Santa Clara County, California Baseline and Alternative Jail Population Projections Report

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1 The JFA Institute Conducting Justice and Corrections Research for Effective Policy Making Santa Clara County, California Baseline and Alternative Jail Population Projections Report Prepared by James Austin Wendy Ware Johnette Peyton Approved: 01/23/2018 October 2017

2 Executive Summary This report contains a detailed jail population projection for Santa Clara County. The report examines a wide variety of factors that can contribute to the current and future size of a county s jail population. The report also provides detailed information on the attributes of the current jail population and people booked and released over a 12 month time frame. In so doing it shows the principle drivers of the jail population. The base projection anticipates no growth in the size of the current jail population of approximately, 3,400 inmates. An estimated, 3,850 beds would be needed to accommodate this daily jail population. There are some reforms presented, that if implemented, would serve to lower this projection. However, until they become more than proposals, they should not be used for planning purposes. Conversely there are two factors that could cause the jail population to rise slightly a growing county jail population and increase numbers of law enforcement personnel deployed to patrol duties. We do not anticipate any major increases in county s current low crime rate. External Factors on Jail Population There are a number of external factors that can have an impact on the future size of a jail population. Some of the key findings are listed below. 1. The county population and the at risk to be incarcerated population (20 44 age group) are projected to increase over the next 40 years. The at risk population will grow at a slower rate as most of the increase will be in the 55 years and older will grow at the fastest rate. 2. Crime rates remain stable and well below the rates that existed in the 1980s and early 1990s. To date the increasing population, AB 109 and Prop 47 have not had an impact on crime rates. 3. Adult arrests increased after AB 109, peaked in in 2014 and have declined since then. 4. Of significance is the dramatic decline in the number of juveniles arrested. While not immediately impacting the jail population, a declining juvenile arrest rate is a good predictor of lower crime rates in the future adult population. 5. Overall, the projected increases in county population is not translating into higher numbers of crimes or people being arrested. This would suggest a level of stability for the foreseeable future in adult arrests and subsequent jail bookings. The one exception would be an increase in total law enforcement workforce which remains uncertain at this time. Jail Population Trends Understanding the future size of a jail population also needs to take into account recent historical trends. The two key drivers of any jail population are the number of admissions and the length of stay(los). 1

3 Comparisons can also be made on Santa Clara s incarceration rates as compared to the U.S., California and selected California counties. 6. Since 2014 jail booking have decreased almost 5% per year. This decrease is directly correlated to the recent decrease in adult arrests. 7. Mirroring the trend in booking, total ADP in the Santa Clara County Jail has also decreased overall during the five year period at a rate of 0.1% per year. The Santa Clara County Jail ADP peaked in 2014 at just over 4,100, increased by almost 12% in 2015 and then decreased slightly in Since 2016, the Santa Clara County Jail population has stabilized and remains at just under 3, Compared to national and California rates of incarceration, Santa Clara is slightly below the national incarceration rates but similar to the overall California jail incarceration rates. 9. Compared to other California counties, Santa Clara county s incarceration rates are average with some above and some below Santa Clara s rates. Current Jail Population Attributes The attributes of the current jail population can be summarized by taking a snapshot of the current jail population on a specific date. Such a snapshot was taken on June 23, 2017 which consisted of 3,461 people. The key attributes of that population are listed below. 10. The jail population is 87% male and 13% female. 11. About 1/3 rd are age 29 and younger % percent are Hispanic % are un sentenced % are sentenced under AB % are held or convicted of a felony crime and 42% are being held on violent felony charges. 16. The majority of female felony charges were for property/non violent crimes while the majority of male felony charges were for violent crimes. Jail Releases Another method for assessing a jail population is from the vantage point of people released from confinement over a 12 month time frame. This population is much larger than the snapshot data since a large number of people are booked and released from the jail in a short period of time. The key attributes of the Santa Clara jail releases are listed below. 17. There were 36,712 releases from the jail system in

4 18. A total of 24,175 people produced the 36,712 releases meaning that 12,357 releases were made by people who were booked more than once in The top three release types form the jail are sentenced served (23%), cite and release (22%) and bail (16%). 20. In terms of release methods and their length of stay (LOS), the following three groups are most critical as they occupy on any given day about two thirds of the total jail population: a. People eventually leaving via time served comprise approximately 28% of the daily jail population; b. Transfers to state prison and state mental health facilities comprise another 28 percent of the jail population; and, c. People sentenced under AB 109 comprise another 8% of the jail population. Length of Stay Jail populations are the product of the number of admissions and how long they remain in custody. There are two ways of measuring the length of stay (LOS) statistic. One method is to calculate for the current jail population, how much time inmates have served to date. The other method is to calculate the LOS for people released from jail over a 12 month time frame. 21. The average LOS for the current jail population is 200 days with a median LOS of 76 days. 22. For jail releases, the average LOS is much lower at 36 days with a median of only two days. 23. These measures of LOS emphasize the two facts that 1) the vast majority of people booked into the jail are released within three days and that if one is not released within three days, one can expect a lengthy period of imprisonment waiting for their criminal charges to be disposed of by the courts. Baseline Projections The baseline projection reflects current demographic, crime, arrests and criminal justice policy trends. Based on these trends, the base projection is a largely non growth trend. This means that the level of bookings will remain constant over the forecast horizon. These two factors (36,000 bookings and an average 36 day LOS) will produce a jail population of about 3,500 inmates. Currently the jail population has been hovering in the to 3,400 level. This is a result of a recently implemented policy recommended by the Bail and Release Work Group to divert some portion of people booked into jail on misdemeanor bench warrants. When additional classification factors are added to the seasonal peaking effects the overall peaking and classification needs factor will increase the projected bed needs to approximately 3,900 beds. 3

