HomeMy WebLinkAboutResolutions - 2020.12.07 - 33981MISCELLANEOUS RESOLUTION #20654 December 7, 2020
BY: Commissioner Penny Luebs, Chairperson, Health, Safety and Human Services Committee
IN RE: PUBLIC SERVICES/COMMUNITY CORRECTIONS DIVISION - AUTHORIZATION TO PARTICIPATE IN
THE HARVARD STUDY TO REDUCE RACIAL DISPARITIES IN BAIL DECISIONS DATA TRANSFER
AGREEMENT
To the Oakland County Board of Commissioners
Chairperson, Ladies and Gentlemen:
WHEREAS Harvard University has created a study entitled Reducing Racial Bias in Bail Decisions to improve
judicial decision -making and reduce racial disparities in bail decisions; and
WHEREAS this study was designed to help judicial officers understand the impact of implicit bias on their bail
decisions; and
WHEREAS the study also alms to identify interventions that are effective at mitigating implicit bias; and
WHEREAS Harvard University is partnering with courts and pretrial services agencies to implement this study; and
WHEREAS the State Court Administrative Office has given permission for judges / magistrates to participate in the
study if they chose; and
WHEREAS each judge or magistrate will have the option to voluntarily participate in the study; and
WHEREAS the results from the study will be shared with participating judges and magistrates to show the
effectiveness of utilized interventions in recognizing and reducing implicit bias in the bail decision; and
WHEREAS the results of the study will be anonymized and not associated with any participating judge or magistrate;
and
WHEREAS Harvard will need data collected by Community Corrections from Oakland County regarding bail
decisions and outcomes both pre and post interventions; and
WHEREAS there may be a cost for the transfer of data to Harvard University; and
WHEREAS Harvard University will pay the County the cost of data extraction and other related costs; and
WHEREAS the Community Corrections Division and Department of Information Technology, with the assistance of
Corporation Counsel, has negotiated the attached Data Transfer Agreement with Harvard University; and
WHEREAS the Community Corrections Division and the Department of Information Technology recommend
approval of the attached Data Transfer Agreement with Harvard University.
NOW THEREFORE BE IT RESOLVED that the County Board of Commissioners hereby approve the attached Data
Transfer Agreement with Harvard University and authorize the Chairperson of the Board of Commissioners to
execute the agreement with Harvard University.
BE IT FURTHER RESOLVED that no budget amendment is recommended at this time.
Chairperson, on behalf of the Health, Safety and Human Services Committee, I move the adoption of the foregoing
resolution.
P 4 Lu" ,_
Commissioner enny Luebs District # 16
Chairperso alth, Safety and Human Services
Committee
HEALTH, SAFETY AND HUMAN SERVICES COMMITTEE VOTE:
Motion carried on a roll call vote with Kochenderfer absent.
DATA LICENSE AGREEMENT
BETWEEN THE COUNTY OF OAKLAND
AND HARVARD
This Data License Agreement (this "Agreement") is made between Oakland County, by its
Department of Community Corrections, a Municipal and Constitutional Corporation, 1200 North
Telegraph Road, Pontiac, Michigan 48341 (the "County"), and the President and Fellows of
Harvard College, acting on behalf of the Malcom Weiner Center for Social Policy at Harvard
Kennedy School (herein "Harvard"), 1033 Massachusetts Ave., 5°i Floor, Cambridge, MA
02138. The County and Harvard may also be referred to jointly as 'Parties" or individually as a
"Party."
PURPOSE OF AGREEMENT, The County and Harvard enter into this Agreement for the
purpose of the County licensing certain criminal justice related information of the County to
Harvard for Harvard to use in a research study regarding judicial bail/bond decisions (herein the
"Research Study"). In consideration of the mutual promises, good and valuable consideration,
obligations, representations, and assurances in this Agreement, the Parties agree to the following:
1. DEFINITIONS. The following words and expressions used throughout this Agreement,
whether used in the singular or plural, shall be defined, read, and interpreted as follows:
I.L Agreement means the terms and conditions of this Agreement and any other mutually
agreed to written and executed modification, amendment, exhibit, and/or attachment.
