks, regardless of age, remains the same. The proportion of cards of black people is three times greater than what black people represent in Toronto s population. If one looks at the latest New York City stop and frisk data and uses the same baseline population analysis, the overrepresentation of blacks in contact card data in Toronto is actually higher than it is for blacks and stop and frisks in NYC. Blacks remain more likely to be stopped than whites in each of the city s patrol zones. Caveat: Please note that Statistics Canada data was used to calculate populations by patrol zone. We have used the same methodology as we did in 2002, 2010 and 2012 to classify population skin colour as either white, black, brown or other in order to compare with the skin colour classifications in the police data. Because of boundary changes, effective September 2011, we have adjusted the analysis, where appropriate, to reflect the changes. Page 2 of 26

3 Looking at the CIPS data, with some variation, it appears there has been little change in the way people identified as black are treated. For example, blacks are much more likely to be ticketed for out-of-sight driving offences than whites. Also in CIPS, we see that blacks are still more likely to be held for bail than whites when facing a simple drug possession charge. However, due to a change in the way the data was released to the Star, we are no longer able to make meaningful comparisons in the current drug possession analysis to past Star analyses. Also unchanged in CIPS, we see that, when compared to their baseline population, blacks are charged for certain criminal offences, including those for serious violent allegations, at a rate higher than their baseline population in census data. We would like to hear your thoughts on these and other issues in the data analysis that follows. We are well aware that the service is conducting an internal review of operations and that you or may not currently be in a position to discuss what is being looked at when it comes to carding, but we would of course like to hear about any plans. We are available to meet whenever it is convenient for you and, as always, look forward to doing so. Sincerely, Andrew Bailey, Data Analyst Hidy Ng, Mapping Specialist Jim Rankin, Reporter Patty Winsa, Reporter Toronto Star Main contact: Jim Rankin jrankin@thestar.ca Page 3 of 26

4 Preliminary Toronto Star Analysis of CIPS/FIR Quick Background The Star tailored its request in order to avoid personal information, and, in an effort to ensure that charge information could not be used to identify an individual in CIPS, offences have been re-coded by the Star into a couple dozen non-descript offence categories. The TPS, as the Star requested, has released the data in a form that, although not perfect, allows for an analysis of people who are arrested and/or documented multiple times. In other words, if Jim Rankin has been arrested five times and also stopped and documented 15 times, we know that this is the same Jim Rankin, identified not by name but by a unique, random number created by police. The updated data covers a period from 2008 to end of Skin colour is identified by police as being either White, Black, Brown, or Other. We have used updated projected Census data to compare rates we are seeing in the police data to baseline populations in Toronto proper. Skin colour % Black 8.1% White 54.1% Brown (S. Asian, W. Asian, Arab) 14.3% Other 23.6% Total 100.0% Where skin colour was part of the Star analysis, police entries that did not have skin colour specified were excluded. We ve divided the findings into two parts. One deals with the Field Information Report (FIR) database analysis; the second, with the Criminal Information Processing System (CIPS) database. Page 4 of 26

5 1. Field Information Report (FIR) Analysis On the rise After peaking in 2007 and dropping in 2008, the number of contact cards has steadily risen through to the end of Cards with no skin colour entered increased by 16 per cent from 2011 to 2012, while black cards decreased by 3 per cent. Overall, the number of cards filled out annually has risen 23 per cent from 2008 to Since 2005, the year Bill Blair became chief and Toronto experienced the so-called year of the gun, the number of cards has risen by 62 per cent. The number of 2012 cards 397,713 is just shy of 2007 levels, the top year for card counts in the past decade. SKINCOLOUR Total Blank 154,735 25,864 20,529 30,396 36,161 41,785 Black 418,507 72,831 84,160 87,659 88,301 85,556 Brown 278,920 51,003 53,767 55,077 59,749 59,324 Other 112,096 17,392 19,705 22,293 24,975 27,731 White 861, , , , , ,317 1,825, , , , , ,713 Count of PREVIOUS YEARS Contacts , , , , ,747 Page 5 of 26