5 Alternative Projections To date the county has been implementing a number of initiatives that have had some impact on the two drivers of the jail population bookings and LOS. Most directly, the county decided to stop the practice of housing inmates from the federal government and other counties as a source of revenue. The county has also funded a Community Awaiting Placement Supervision (CAPS) Program which began operations this year. It consists of a five person team from probation, pretrial, behavioral health, and the Sheriff s Office that reviews and assesses 12 individuals per week that are on the JAC list. There is talk of expanding CAPS supervision program beyond mentally ill/substance abusers to all populations giving all Courts another option as to release. Other proposals that, if implemented, could lower the current baseline projection are as follows: 1. Funding of a Sobering Center that will in crease the capacity from 5 to 20 sobering chairs by January 1, This will increase the community option for law enforcement to divert people from a short term booking. 2. Increasing treatment bed capacity in the community (Muriel Wright Conversion), a pretrial mental health diversion program (already underway since January 2016). Efforts to expedite case processing times for people likely to be transferred to state prison, time served and AB 109 sentenced people would likely to have the largest impact on the jail population and reduce the higher custody and special populations numbers. Releasing more people to a supervised release program will likely impact people assigned to the general population and in the minimum and medium custody levels. For these reasons, the expected bed savings would be in the 450 range. However, these bed reduction estimates should not be adopted by the County until there is more evidence that the key criminal justice stakeholders are prepared to change current criminal justice policies and allocate resources needed to support such initiatives. 4

6 Introduction This report presents a baseline and alternative impact jail population projection for Santa Clara County, California. The baseline projection is based on aggregate level data on some of the key drivers of a jail population including demographic trends, crime rates, adult arrests and bookings, and takes into account comments received from the key Santa Clara County officials both within and external to the local criminal justice system. The baseline is intended to show the likely future size of the jail population under current policies and trends without influence of newly enacted policies and reduction strategies. The impact projection is based on adjustments to the baseline projection and takes into account the strategy areas identified by County officials that, if implemented, could serve to reduce the baseline estimates. It is important to emphasize that projections are based on current data, recent historical trends, and current criminal justice system policies. Such projections are subject to inherent risks and uncertainties. In particular, the projections will be impacted by future events that cannot be predicted or controlled, including, without limitation, changes in criminal justice system policies, the passage of new legislation impacting the criminal justice system, and changes in socio economic and demographic patterns, and associated changes in crime rates. County Demographics Trends Demographic population levels, trends and forecasts can assist in analyzing a criminal justice system by providing context on the overall population of the jurisdiction. In particular, projected increases in the socalled at risk population. The at risk population are those people most likely to be arrested and booked into the County jail system. As will be shown in the report, this population consists of Hispanic males who are age As shown in Figure 1, the Santa Clara County population is projected to continue to increase at a rapid rate. The population aged will also increase but at a much slower pace. Much of the growth in the county will be due to extended life spans and an associated aging of the population. For example, while the county is expected to increase by 57% by 2060, the population age 55 and older will increase by 166%. Conversely, the age group will increase by only 27%. An aging population should have a suppressing impact on crime rates and the associated need for criminal justice services. One also notes the projected increase in the Hispanic population. This is significant given the high proportion of jail population that is Hispanic. It should also be noted that these estimates by the California Department of Finance are unable to take into account changing migration patterns that may alter the socio economic status of the resident population. Santa Clara County is becoming an increasingly expensive place to live. As expenses increase there may be an increase in the number of low income people leaving the county to more affordable housing. 5

7 Source: Demographic Research Unit, California Department of Finance, February 2017 Crime Trends Reported crime is typically measured by law enforcement agencies using the FBI s Uniform Crime reporting system (UCR). The UCR consists of the following crimes: 1. Murder 2. Rape 3. Robbery 4. Assault 5. Burglary 6. Theft 7. Auto Theft 8. Arson Santa Clara County s law enforcement agencies all use the UCR major crime types and report these crimes on an annual basis to the California Attorney General as well as the FBI. A crime rate is also computed based on the number of crimes per 100,000 population. 6