1.2. Claims mean any alleged losses, claims, complaints, demands for relief or damages,
lawsuits, causes of action, proceedings, judgments, deficiencies, liabilities, penalties,
litigation, costs, and expenses, including, but not limited to, reimbursement for
reasonable attorney fees, witness fees, court costs, investigation expenses, litigation
expenses, amounts paid in settlement, and/or other amounts or liabilities of any kind
which are incurred by or asserted against County or Harvard, or for which County or
Harvard may become legally and/or contractually obligated to pay or defend against,
whether direct, indirect or consequential, whether based upon any alleged violation of
the federal or the state constitution, any federal or state statute, role, regulation, or any
alleged violation of federal or state common law, whether any such claims are brought in
law or equity, tort, contract, or otherwise, and/or whether commenced or threatened.
1.3. County means Oakland County, a Municipal and Constitutional Corporation, including,
but not limited to, all of its departments, divisions, the County Board of Commissioners,
elected and appointed officials, directors, board members, council members,
commissioners, authorities, committees, employees, agents, volunteers, and/or any such
persons' successors.
1.4. County Data means any and all information and data in any format, including, but not
limited to criminal justice related information, that County provides to Harvard under
this Agreement.
1.5. Harvard means the President and Fellows of Harvard College (aka Harvard tlniversity),
including, but not limited to, all of its departments, divisions, elected and appointed
officials, directors, board members, commissioners, authorities, committees, employees,
agents, volunteers, and/or any such persons' successors.
1.6. PH (Personally Identifiable Information) means any County Data that does any of the
following: 1) identifies a person; 2) provides a reasonable basis to believe that the
infornation or data can be used or identify a person; or 3) can be reasonably attributed to
a particular person.
2. COUNTY RESPONSIBILITIES.
2.1. County may provide to Harvard all or a portion of County Data, at County's sole
discretion, that Harvard requests from County to use in Harvard's Research Study.
2.2. Oakland County judges and/or magistrates ("Court Officials") may choose to voluntarily
participate in the Research Study by signing the Consent form which is incorporated into
this Agreement and attached as Exhibit 1. Court Officials are not required nor obligated
to participate in the Research Study and may withdraw their participation at any time by
providing written notice to Harvard.
2.3. License Grant. County grants to Harvard a nonexclusive, nontransferable, license to use
County Data for Harvard's Research Study only, in accordance with the terms and
conditions in this Agreement.
2.4. The County is not obligated to provide Harvard with County hardware or computer
systems for use of the County Data.
2.5. Ownership of County Data. All County Data is owned by the County. The County Data
is protected by copyright and other intellectual property laws. Harvard does not own the
County Data, but merely has a license to use County Data in accordance with this
Agreement.
2.6. The County has no obligation to provide Harvard with installation, consulting, training
service, transportation, indemnification, or insurance.
3. HARVARD RESPONSIBILITIES.
3.1. Harvard shall respond to and be responsible for all third -party legal requests for
information or records that are made to Harvard.
3.2. Harvard shall use the County Data for the Research Study only and shall not disclose
any PII to third parties, except as required by law. Harvard shall anonymize and/or
remove all PII from the results, conclusion, and/or any publication related to the
Research Study.
3.3. Harvard will promptly cooperate with any reasonable request by the County in any
investigation or possible infringement of any applicable intellectual properly rights or
other proprietary rights related to Harvard's use of County Data.
3.4. Harvard may provide the County with decision -making aids or training (including
materials) during the Research Study. The County may use and retain the decision -
making aids or training materials at its sole discretions, but has no obligation to use
and/or retain the decision -making aids or training materials.
3.5. Prior to Harvard publishing or disclosing to any third parties any results, findings, or
conclusions of the Research Study pertaining to the County Data. Harvard shall provide
the County with the results, findings, and conclusions of the Research Study pertaining
to the County Data. Harvard shall not publish or disclose to any third parties any results,
findings, or conclusions of the Research Study pertaining to the County Data until
County has reviewed them solely for purposes of identifying for removal any PII
inadvertantly contained therein, or other County Data of which County does not consent
to the disclosure. Harvard shall be required to remove any PII or County Data so
identified prior to publication or disclosure of such results, findings and/or conclusions.