6 The number of individual people carded each year also continues to rise. Count of Unique YEAR Individuals Page 6 of 26

7 Blacks more likely than whites to be documented Not much has changed since our last analysis of cards. Using updated census population figures as a baseline, blacks in Toronto remain three times more likely than whites to be carded. Looking at patrol zones, it remains the case that blacks are more likely than whites to be documented in each of the city s patrol zones. We have looked at this for the period before boundaries were changed, and afterward. Using this formula for each zone: (black cards/total cards) / (black population/total population) (white cards/total cards) / (white population/total population) Below are some of the highest likelihood differences.. Likelihood Black to White Citywide 3 Highest Zones (Pre) Zone Likelihood Highest Zones (Post) Zone Likelihood Page 7 of 26

8 Young men: Documented vs. population within patrol zones We looked in the past at individuals documented vs. actual populations in the patrol zones, from 2008 to mid This was complicated this time by the fact the boundaries changed in late Last time, we looked specifically at young males, aged 15 to 24, by the four skin colour categories, within each of the patrol zones. The data allowed us to control for individuals who were carded multiple times. For that analysis, we looked at individuals who were carded at least once during this three and a half year period in individual patrol zones. We also pulled census data and calculated the populations of young men within each patrol zone, according to the four skin colour categories. Using this formula for each patrol zone: Unique individuals carded by skin colour Patrol zone population by skin colour We produced ratios for each patrol zone for each group of young males, by skin colour. For white young males, the ratios ranged from 23:1 in zone 523 to 0.3:1 in zone 325, but most zones had a ratio of between 1:1 and 2:1. For black males, it ranged from 252:1 in zone 523 to 1.9:1 in zone 424, with most zones in the range of 4:1 to 8:1. For brown young men, the ratios range from a high of 65:1 in zone 523, to a low of 1.2:1 in zone 233. Most zones had a ratio of 2:1 to 8:1. For young men in the other skin colour group, the ratios range from 7.5:1 in zone 523 to 0.2:1 in zone 331. Most zones have a ratio of less than one to one. Page 8 of 26

9 The same analysis for the entire city controlling for individuals who have been carded multiple times, and in multiple patrol zones. Again, this is for the period from 2008 to mid Young Black cards Young Black Men carded Black Cards per young black male carded Black Males in Toronto Black Card Ratio 111,383 46, , Young Brown cards Young Brown Men carded Brown Cards per young brown male carded Brown Males in Toronto Brown Card Ratio 77,289 39, , Young White cards Young White Men carded White Cards per young white male carded White Males in Toronto White Card Ratio 134,558 80, , Young Other cards Young Other Men carded Other Cards per young other male carded Other Males Other Card Ratio 17,396 13, , These numbers, of course, have not changed, but we felt it was not possible to make a meaningful calculation looking at the new data from the post re-drawing of boundaries. As suggested earlier, this analysis raises the question of whether it is possible that, in certain areas of the city, every young black man and brown in some zones may have been stopped and documented by police during this time frame. But it does not, of course, answer it. Page 9 of 26

10 Carding location vs. home location In an attempt to better explore the extent to which young men in particular have been documented in their home neighbourhoods, we asked police to provide home patrol zone or home city data for individuals. As the patrol zones cover areas ranging from 0.62 to 32.9 square kilometres (zones 513 and 424, respectively), there is no way to determine where within the patrol zones incidences occur, or where in a patrol zone those carded live. Therefore, based on the principle that distance is the shortest separation between two points, we calculated the closest point of every patrol zone to all the other patrol zones. Thus, adjacent patrol zones are given a distance of 0 km between them. This was also done based on the supposition that most people are documented near where they live. To accommodate the boundary changes that occurred on September 26 th, 2011, we divided the data into two sets. The first set reflects the old boundaries, with contact cards given from January 1, 2008 to September 25 th, The second set reflects the new boundaries, and contains those records from September 26 th, 2011 to December 30 th, We did not use those records where incidences occurred before January 1, 2008, leaving us with 1,824,311 records in total, between the two sets of data. Of those 1,824,311 unique carding records, 61% (1,114,612 records) contained both the zone which the card was given, as well as the home patrol zone of the person carded. Using that 61% as the universe, we determined that 461,673 incidences occurred where they were given to those in their home patrol zone (41%) and the remainder of the incidences (652,939, or 59% of the universe) occurred outside of the carded person s home patrol zone. To put it another way, 25 per cent of people carded (461,673 of 1,824,311) were carded in their home patrol zone. A further 17 per cent of people carded (303,156 of 1,824,311) lived in an area adjacent to the patrol zone where they were carded. Another 11 per cent were carded (193,684 of 1,824,311) in a patrol zone that is not adjacent but is close to their home patrol zone. Looking at this group as a whole, the data shows that half (53 per cent) of the people documented live in or within 5 kms to the patrol zone where they were carded. Below are tables showing more detailed findings of the old set of boundaries, and the new set of boundaries. It s important to note that these tables look only at those who had a home patrol zone other than the patrol zone where they were stopped. They do not include those who were stopped in their home patrol zone. January 1, September 25, 2011 In this set of data, we can see in the data that 58.6% of the contact cards were for individuals outside of their home patrol zone. Of those cards outside of an individual s patrol zone, 46% were filled out in a patrol zone adjacent to the individual s home patrol Page 10 of 26