8 Despite the continuing increases in the county population and for the at risk populations, the amounts of reported crime and crime rates have remained stable (Figure 2). The data shown in Figure 2 is based on data maintained by the various county law enforcement agencies and includes police agencies that patrol unincorporated areas. The absence of any significant increase in crime rates despite the implementation of Realignment in 2011 and Proposition 47 in The crime rate has remained at the 2,800 per 100,000 population. This means that over 97% of the people in the county do not report a UCR crime to the police each year. More historical data are available from the California Attorney General s Office which also maintains reported crime data for each county. Using that data source, one can see there has been a long term and significant decline in the number of crimes reported by the public to the police since In 1990, the number of reported crimes was nearly 80,000 but by 2015 it was below 50,000 (Figure 3). The figure also shows that the vast majority of crimes are non violent offenses (largely theft) with a value under $ ,000 Figure 2. Santa Clara County Crime Trends ,200 60,000 50,000 3,100 3,000 2,900 Total Cirmes 40,000 30,000 20,000 10,000 2,800 2,700 2,600 2,500 2,400 Crime rates Major Cities Unicorporated Total Crime rate 2,300 Source: Campbell Police Department 7

9 90,000 Figure 3. Reported Crime Santa Clara County ,000 70,000 60,000 50,000 40,000 30,000 20,000 10,000 0 Source: California Attorney General Violent Crimes Property Crimes Total Arrest Trends Trends in adult arrests are important indicators of a jail population as most people today who are arrested are also booked into the county jail system. The overall trend in total arrests in Santa Clara County using the is local reporting data systems as referenced above shows that total arrests increased slightly between 2011 and 2014 after AB109 and have since declined after Prop 47 returning to the same level as Overall, one would have to conclude that arrests have remained fairly stable. The California Attorney General s data base is current only thru 2014 but offers much more details on the types of crimes people are being arrested for. It is also able to dis aggregate between adult and juvenile arrest statistics and over a longer time span. Figure 5 shows the adult arrest trends between 2005 and Consistent with the declining crime rates, adult arrests have dropped significantly since 2005 from about 50,000 to below 40,000 by There was a slight increase in arrests after 2012 thru This upward trend mirrors the County based data trend. But the downward trend since then would suggest fewer bookings for the jail system. Also of note is the significant decline in juvenile arrests which is consistent with state and national trends. A declining juvenile arrest trend bodes well for the future as arrest as a juvenile is a strong predictor of 8

10 subsequent adult criminal activity. There are a number of positive trends for the juvenile population (smaller household size, reduced teenage pregnancies, reduced drug abuse, and delays in child birth for women) that suggest the next generation is much less involved in criminal activities. Figure 4. Santa Clara County Arrests ,000 45,000 42,578 43,087 44,652 43,609 40,000 39,011 39,428 35,000 Total Arrests 30,000 25,000 20,000 15,000 10,000 5,

11 60,000 Figure 5. Santa Clara County Adult Arrests Per Year ,000 40,000 Arrests Per Year 30,000 20,000 10, Felony Misd Total 10

12 16,000 Figure 6. Santa Clara County Juvenile Arrests ,000 12,000 Juvenile Arrests 10,000 8,000 6,000 4,000 2, Felony Misd Status Total 11

13 Figure 6. Santa Clara County Arrests ,000 45,000 42,578 43,087 44,652 43,609 40,000 39,011 39,428 35,000 Total Arrests 30,000 25,000 20,000 15,000 10,000 5, Historical Jail Bookings and Daily Population Trends Analysis of historical jail trends such as number of bookings, length of stay and average daily population assist in providing valuable background information used for future projection trends. Table 1 presents all jail bookings and the average daily population (ADP). each year for the Santa Clara County Jail from 2012 through The largest drop is in the number of bookings between 2014 and 2015, 14.3 percent. Overall, bookings to the Santa Clara County Jail system have fallen an average of 0.7% percent per year over the five year period, although not consistently. The annual bookings increased consistently from 2012 though 2014 and reached a high point of just under 50,000. Since 2014 booking have decreased almost 5 percent per year. This decrease is directly correlated to the decrease in annual arrests presented previously in this report. Mirroring the trend in booking, total ADP in the Santa Clara County Jail peaked in 2014 at just over 4,100 and decreased after Prop 47 by almost 12 percent in 2015, and then again decreased slightly in In 2017, the Santa Clara County Jail population has stabilized and remains at just under 3,600. Estimated LOS is a product of reported booking and ADP and follows the small trends. If Santa Clara County could reach the 23 day level, the jail population would decline by about 600 inmates. Table 2 provides the peaking factor for the jail system in For the purposes of this report, peaking factor is defined as the maximum monthly variance in the county jail population compared to the annual ADP. The peaking factor is a rough estimate of maximum bed space needs based on the actual ADP. The 12