3.6. County shall have the right to use, publish, distribute, broadcast, reproduce, display,
exhibit, and/or create derivative works of the County Data and the results, findings, and
conclusions of the Research Study for any lawful purpose at the County's discretion.
3.7. Harvard will return or destroy County Data to County at County's sole discretion and
upon County's request.
3.8. Harvard shall notify the County if the Research Study is not completed prior to the
expiration of this Agreement. Such notification shall indicate the anticipated date of
completion and shall be accompanied by a request for an extension of the existing
Agreement, if further use is desired. If Harvard is no longer pursuing the research
project, it shall immediately provide the collaborating jurisdiction with an explanation as
to why the project is no longer being pursued and a copy of all findings made as a result
of the research that was conducted.
4. Fees.
4.1. Except as otherwise provided in this Agreement, neither Party is required nor obligated
to pay the other Party any money under this Agreement.
5. DATA USE AND SECURITY.
5.1. Use of County Data and PII. Harvard shall use appropriate safeguards to protect the
confidentiality, security, and integrity of County Data. Harvard shall implement and
maintain appropriate administrative, technical, and organizational security measures to
safeguard against unauthorized access to County Data. Such measures shall be in
accordance with security industry best practice and not less stringent than the measures
Harvard applies to protect its own data of a similar kind. Harvard shall only use County
Data for the Research Study in accordance with the terms of this Agreement. Harvard shall
not reproduce, provide, disclose, or give access of PIT to any Harvard employee or agent
not having a legitimate need to know or to any third -party. Notwithstanding the foregoing,
Harvard may disclose PIT, if required by law, statute, or other legal process; provided that
Harvard: (a) gives the County prompt written notice of the impending disclosure, to the
extent not prohibited by law; (b) provides reasonable assistance to the County in opposing
or limiting the disclosure; and (c) makes only such disclosure as is compelled or required.
5.2, Unauthorized Access/Disclosure or Theft of County Data. Harvard shall notify the
County as soon as practicable but no later than forty-eight (48) hours of "Discovery" of
suspected unauthorized access, acquisition, disclosure, or theft of County Data (a
"Security Breach"). "Discovery" means the first day on which the Security Breach is
known to Harvard. Upon Discovery of a Security Breach, Harvard shall do the following:
(a) take reasonable measures to promptly cure the deficiencies relating to the Security
Breach in order to secure County Data; (b) cooperate with the County in investigating the
occurrence, including making available all relevant records, logs, files, and data reporting
materials required upon request by the County; and (c) comply with all applicable federal
or state laws and regulations pertaining to unauthorized disclosures or as otherwise
directed by the County. Harvard shall comply with and follow the procedures in the PII
Exhibit which is attached and incorporated in this this Agreement as Exhibit 2.
5.3. Storage of Countv Data. Harvard shall only store and process County Data at and from
data centers located within the United States. Prior to publishing or making the results or
conclusions of the Research Study public, Harvard shall encrypt County Data at rest and in
transit. Harvard shall encrypt PIT at rest and in transit.
5.4. Resnanse to Legal Reauest for Countv Data. If the County receives a Court Order, a
Freedom of Information Act (FOIA) request, or other legal request to provide County
Data held by Harvard, then Harvard shall provide County Data to the County, in a
format directed by the County, within the time frame required by law.
5.5. Comnletion of Countv Securitv Ouestionnaire. At the request of County and on an
annual basis, Harvard shall provide the County with the answers to the County's security
questionnaire.
5.6. Audit. Al County's request, Harvard shall permit County to monitor, audit, inspect, and
review the activities, practices, procedures, and policies of Harvard in performing this
Agreement and the Research Study, in order to verify compliance with this Agreement.
5.7. Additional Seeurity Measures. In addition to and without limiting any other
requirements in this Agreement, Harvard shall do the following:
5.7.1. Conceal the identity of persons whose individual criminal history information is
supplied to Harvard.