11 zone. Here is a detailed breakdown of the proximity of home patrol zone to the zone where the card was filled out. September 26, 2011 December 30, 2012 The change in boundaries did not appear to have any effect on the proportion of cards filled out in an individual s home patrol zone. We can see in the data that 58.5% of the contact cards were for individuals outside of their home patrol zone. This table shows a breakdown of the proximity of home patrol zone to the zone where the card was filled out. Page 11 of 26

12 Carding by individual officers The Star used standard deviation as a way of comparing how individual officers card. Standard deviation is a measure of how spread out numbers are. It s a measure of the dispersion of a set of data from its mean, or more simply, the average distance from the average. The more spread apart the data, the higher the deviation. The analysis takes into account volume of cards, location, unit, platoon and skin colour of the people they documented. The analysis compares individual officers to benchmarks set by their peer groups. Colour rates for officers were established measuring officers in the same unit, zone and platoon against each other. For example, when looking at an individual officer who is attached to TAVIS, we were able to calculate a benchmark set by fellow TAVIS officers who worked in the same patrol zones as that officer, and see how similar or dissimilar the officer s carding rates by skin colour were from his fellow TAVIS officers. The analysis considers two standard deviations or more above a peer benchmark as high. Only officers who carded 50 or more individuals in a given patrol zone between 2008 and 2012 were counted in this analysis. Only cards where the reason for contact was general investigation were included in this part of the Star analysis. The rationale behind that is that this category seems to be the most subjective of all of the reasons for contact. In all, 534 officers fell into the high categories for one or more skin colour group. There were 135 Toronto police officers who performed street checks of blacks in certain patrol zones of the city at a standard deviation of two or more higher than their peers. For street checks of people with brown skin, there were 169 officers who were that high. For street checks of people whose skin colour was classified as other, 190 officers were high. For people with white skin, there were 111 officers who had standard deviations of two or more higher than their peers. There were 68 officers who had high rates for more than one skin colour category. For a better comparison, the Star created a score for officers. This score was created by grouping all cards together by Unit, Zone and Platoon. We then counted cards by skin colour and an average rate was determined for each skin colour. We then grouped together all cards by Officer, Unit, Zone and Platoon. Cards were again counted by skin colour and rates were established for these individual officers inside a specific Unit, Zone and Platoon group. Officers had to have at least 50 total cards in a given Unit, Zone & Platoon to be included. These officer rates were then used to create a score using the following formula: ((Officer UnitZonePlatoon Colour Rate)-(Avg. UnitZonePlatoon Colour Rate)/(Standard Deviation of UnitZonePlatoon Colour Rates)) x OfficerUnitZonePlatoon Color Count Page 12 of 26

13 These officers had extremely high black rate scores compared to their colleagues (POC is the internal code for TAVIS): Officer Score OverallCountRank th most cards - POC rd highest - POC nd highest count - POC th highest - POC & D th POC & D rd D th D th - POC th D th D51 Other officers had high white rates: Officer Score OverallCountRank nd D th D th D14 Others had high brown rates: Officer Score OverallCountRank th D42 & POC th - POC th - POC th - POC High Other rates: Officer Score OverallCountRank th D th D th - POC Page 13 of 26

14 Officer patterns for the most part remain the same when looking at young male cards (ages 15-24). It should be noted that the data shows that officers who are not classified as POC or TAVIS are sometimes performing TAVIS duties outside of their home divisions. This does not significantly impact the scores. Partners were then assessed in the same manner individual officers were. These officers were in at least 5 partnerships with high black rates: Officer Partnerships We are interested to hear your thoughts on why these officers have rates different than their peers. Looking at the average ages of people carded where the nature of contact was general investigation, black and brown skinned were younger. SEX Black Brown Other White Total Female Male Page 14 of 26