14 seasonal peaking factor determined for Santa Clara jail in 2016 was less than 1.3% which is quite low and will be applied to the bed space forecast later in this report. Finally, one can compute jail incarceration rates based on three measures; rates per 100,000 population, rates per 1,000 reported crimes, and rates per 1,000 arrests. Figure 7 shows these rates for the US, California and Santa Clara County. In general terms, California s rates are below the national rates on all three measures plus a composite index score of all three. Santa Clara County is also below the national rates but slightly above the California rates. TABLE 1 Santa Clara County Jail Bookings, Jail Population and LOS Year Bookings Population ,860 3, ,800 4, ,880 4, ,664 3, ,329 3,593 Average % Change 0.7% 0.1% TABLE 2 Santa Clara County Monthly Peaking Factor Monthly ADP Monthly Peak January 3, % February 3, % March 3, % April 3, % May 3, % June 3, % July 3, % August 3, % September 3, % October 3, % November 3, % December 3, % High Peak (+/ ) 1.9% 13

15 250 Figure 7. U.S., California and Santa Clara County Incarceration Rates Incarcerration Rates Per 100,000 Capita Per 1,000 Crimes Per 1,000 Arrests Index US Santa Clara California Analysis was also conducted to see how Santa Clara County compared with other California counties. There are no counties that are counties that are directly comparable to Santa Clara which has its own unique attributes. But it is instructive to see how the county compares with other counties on key attributes. What was done was to make some comparisons with two Bay Area counties (Contra Costa and Alameda), two large southern counties (San Diego and Los Angeles) and an Inland Empire county (San Bernardino). In addition to the jail population numbers for each county we also added the counts for the probation, parole and prison populations to compute Total Corrections rates based on the county s population, number of reported crimes and adult arrests. As shown in Table 3, Contra Costa consistently has the lowest rates of correctional control while San Bernardino has the highest rates whether it s based on the county s population, amount of reported crime, or the number of adults arrested. For Santa Clara County, it s rates remain between these two counties and comparable to Los Angeles and San Diego. A report by the Center on Juvenile and Criminal Justice (NCJC) and quoted by a Santa Clara Grand Jury report on Court Delay stated that Santa Clara has one of the highest jail incarceration rates per 1,000 adult felony arrests but that is due to the County s very low (3 rd lowest in the state) felony arrest rate. 14

16 TABLE 3 County Comparisons on Key Correctional Population Rates Contra San Indicator Santa Clara Costa Los Angeles Bernardino Alameda San Diego Population 1,915,102 1,126,824 10,182,961 2,135,724 1,629,233 3,286,717 Reported Crime 49,941 35, ,516 69,539 69,688 74,387 Adult Arrests 55,890 24, ,643 72,071 42,002 84,582 Corrections Populations Jail Population 3,556 1,411 16,297 5,176 2,667 5,147 Probation Caseload 8,098 3,626 46,486 14,650 8,543 9,894 Parole Population ,176 3, ,304 Prison Population 4,038 1,906 43,159 8,068 3,533 8,830 Total Corrections 16,613 7, ,118 31,122 15,474 26,175 Jail Rates Per 100,000 Capita Per 1,000 Crimes Per 1,000 Arrests Index Total Corrections Rates Per 100,000 Capita ,140 1, Per 1,000 Crimes Per 1,000 Arrests Index Sources: California Attorney General website, Criminal Justice Profiles. California Department of Finance website, Population Estimates, and California Department of Corrections and Rehabilitation. Detailed Attributes of the Jail Population The following section describes the detailed attributes of the Santa Clara County Jail population from two perspectives the current jail population (snapshot) and jail releases over a 12 month period. The latter data focuses on jail release trends by the methods of release which determine average length of stay for cohorts used to build the simulation model. Data for this section was provided in two case level extract datasets; all 2016 jail bookings and all confined offenders on a single day (June 23, 2017). Presented first is the analysis of the jail population snapshot on June 23,

17 Analysis of the Current Jail Population The County generated a snapshot of the County jail population for June 23, While the release cohort provides the simulation model with a baseline of how a population will change over time, a point in time description of the recent jail population sets the starting line for the number of all groups to be forecasted. Looking at the general characteristics of the current jail population allows identification of any trends that could be seen as extraordinary as well as potential obstacles in the system. The snapshot also illustrates that the overall profile of inmates staying in the jail (daily population census) can be very different from those quickly passing through the jail (release profile). Tables 4 and 5 detail demographics and most serious offense of County Jail detainees respectively. The typical Santa Clara County Jail inmate, based on the snapshot analysis, can be described as: A male, aged 25 to 29 at booking, unsentenced, who is likely to be Hispanic, was committed by the San Jose PD, is not under AB 109, is being held on violent felony charges, and and has been in custody for a substantial period of time. More detailed descriptive of the confined population are: The jail population is 87% male. 35% are age 29 and younger; 55% of the jail population are Hispanic. 70% are unsentenced. 14% are sentenced under some form of AB % are charged or sentenced for a felony and 39% are being held on violent felony charges. The average LOS for all detainees currently in the jail is approximately 200 days. The majority of female felony charges were for property/non violent crimes while the majority of male felony charges were for violent crimes. While not currently housed in the main jail, the Santa Clara Sherriff s Office also manages a large community supervision population. From the June 23, 2017 snapshot file, this population measured 1,124 offenders. Characteristics of this population is very different from the jail population with respect to their legal status and offenses. Unlike the jail population, the community supervision population is largely people sentenced for misdemeanor level crimes (Table 6). 16