5.7.2. Protect the confidential nature of the individual criminal history information.
5.7.3. Use the information furnished under this Agreement only for the research
purposes described herein.
5.7.4. Store all electronic media containing the data on encrypted hard drive and/or flash
drives and/or a secure server. Password protection will be required to access the
data and will only be available to persons authorized by Harvard that are involved in
the Research Study. Data storage policies will comply and receive approval from
the Harvard University's cognizent School Security Officer.
5.7.5. Store all physical media containing data received from the collaborating
jurisdiction in secure, locked containers.
5.7.6. Secure all electronic media containing data received from County against
unauthorized access.
5.7.7. Retain County Data only so long as may be necessary to effectuate the purpose(s)
of the Research Study described and to thoroughly and irretrievably destroy all
originals and copies of County Data in such a way as to prevent their unauthorized
use. For the avoidance of doubt, County acknowledges and agrees that de-
indentified copies of County Data may be provided to the funder of the Research
Study, J-PAL North America, to substantiate the project results and otherwise
support the conclusions of the Research Study.
6. ASSURANCES, INDEMNIFICATION, AND LIABILITY.
6.1. HARVARD SHALL INDEMNIFY, DEFEND, AND HOLD THE COUNTY
HARMLESS FROM ALL CLAIMS, INCURRED BY OR ASSERTED AGAINST THE
COUNTY BY ANY PERSON OR ENTITY, WHICH ARE ALLEGED TO HAVE
BEEN CAUSED FROM THE ACTS OR OMISSIONS OF HARVARD, HARVARD'S
4
EMPLOYEES OR AGENTS, AND/OR ANY MEMBER OF THE, RESEARCH
STUDY TEAM.
6.2. HARVARD SHALL HAVE NO RIGHT UNDER THIS AGREEMENT OR UNDER
ANY OTHER LEGAL PRINCIPLE TO BE INDEMNIFIED OR REIMBURSED BY
THE COUNTY OR ANY COUNTY AGENTS.
6.3. HARVARD SHALL BE SOLELY RESPONSIBLE FOR ALL COSTS, FINES,
PENALTIES, AND FEES ASSOCIATED WITH ANY UNLAWFUL USE OR
MISUSE OF THE COUNTY DATA BY HARVARD OR ITS EMPLOYEES OR
AGENTS.
6.4. THIS AGREEMENT DOES NOT, AND IS NOT INTENDED TO, IMPAIR, DIVEST,
DELEGATE OR CONTRAVENE ANY CONSTITUTIONAL, STATUTORY,
AND/OR OTHER LEGAL RIGHT, PRIVILEGE, POWER, OBLIGATION, DUTY,
OR IMMUNITY OF THE PARTIES. NOTHING IN THIS AGREEMENT SHALL BE
CONSTRUED AS A WAIVER OF GOVERNMENTAL IMMUNITY FOR EITHER
PARTY.
6.5. The Parties have taken all actions and secured all approvals necessary to authorize and
complete this Agreement. The persons signing this Agreement on behalf of each Party
have legal authority to sign this Agreement and bind the Parties to the terms and
conditions contained herein.
6.6. Each Party shall comply with all federal, state, and local ordinances, regulations,
administrative rules, and requirements applicable to its activities performed under this
Agreement.
6.7. IN NO EVENT WILL THE COUNTY BE LIABLE TO HARVARD OR ANY OTHER
PERSON, FOR ANY LOST REVENUES OR PROFITS, CONSEQUENTIAL,
INCIDENTAL, DIRECT, INDIRECT, SPECIAL, AND PUNITIVE OR OTHER
DAMAGES ARISING OUT OF OR RELATING TO THIS AGREEMENT OR THE
COUNTY DATA, HOWEVER CAUSED AND REGARDLESS OF THEORY OF
LIABILITY, EVEN IF HARVARD HAD KNOWLEDGE OF THE POSSIBILITY OF
SUCH DAMAGES.