15 Carding by unit Looking at all cards from 2008 to end of 2012, TAVIS (POC) officers have the highest card credits per officer of any other unit. Multiple officers can receive credits on a single card. UNIT Officers CardCredits Black Brown Other White Blank Card Credits/Officer POC , ,748 78,800 22, ,137 17, D ,782 42,102 38,435 11, ,375 16, D ,493 12,540 22,711 10,550 98,730 28, D ,352 44,031 24,279 26, ,622 19, D ,631 51,175 90,145 25,162 42,424 12, D ,000 35,018 11,632 9, ,633 7, D ,382 59,401 19,038 13, ,750 12, D ,756 54,851 55,530 7,437 71,333 19, D ,365 76,938 47,233 5,853 55,588 10, D ,954 23,683 17,354 11, ,402 18, D ,520 69,021 18,159 6,829 82,256 10, D ,650 23,941 13,683 5, ,648 15, D ,447 28,094 15,139 13,161 92,262 14, D ,459 37,391 37,051 8,454 78,042 18, D ,638 94,833 37,101 10,006 74,151 22, D ,765 33,640 9,718 5,863 71,181 8, D ,694 19,137 18,093 19,363 97,096 16, D ,788 22,501 21,016 15,643 55,936 10, TSV ,431 16,337 13,328 6,004 54,899 7, OSC ,971 5,249 3,073 1,542 17,704 1, MTD 95 8,810 1,120 1, , MAR 116 4, , ETF 117 3, , Page 15 of 26

16 General Investigation card credits Looking solely at general investigation cards from 2008 to end of 2012, TAVIS officers have the highest card credits per officer of any other unit. UNIT Officers CardCredits Black Brown Other White Blank Card Credits/Officer POC , ,948 63,732 18, ,409 15, D ,886 19,700 9,646 10,120 63,746 4, D ,444 12,001 11,203 2,962 39,112 4, D ,489 16,066 3,921 2,921 41,868 1, D ,207 30,663 6,880 2,446 33,981 4, D ,256 14,719 3,892 2,475 28,644 3, D ,815 9,224 5,740 3,745 43,113 3, D ,981 15,375 29,265 5,201 11,901 4, D ,186 23,719 5,659 4,257 40,726 1, D ,833 6,768 5,431 7,832 36,554 4, D ,988 17,261 15,901 1,688 20,907 5, D ,538 9,018 5,043 3,466 27,989 4, D ,153 11,946 10,737 2,026 25,585 4, D ,829 22,460 12,152 1,135 13,463 2, D ,442 7,613 3,855 1,180 31,963 2, D ,838 28,395 10,132 2,501 20,422 3, D ,727 2,632 5,361 1,523 18,046 3, OSC ,486 2,796 1, , D ,499 6,423 4,736 2,479 12,239 1, TSV ,106 3,438 2,084 1,307 11, MTD 84 2, , MAR 90 1, Page 16 of 26

17 Youth General Investigation card credits (ages 15-24) TAVIS officers are also most likely to be carding youth for general investigation. Card UNIT Officers CardCredits Black Brown Other White Blank Credits/Officer POC ,517 80,164 38,445 9,526 58,896 8, D ,053 6,322 6,782 1,263 15,053 1, D ,220 8,792 17,243 1,733 4,655 1, D ,584 13,718 2, ,475 1, D ,690 13,878 6, ,321 1, D ,841 6,863 1, ,228 1, D ,258 10,022 9, ,159 2, D ,934 5,363 2,821 1,751 14,031 1, D ,305 6,530 3,768 3,602 16,964 1, D ,075 4,392 3,097 1,296 12,901 1, D ,837 5,504 1,375 1,094 10, D ,015 4,185 1, ,241 1, D ,373 5,849 5, ,143 2, D ,017 14,980 4,899 1,154 8,405 1, D ,257 2,912 2,662 2,166 11,092 1, D ,539 3,803 2,856 1,223 5, OSC 125 6,894 1, , D ,323 1,122 3, , D ,522 6,067 1,844 1,011 7, TSV 244 6,164 1, , MTD 73 1, Page 17 of 26

18 TAVIS officers received credits for one out of every three youth cards where the nature of contact was general investigation (GI). UNIT GI Credits for Youth Cards Per cent of GI Youth Cards POC % D % D % D % D % D % D % D % D % D % D % D % D % D % D % D % D % D % OSC % TSV % Page 18 of 26