18 Characteristic TABLE 4 Santa Clara County Current Jail Population Demographics June 23, 2017 Females N % Avg. Stay so far (days) Males N % Avg. Stay so far (days) Total , Ethnicity Asian % % Black % % Hispanic % , % White % % Other % % Arresting Agency CHIPs San Jose 1 0.1% % Gilroy PD % % Santa Clara County DOC % % Santa Clara County Sheriff % % Santa Clara PD % % San Jose PD % , % Other % % Crime Level Misdemeanor % % 51.2 Felony % , % Other 2 0.3% % Legal Status Sentenced % % Unsentenced % , % Age at Booking Average Age Mean Age AB 109 Status 1170 (H) Jail % % (H) Split % % (H) Jail + Split 0 0.0% 2 0.1% PRCS Flash 0 0.0% 4 0.1% PRCS Revocation 5 0.7% % 1094 PC % % MS % %

19 TABLE 5 Santa Clara County Current Jail Population by Primary Offense June 23, 2017 By Gender Females Males Offense * LOS LOS N % N % (days) (days) Misdemeanor Assault 8 1.8% % 32.2 Sex 0 0.0% % 94.2 Drug Possession % % 60.0 Burglary 0 0.0% 4 0.1% 25.3 Theft/Fraud/Forgery 5 1.2% % 28.8 DUI 5 1.2% % 32.2 Weapons 1 0.2% % 55.8 Other non violent 6 1.4% % 45.5 Other property 3 0.7% % 54.6 Other violent 8 1.8% % 57.7 Traffic 0 0.0% 7 0.2% 27.9 Under the influence 1 0.2% % 38.0 Domestic violence 5 1.2% % 55.0 Total Misdemeanor % % 51.2 Murder % % Assault % % Sex 3 0.7% % Robbery % % Drug Sale % % Drug Possession % % Burglary % % Theft/Fraud/Forgery % % 97.2 DUI % % Weapons 3 0.7% % Other non violent % % 77.4 Other property % % 99.7 Other violent % % Domestic violence 8 1.8% % Total Felony % , % Total Other/Unknown 2 0.5% % *The most serious charge presented in the entirety of this report is based on the CJIC hierarchy table that has not been updated for several years and is not able to rank newer felony charges accurately or felony charges as misdemeanors. This results in an inflated number of misdemeanors listing as the most serious charge. 18

20 TABLE 6 Current Santa Clara Sheriff s Community Supervision Program Population Characteristic Females Males N % N % Total Community Population Ethnicity Asian % % Black % % Hispanic % % White % % Other 4 3.2% % Crime Level Misdemeanor % % Felony % % Other 1 0.5% 6 0.7% Current Age Average Age Median Age Jail Releases and Length of Stay (LOS) Tables 7, 8, and 9 present the release data provided from the Sheriff s office for It should be noted that due to some data limitations in determining an exact confinement LOS for all jail releases, a number of releases were excluded as they were not in the custody of the jail at the time of release. 1 As a result, total releases analyzed are lower than the total jail releases for 2016 of approximately 45,350. In terms of the overall LOS, the average LOS is 36 days (Table 7). However, this statistic is misleading in that there is a large number of people released from the jail that spend a very short period of time. Here are some other key findings: 1. The median (mid point of LOS) is only two days; 2. 38% of all jail bookings are released in one day; 3. 55% of all jail bookings are released within three days; 4. 79% of all jail bookings are released within 30 days; 5. 92% of all jail bookings are released within 120 days; and, 6. 97% of all jail bookings are released within 240 days. 1 All of the following tables exclude the following housing codes at the time of release : (Reentry Correction Program Phase 2), (Public Service Program (PSP)), (Juveniles in Juvenile Hall fulfilling an adult sentence), (Weekend Work Program (WWP), (Temporarily signed out), (Custody Alternative Supervision Program (CASP), (Serving sentence part time), (Serving their sentence in State Prison), and/or persons released after 1000 days or more. 19