7. DISCLAIMER AND WARRANTIES.
7.1. THE COUNTY DATA IS PROVIDED TO HARVARD "AS IS," "AS AVAILABLE,"
AND "WITH ALL FAULTS." THE COUNTY EXPRESSLY DISCLAIMS ALI,
WARRANTIES OF ANY KIND, WHETHER EXPRESS OR IMPLIED, INCLUDING,
BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE, AND NON- INFRINGEMENT.
7.2. COUNTY MAKES NO WARRANTY THAT (I) THE. COUNTY DATA WILL MEET
HARVARD'S REQUIREMENTS OR BE SUITABLE FOR HARVARD'S
PURPOSES; (II) THE COUNTY DATA WILL BE PROVIDED TO HARVARD BY A
SPECIFIC DATE; (III) THE COUNTY DATA WILL BE ERROR -FREE,
ACCURATE, OR RELIABLE; OR (IV) THE COUNTY DATA WILL CONFORM TO
OR SATISFY ANY FEDERAL, STATE, OR LOCAL. LAWS OR REGULATIONS.
7.3. THE COUNTY DATA PROVIDED TO HARVARD IS ACCESSED AND USED AT
HARVARD'S DISCRETION AND RISK. HARVARD WILL BE SOLELY
RESPONSIBLE FOR ANY DAMAGE TO ITS COMPUTER SYSTEM, EQUIPMENT,
OTHER PROPERTY, OR LOSS OF DATA THAT RESULTS FROM ACCESSING
OR USING THE COUNTY DATA.
8. DISPUTE RESOLUTION
8.1. All disputes relating to the execution, interpretation, performance, or nonperformance of
this Agreement involving or affecting the Parties may first be submitted to County's
Manager of Community Corrections and Harvard's Agreement administrator for
possible resolution. County's Manager of Community Corrections and Harvard's
Agreement administrator may promptly meet and confer (in person or remotely) in an
effort to resolve such dispute.
9. TERM AND TERMINATION OF THIS AGREEMENT.
9.1. Term. This Agreement shall be effective on the last signature date set forth below
(effective date) and shall remain in effect until it expires on December 31, 2022
(expiration date), unless this Agreement is terminated prior to the expiration dale as
otherwise provided in this Agreement.
9.2. Either Party may cancel or terminate this Agreement upon written notice to the other
Party for any reason, including convenience, upon thirty (30) calendar days written
notice to the other Party.
9.3. Either Party may terminate this Agreement upon seven (7) calendar days written
notice to the other Party if the other Party materially breaches this Agreement and fails
to cure the material breach before the effective date of termination.
9.4. The effective date of termination and/or cancellation shall be clearly stated in the written
notice. Upon the termination and/or expiration of this Agreement, Harvard shall
immediately return all copies of the County Data in Harvard's possession. Harvard will
not be entitled to any refund of the license fee paid to the County.
9.5. Oblivations anon Expiration. Termination or Cancellation of Contract. At the
County's sole discretion, upon expiration, termination, or cancellation of this
Agreement, Harvard shall return PIT in a mutually agreeable format in a prompt and
orderly manner or provide for the secure disposal of PII as directed by County.
10. DELEGATION OR ASSIGNMENT. Except as otherwise provided in this Agreement,
neither Party shall delegate or assign any obligations or rights under this Agreement without
the prior written consent of the other Party.
1 L NO EMPLOYEF,-EMPLOYER RELATIONSHIP. Nothing in this Agreement shall be
construed as creating an employee -employer relationship between County and Harvard. In no
event, shall Harvard employees be deemed employees, agents, volunteers, or subcontractors
of the County. Harvard shall ensure that Harvard Employees are apprised of their status and
the limitations. Harvard and/or Harvard employees shall not represent themselves as County
employees. Harvard and Harvard employees shall not be entitled to participate in any County
employee benefit plans or programs.
12. NO THIRD -PARTY AF,NFFICIARIES. Except as provided for the benefit of the Parties,
this Agreement does not and is not intended to create any obligation, duty, promise,
contractual right or benefit, right to indemnification, right to subrogation, and/or any other
right in favor of any other person or entity.