19 All cards by skin colour Looking at all cards, TAVIS has the highest black card credit rate per officer. The division with the highest incidence of cards for which there was no skin colour specified is 53 Division, followed by the marine unit. UNIT %Black %Brown %Other %White %Blank POC 40.0% 17.4% 5.0% 33.6% 4.0% D % 15.5% 4.2% 31.1% 9.4% D % 24.1% 3.0% 28.3% 5.5% D % 9.7% 3.7% 44.1% 5.5% D % 8.5% 6.0% 53.4% 5.6% D % 26.6% 3.6% 34.2% 9.4% D % 7.5% 4.6% 55.3% 6.5% D % 40.7% 11.4% 19.1% 5.7% D % 20.6% 4.7% 43.5% 10.3% D % 6.7% 5.2% 63.6% 4.4% OSC 18.1% 10.6% 5.3% 61.1% 4.8% D % 16.4% 4.9% 53.8% 6.9% D % 16.7% 12.4% 44.5% 8.5% D % 9.3% 8.1% 56.4% 9.0% TSV 16.6% 13.5% 6.1% 55.8% 8.0% D % 8.8% 9.4% 59.0% 7.0% D % 8.4% 3.2% 64.6% 9.2% D % 9.7% 6.3% 60.6% 10.2% MTD 12.7% 13.7% 5.6% 61.7% 6.3% D % 10.7% 11.4% 57.2% 9.4% D53 7.2% 13.1% 6.1% 56.9% 16.7% MAR 5.6% 10.5% 3.2% 66.5% 14.2% Page 19 of 26

20 General Investigation cards, by skin colour TAVIS also has the 3rd highest rate of general investigation cards for people with black skin. Divisions 31 and 23 had the highest black card credits per officer for general investigation. The division with the highest incidence of general investigation for which there was no skin colour specified is the marine unit, followed by 53 Division. UNIT %Black %Brown %Other %White %Blank D % 15.6% 3.9% 31.5% 5.2% D % 23.4% 2.2% 26.0% 5.1% POC 39.9% 17.1% 5.0% 33.8% 4.2% D % 8.8% 3.1% 43.5% 5.4% D % 7.4% 5.6% 53.5% 2.4% D % 26.1% 2.8% 34.3% 8.6% D % 7.3% 4.6% 53.8% 6.6% D % 5.9% 4.4% 63.0% 2.6% D % 17.2% 9.0% 44.5% 5.9% D % 44.4% 7.9% 18.0% 6.4% D % 19.5% 3.7% 46.4% 8.8% D % 8.9% 9.4% 59.1% 4.3% D % 10.2% 7.0% 56.5% 8.1% OSC 18.1% 11.1% 5.0% 59.4% 6.4% TSV 18.0% 10.9% 6.8% 60.3% 4.0% D % 16.1% 4.3% 56.3% 6.0% MTD 16.3% 16.0% 3.8% 56.7% 7.2% D % 8.1% 2.5% 67.4% 6.0% D % 8.7% 5.7% 65.5% 6.1% D % 8.9% 12.9% 60.1% 7.0% D53 8.6% 17.4% 5.0% 58.7% 10.3% MAR 4.6% 10.0% 3.4% 52.7% 29.3% Page 20 of 26

21 Multiple credits? There are 6230 incidents where officers have multiple IDXs ie the officer shows up multiple times for the same ContactID and the ContactID is for a singular card. These 6230 instances involve roughly 1100 officers. For 585 of these, this only occurred once. However, for the officers in this table, this has happened on 50 or more cards. Rec Row Labels Count Is this a programming glitch? Or, are officers somehow getting multiple credits for single contact cards? If so, how does that happen? Page 21 of 26

22 More on who is documented Overall, when compared to baseline racial populations in the city, a disproportionately high number of cards were filled out for people who are Black and Brown. Cards filled out for Other were disproportionately low, while cards for Whites were proportionate to the general population. We have drilled down on race demographics within patrol zones to test whether black and brown people remain more likely to be documented in areas where more black and brown people live, and same with other categories. Indeed, the card rates are higher in patrol zones with higher proportions of people in our skin colour categories, but the disproportionate levels of stops, relative to the baseline population within these zones, remains, particularly so for black people. Overall, here is how this looks in the 2008 to 2012 FIR dataset: %Black %Brown %Other %White In Contacts Database 25.0% 16.7% 6.7% 51.6% In General Population 8.1% 14.3% % The black card percentage dropped from 25.2 in 2011 to 24 in SKINCOLOUR % 2011% Black % 25.2% Brown % 17.1% Other % 7.1% White % 50.6% Totals % 100.0% This is how it looked from 2003 to 2007 in Master Names Index (MANIX): MANIX Overall SKIN_COLOUR CountOfCards Per cent Total BL % BR % OT % WH % % Page 22 of 26