21 TABLE 7 Jail Length of Stays Attributes Jail Releases vs. Current Jail Population Attribute Jail Releases Current Jail Population Total 36,712 3,518 Ave. LOS 36 days 200 days Median LOS 2 days 76 days Within 3 days 55% 4% Within 30 days 79% 26% Within 120 days 92% 64% Within 240 days 97% 79% These statistics are in stark contrast to the LOS for the snapshot jail population as noted earlier where the overall average LOS to date was 200 days and a median of 76 days. These statistics as summarized in Table 7 underscores the fact that if a person is not released within 3 days, they are likely to spend a lengthy period of incarceration waiting for the courts to dispose of their charges or to complete the imposed sentence. In terms of the attributes of the typical Santa Clara County Jail release can be described as: Male; Aged 25 to 29 at booking; Likely to be Hispanic; Equally likely to have been in jail for misdemeanor and felony charges; Has been in custody for an average of about 30 days; and, Was either released via cite and release or having served a sentence (Table 8). More detailed descriptive of all jail releases are: The jail release volume is approximately 20% female and 80% male; 39% are age 29 and younger; 49% are Hispanic; 5% were released after some form of AB 109 hold; 56% were held on misdemeanor charges and 44% were held on violent charges; The average LOS for all detainees in jail at any point in time is 29 days, females serving just under 1/3 less time than males; and, The top three release types form the jail are sentenced served (20%), cite and release (22%) and bail (16%) (Table 9). 20

22 Characteristic TABLE 8 Santa Clara County Release Population Demographics May 2016 April 2017 Females Avg. Stay N % (days) N % Males Avg. LOS (days) Total Releases 7, , Ethnicity Asian % , % 40.8 Black % , % 46.5 Hispanic 3, % , % 44.7 White 2, % , % 31.5 Other % , % 20.7 Arresting Agency CHIPs San Jose % 2.3 1, % 8.9 Gilroy PD % , % 44.3 Santa Clara County DOC % , % 35.9 Santa Clara County Sheriff 1, % , % 34.7 Santa Clara PD % , % 46.8 San Jose PD 2, % , % 31.2 Other Agencies 1, % , % 35.9 Crime Level Misdemeanor 4, % , % 7.6 Felony 2, % , % 81 Other % % 1.3 Age at Booking Average Age 34.5 yrs yrs. Median Age 32.5 yrs yrs. AB 109 Status 1170 (H) Jail % % (H) Split % % (H) Jail + Split 1 0.0% % PRCS Flash 4 0.1% % PRCS Revocation % % 50.6 PC % % 68.1 MS % % 31.3 Out of County Detainer 9 0.1% % 15.9 Probation Hold % %

23 TABLE 9 Santa Clara County Release Population by Offense 2016 Females Males Offense * LOS LOS N % N % (days) (days) Misdemeanor Assault % % 17.8 Sex 6 0.1% % 26.8 Drug Possession % % 9.7 Burglary % % 8.3 Theft/Fraud/Forgery % % 7 DUI % % 3.8 Weapons % % 7.8 Other non violent % % 5.6 Other property % % 6.5 Other violent % % 10.2 Traffic % % 2 Under the influence % % 0.7 Domestic violence % % 11.2 Total Misdemeanor 4, % , % 7.6 Murder % % Assault % % Sex 2 0.0% % Robbery % % Drug Sale % % 83.1 Drug Possession % % 42.5 Burglary % % 93.3 Theft/Fraud/Forgery % % 65.1 DUI % % 66.7 Weapons % % 37.6 Other non violent % % 55.8 Other property % % 43.6 Other violent % % 79 Domestic violence % % 25 Total Felony 2, % , % 81 Other % % 1.3 Unknown 8 0.1% % 2.8 *The most serious charge presented in the entirety of this report is based on the CJIC hierarchy table that has not been updated for several years and is not able to rank newer felony charges accurately or felony charges as misdemeanors. This results in an inflated number of misdemeanors listing as the most serious charge. 22

24 Table 10 shows the number of releases by the method of release, their associated LOS and the amount of jail beds these release groups are occupying. This table highlights in yellow those populations that are driving the current jail population. Any reforms to lower the jail population would have to impact the release groups highlighted in Table 10. In terms of release methods and their use of jail space the following three groups are most critical as they occupy on any given day about two thirds of the total jail population: Offenders eventually leaving via time served comprise 28% of the current jail population; Transfers to state prison comprise another 28% of the jail population, and; Offenders sentenced under AB 109 (PC 1170(h)) comprise nine percent of the jail population. The other large group are people listed as charges dismissed but this statistic may not be accurate since many releases had multiple charges and that the true court disposition may not be due to dismissed charges. Impacting these three groups will require efforts to somehow expedite the time it takes the court to reach a final disposition. There may also be opportunities to release people whose charges are eventually dropped or get a credit for time served to supervised pretrial release. Conversely, although release via bail or cite and releases make up over one third of all jail releases, these offenders compromise only three percent of the jail population. Efforts to divert these people will have minimal impact on the jail population. 23