13. NO IMPLIED WAIVER. Absent a written waiver, no act, failure, or delay by a Party to
pursue or enforce any rights or remedies under this Agreement shall constitute a waiver of
those rights with regard to any existing or subsequent breach of this Agreement. No waiver
of any term, condition, or provision of this Agreement, whether by conduct or otherwise, in
one or more instances shall be deemed or construed as a continuing waiver of any term,
condition, or provision of this Agreement. No waiver by either Party shall subsequently
affect its right to require strict performance of this Agreement.
14. SEVERARILITV. If a court of competent jurisdiction finds a term or condition of this
Agreement to be illegal or invalid, then the term or condition shall be deemed severed from
this Agreement. All other terms, conditions, and provisions of this Agreement shall remain
in full force.
15. CAPTIONS. The section and subsection numbers, captions, and any index to such sections
and subsections contained in this Agreement are intended for the convenience of the reader
and are not intended to have any substantive meaning. The numbers, captions, and indexes
shall not be interpreted or be considered as part of this Agreement. Any use of the singular
or plural, any reference to gender, and any use of the nominative, objective or possessive case
in this Agreement shall be deemed the appropriate plurality, gender or possession as the
context requires.
16. FORCE MASEITRE. Notwithstanding any other term or provision of this Agreement,
neither Party shall be liable to the other for any failure of performance hereunder if such
failure is due to any cause beyond the reasonable control of that Party and that Party cannot
reasonably accommodate or mitigate the effects of any such cause. Such cause shall include,
without limitation, acts of God, fire, explosion, vandalism, national or state emergencies,
pandemics, insurrections, riots, wars, strikes, lockouts, work stoppages, other labor
difficulties, or any law, order, regulation, direction, action, or request of the United States
government or of any other government. Reasonable notice shall be given to the affected
Party of any such event.
17. NOTICES. Notices given under this Agreement shall be in writing and shall be personally
delivered, sent by express delivery service, certified mail, or first-class US. mail postage
prepaid, and addressed to the person listed below. Notice will be deemed given on the date
when one of the following first occur: (i) the date of actual receipt; (ii) the next business day
when notice is sent express delivery service or personal delivery; or (iii) three days after
mailing first class or certified U.S. mail.
17.1. If Notice is sent to County, it shall be addressed and sent to: Manager, Oakland
County Community Corrections, 250 Elizabeth Take Rd, Ste. 1520, Pontiac, MI 4834,
and the Oakland County Purchasing Department, 2100 Pontiac Lake Road, Waterford,
Michigan 48328.
17.2. If Notice is sent to Harvard, it shall be addressed to: Grants and Contracts Officer,
Harvard University Office for Sponored Programs, 1033 Massachuetls Ave., 5th Floor,
Cambridge, MA 02138.
17.3. Either Party may change the individual to whom Notice is sent and/or the mailing
address by notifying the other Party in writing of the change.
18. GOVERNING LAW/CONSENT TO JURISDICTION AND VENUE. This Agreement
shall be governed, interpreted, and enforced by the laws of the State of Michigan. Except as
otherwise required by law or court rule, any action brought to enforce, interpret, or decide
any Claim arising under or related to this Agreement shall be brought in the 6th Judicial
Circuit Court of the State of Michigan, the 501h District Court of the State of Michigan, or
the United States District Court for the Eastern District of Michigan, Southern Division, as
dictated by the applicable jurisdiction of the court. Except as otherwise required by law or
court rule, venue is proper in the courts set forth above.
19. SURVIVAL OF TERMS. The termination or expiration of this Agreement howsoever
arising shall not affect the rights, benefits, obligations, duties, or liabilities of either Party
accrued prior to termination or expiration. The following sections, terms, and conditions shall
survive and continue in full force beyond the termination or cancellation of this Contract (or
any part thereof) until the terms and conditions are fully satisfied or expire by their nature:
Sections 5 (Data Use and Security), 6 (Assurances and Liability), 7 (Disclaimer and
Warranties), 8 Dispute Resolution, 1 I (No Employee -Employer Relationship), 12 (No Third -
Party Beneficiaries), 13 (No Implied Waiver), 14 (Severability), 16 (Force Majeure), 17
(Notices), 18 (Governing Law/Consent to Jurisdiction and Venue), and 20 (Entire
Agreement).