23 Highest carding areas for 2012 PcntDiff Total Cards ZONE Neighbourhood Agincourt - Malvern Milliken % Flemingdon Park % East York - The Danforth % Entertainment District % Rexdale % Wexford- Maryvale- Dorset 411 Park % Crescent Town - Oakridge % East York- Riverdale- 552 Leslieville % Cabbagetown South % Kingston- Galloway % Arrests vs contacts About one out of every 10 people documented on contact cards between 2008 and 2012 was also arrested and charged by Toronto police during that same time period Individuals carded Individuals carded & arrested Per cent % Page 23 of 26

24 2. Criminal Information Processing System (CIPS) Analysis Violent charges Blacks are charged with a disproportionate number of violent crimes. While 8.1 per cent of Toronto s population is black, 30 per cent of violent crime charges (coded by us as either Violent Major, Violent Minor, Sex Serious, or Firearm Violent) laid between 2008 and 2012 were laid against blacks. SKIN_COLOUR 2008 Pcnt Pcnt Total Pcnt Black % % % Brown % % % Other % % % White % % % TOTAL % % % Patrol zone with most violent crime charges Looking at the last two years of the CIPS data, Patrol Zone 434 saw the most charges laid for serious violent offences, which includes charges we re-coded as Violent Major, Violent Minor, Sex Serious, or Firearm Violent. Zone Grand Total 2009/ / Page 24 of 26

25 One count of drug possession Blacks charged with one count of simple drug possession of marijuana were released on Form 9s less often than whites facing the same single charge, and held for show cause more often than whites. This has not changed but the gap has narrowed. In 2002, the previous five years of arrest data indicated that blacks were released at the scene 61.8 % of the time; whites 76.5%. Blacks were held for bail 15.5%; whites 7.3. In other words, whites were 1.24 times more likely to be released at scene, and blacks 2.1 times more likely to be held for bail. In 2010, an analysis of 2003 to 2008 data shows that blacks were released at scene (Form 9) 58.3 % of the time; whites 64.5 %. As for bail, blacks held 14.3% of the time; whites In other words, whites were 1.1 times more likely to be released at the scene, and blacks 1.5 times more likely to be held for bail. Conversely, it can be said that blacks are about 1.5 times more likely to be taken to the station, and then either released on some other form (some (11.1) with baillike conditions) or held for a bail hearing. Brown and Other, while a small pool, were both treated more like whites, which is consistent with our 2002 findings. In 2012, an analysis of 2008 to mid-2011 data shows, overall, fewer people were being released on Form 9s at the scene and fewer people were held for a show cause, meaning more were processed at the station and released. Blacks were released on Form 9s 47.5 per cent of the time. For whites, it was 56.3 per cent. Looking at bail, blacks were held 9.2 per cent of the time; whites 7.7 per cent. Brown and Other, while a small pool, were both closer to the rates for whites, which is consistent with our 2002 findings. In our current analysis, a change in coding has made it difficult to do any meaningful comparisons. We are no longer able to differentiate between a charge of possession for marijuana and other drugs. One count of Out-of-Sight Driving Offences A disproportionate number of blacks have been ticketed for violations that routinely surface only after a traffic stop has been made. Offences that fall into this out-of-sight category of charges include driving while under suspension, failing to carry a licence, failing to change address on licence, and driving without insurance. The numbers today are nearly identical to what they were in In 2002, the previous five years of data showed black motorists accounted for 33.6% of these offences, while blacks, overall, made up 8.1% of Toronto population. Whites accounted for 52.1% of these offences, while making up 62.7% of population(1996 Census). Page 25 of 26

26 In 2013, our look at the 2008 to 2012 data again shows little change. Percentages Skin Colour Total Black 31.70% 34.40% 30.90% 31.90% 32.10% 32.10% Brown 15.80% 15.40% 14.00% 15.80% 13.80% 14.90% Other 5.30% 5.90% 5.90% 5.70% 5.40% 5.70% White 47.20% 44.30% 49.20% 46.50% 48.70% 47.30% Grand Total % % % % % % Page 26 of 26