25 TABLE 10 Jail Releases, LOS and Beds by Release Type Females Males Average Estimated Average Estimated Release Reason Length Average Length Average N % N % of Stay Daily of Stay Daily (days) Population (days) Population Total Releases 7, , ,160 Release Method Cite & Release 1, % , % Time Served 1, % , % Bail Bond 1, % , % OR 1, % , % Charges Dismissed % , % Rehab % , % State Prison % , % Other County % % % , % H % % PRCS Revoke % % US Marshall % % Other % % Jail Population Projections Table 11 provides the population projections by gender produced for the Santa Clara County jail. These projections were based on the most current demographic, crime, and criminal justice policy trends discussed earlier and were developed using the JFA proprietary simulation model, Wizard. The simulation model was built using the release and confined population analysis detailed in the sections above. In essence, the base projection is a largely non growth trend. This means that the level of booking, approximately 36,000 and the current ALOS of approximately 36 days will remain constant over the forecast horizon. These two factors (36,000 releases and 36 day LOS) will produce a jail population of about 3,550 inmates. It should be noted that since September 2017, the County has begun implementing some of the pretrial booking reforms that are having a slight impact on lowering the jail population. In particular, the Bail and Release Work Group recommended modification of bail booking policy which was implemented on October 1, The cutoff for citation has been raised to $15,000. The overall intent is to divert some portion of people booked into jail on misdemeanor bench warrants to be quickly released to pretrial services at time of booking. It is estimated that a reduction of as many as 3,700 bookings could be 24

26 achieved but there is no firm analysis of such an impact. For this reason, we slightly lowered the baseline projection to reflect this recent development. Conversely there are two factors that could cause the jail population to rise slightly a growing county jail population and increase numbers of law enforcement personnel deployed to patrol duties. We do not anticipate any major increases in county s low crime rate. We have also factored in a peaking factor to account for seasonal fluctuations in the jail population plus the need to have some excess bed capacity to house special management populations and the need to perform jail facility maintenance from time to time. Table 2 presented the average annual and high yearly counts for the jail. The average seasonal high peak for the 2016 year (1.9%) was applied to the forecast in With the seasonal peaking factor added to the estimate the future bed needs would be about 3,725. When additional classification factors are added to the seasonal peaking effects, the overall peaking and classification needs factor will increase the projected beds to approximately 4,100 beds. TABLE 11 Santa Clara County Jail Historical and Projected ADP By Gender (Base Projection Current Policies and Trends with Seasonal Peaking) Year Total Male Total Female Total Jail , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,511 The baseline projection also needs to be adjusted to account for classification/housing factors. The classification/housing factor recognizes that a jail cannot safely operate at full capacity for any sustained 25

27 period of time. Surplus or vacant beds are needed at all times to be able to transfer inmates to the appropriate housing units. In particular, the special management units require higher peaking factors. Table 12 shows the details of accounting for the special and general populations now housed in the jail. These estimates were developed in close consultation with the classification staff and representatives from Custody Health Services. 2 Santa Clara s special inmate population is unique due to the significant number of males in the protective custody population. Now with over 900 male inmates with a protective custody designation, they consume nearly 30% of the entire male jail population and nearly 1/4 th of the total jail population. Table 12 also shows the custody level of the protective custody population by gender. The majorities of these inmates are medium custody but a significant number are maximum custody which means they must be separated from the minimum custody protective custody inmates. TABLE 12 Current Jail Population by Classification Level and Bed Needs Total Inmates Total Beds % Population Type Females Males Inmates Peaking Beds Inmates Peaking Beds Total Jail Population ,027 3,466 3,461 4, % Special Populations ,304 1,462 1,433 1,644 41% Mental Health % Acute % Sub Acute % Medical Acute % Protective custody ,025 26% Maximum % Medium % Minimum % Administrative % Disciplinary % General Population ,843 1,999 2,169 2,350 59% Max % Medium % Minimum ,049 1,101 28% Booking/Intake % 2 Custody Health Services staff estimates about 100 inmate patients are housed in General Population for lack of sufficient Special Management /Subacute housing. In addition, they estimate that there are approximately 40 security level 4 SMI inmate patients housed in General Population that warrant Special Management Housing. 26

28 Each classification level has an associated peaking and classification factor that range from 1.05 to 1.20 of the inmate population. These seasonal peaking/classification rates are used to estimate the number of beds needed for each classification category and for the entire jail system dis aggregated by gender. With a current inmate population of about 3,400, the total bed need is estimated at about 3,900. Since the current jail population projection is essentially flat, this also results in a long term bed need also set at about 3,900 (Table 13). TABLE 13 Santa Clara County Jail Historical and Projected Bed Needs by Gender (Base Projection Current Policies and Trends with Seasonal Peaking and Classification Factors ) Year Total Male Beds Total Female Beds Total Jail Beds , , , , , , , , , , , , , , , , , , , ,888 Alternatives to the Base Projection A key question that surfaces in any jurisdiction is whether the jail population can be lowered without jeopardizing public safety. On the latter point, there is no question that jail populations can be lowered which is basically a matter of either reducing jail admissions and/or lowering the LOS. The question is which policies is the county willing to implement that would accomplish this goal and what would be the impact on public safety? To date the county has been implementing a number of initiatives that have had some impact on the two drivers of the jail population bookings and LOS. Most directly, the county decided to stop the practice of housing inmates from the federal government and other counties as a source of revenue. Future unfunded reforms that need to be assessed include a Behavioral Health request for funding for a Sobering Center the Whole Person Care Initiative. The current capacity of the program is 5 chairs which will be increased to 20 chairs by January 1, If they are successful, this will create another community option for law enforcement to divert people from a short term booking event. 27

29 In the same vein, the Board has approved ten recommendations designed to divert the booking /expedite the release of the mentally ill, homeless and substance abuse defendants from jail. These recommendations include increasing treatment to a 45 bed capacity in the community by 2018 (Muriel Wright Conversion), a pretrial mental health diversion program (already underway since January 2016) and several pre booking diversion options for law enforcement. Under these reforms, people would be diverted from the jail to a pre booking diversion station at the Reentry Center, Restoration Center in the community and mobile crisis intervention where teams will respond to police location in community to divert individuals to services instead of jail. There is the creation of the Community Awaiting Placement Supervision (CAPS) Program which began operations this year. It consists of a five person team from probation, pretrial, behavioral health, Re Entry Services, and the Sheriff s Office that reviews and assesses 12 individuals per week that are on the JAC list. They then make recommendations to the Court on 5 individuals/per week that can be safely supervised in the community until their treatment bed is available. The team then provides supervision and treatment services to the individual in the community until they are moved into a treatment bed. Once Jail Assessment Coordinator (JAC) list is eliminated or greatly reduced, the Court will directly order individuals released to program. There is talk of expanding CAPS supervision program beyond mentally ill/substance abusers to all populations giving all Courts another option as to release. Collectively most of these reforms seem to be targeting people who have a relatively short LOS. As such they would have an impact on jail bookings but less of an impact on the jail population. Specifically, it would be reasonable to expect a 100 jail population reduction. The more important drivers of the jail population were highlighted in Table 10. The largest contributors are people who are released for Time Served and Sentenced to State Prison. Between the two groups they occupy on any given day 1,723 beds or about half of the jail population. Other significant release groups are people who have their charges dismissed by the courts, or are sentenced under AB 109. In order to lower the jail population, the LOS associated with these release groups would need to be lowered. Ultimately the time it takes to process these in custody cases must be addressed. There seems to a consensus that improvements in case processing is needed and can be accomplished. According to a recent Grand Jury report that examined court delays, Santa Clara County ranks last among the 49 counties that reported data to the Judicial Council with only 47% of felony cases being disposed of within 12 months of filing the charges. Several recommendations were made that if implemented could serve to lower the time to disposition for those in custody. To more closely examine this issue, two stress tests were conducted by JFA and the Pretrial Services Department to determine if cases that now had a disposition of sentenced to state prison or time served could be processed faster. The initial tests led to the conclusion that, in general, criminal cases could be processed and disposed of in a more efficient manner but there was a lack of specification of which cases could be expedited. Based on the initial assessments a second assessment was conducted which showed similar results. Our best guess at this time is that the base projection could be reduced by about 513 inmates through a combination of an expanded supervised release program and efforts to expedite the processing of criminal cases that now result in a disposition of time served, sentenced to state prison, and

30 Sentences, and diverting short term bookings. Table 14, shows the simulated results of altering the time required to dispose of such cases by either 10 or 30 days. The total reduction would be 341 inmates. The second reduction reform would be the expanded use of supervised pretrial release. This reform would focus in pretrial defendants who have been charged with felony level crimes but were unable to secure release at their first appearance. In one of the stress tests we were able to identify about 200 people who were recommended for release to the court but for which the court chose not to release at the initial hearing. In total, an estimated 541 population reduction would likely occur if these four reforms were implemented (Table 14). There would also be some modest effects from implementing the diversion of short term inmates as noted earlier that could further reduce the jail population by another 100 inmates. It is also prudent to apply a 20% discount factor to these estimates as there will be some level of resistance or lack of impact due to implementation issues/resistance. In terms of the impact of these reductions on the type of jail bed needs, one should assume that they would serve to impact all classification and special populations. Efforts to expedite case processing times for people likely to be transferred to state prison, time served and AB 109 sentenced people would likely impact the higher custody and special populations numbers. Releasing more people to a supervised release program will likely impact people assigned to the general population and in the minimum and medium custody levels. However, these bed reduction estimates should not be formally adopted until there is more evidence that the County s criminal justice policy leaders are jointly prepared to change current criminal justice policies and allocate resources needed to support such initiatives. Table 14 Summary of Potential Future Population Reductions by Target Population Target Populations Male Female Total 1. Released via Time Served Released via State Prison Released via 1170H Supervised Pretrial Release Totals With 20% Discount

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