20. ENTIRE AGREEMENT.
20.1. This Agreement represents the entire agreement and understanding between the
Parties regarding the Research Study and County Data described in this Agreement and
supersedes all other oral or written agreements between the Parties.
20.2. The language of this Agreement shall be construed as a whole according to its fair
meaning, and not construed strictly for or against any Party.
FOR THE PRESIDENT AND FELLOWS OF HARVARD COLLEGE:
IN WITNESS WHEREOF, Rob Kirsh, Director, Pre -Award Services, hereby acknowledges that
he/she has been authorized by the President and Fellows of Harvard College to execute this
Agreement on behalf of the President and Fellows of Harvard College and hereby accepts and
binds the President and Fellows of Harvard College to the terms and conditions of this
Agreement.
EXECUTED:
Rob Kirsh
DATE:
Director, Pre -Award Services
FOR OAKLAND COUNTY:
IN WITNESS WHEREOF, David T. Woodward, Chairperson, Oakland County Board of
Commissioners, hereby acknowledges that he has been authorized by a resolution of the Oakland
County Board of Commissioners to execute this Agreement on behalf of Oakland County, and
hereby accepts and binds Oakland County to the terms and conditions of this Agreement.
EXECUTED: DATE:
David T. Woodward, Chairperson
Oakland County Board of Commissioners
EXHIBIT 1
COURT OFFICIAL PARTICIPATION CONSENT FORM
Study Title: Reducing Racial Disparities in Bail Decisions
Researchers: Will Dobbie, Harvard University
Crystal S. Yang, Harvard University
Version Date: 2/19/2020
Kev Information
The following is a short summary of this study to help you decide whether or not to be a part of
this study. More detailed information is listed later on in this form.
Why am I being invited to take part in a research study?
We invite you to take part in a research study because you are ajudicial officer in Oakland County
with jurisdiction over criminal and bail proceedings.
What should I know about a research study?
• Someone will explain this research study to you.
• Whether or not you take part is up to you.
• Your participation is completely voluntary.
• You can choose not to take part.
• You can agree to take part and later change your mind.
• Your decision will not be held against you.
Your refusal to participate will not result in any consequences or any loss of benefits that
you are otherwise entitled to receive.
• You can ask all the questions you want before you decide.
Why is this research being done?
We are interested in helping improve judicial decision -making and reduce racial disparities in bail
decisions. Following the completion of the study, we will share our findings with both you and
Oakland County, as well as help implement any "best practices" that we discover during the study.
How long will the research last and what will I need to do?
We expect that you will be in this research study for 30 months. You will be asked to complete a
short survey at the beginning of the study, as well as a second short survey at the end of the study.
We expect each survey to take about 30-45 minutes. We may also provide you with different
decision -making aids during the study, which you are free to use (or not) at your own discretion.
Members of the research team may also attend your courtroom sessions and observe the decision -
making process.
10
Is there any way being in this study could be bad for hne?
The main potential risk from participating in this study is informational privacy, such as breaches
of confidentiality. We perceive these risks as minor, as we intend to fully anonymize the results,
and we will never share your personal data with any outside party, including Oakland County.
More detailed information about the study procedures can be found under "What can I expect if I
take part in this research. "
Will being in this study help hne in any way?
We cannot promise any benefits to you or others from your taking part in this research. However,
possible benefits include valuable insights into your own decision -making process and access to
new decision -making aids. We also believe that your participation could help improve judicial
decision -making and reduce racial disparities in bail decisions in Oakland County.
Detailed Information
The following is more detailed information about this study in addition to the information listed
above.
What is the purpose of this research?
We are interested in identifying interventions that can help improve judicial decision -making and
reduce racial disparities in bail decisions. Racial disparities exist at every stage of the U.S. criminal
justice system but are particularly prominent in the setting of bail. We hope to substantially reduce
or eliminate these disparities through our work with Oakland County, as well as a number of other
jurisdictions around the country.
How long will I take part in this research?
We expect that you will be in this research study for roughly 30 months.
What can I expect if I take part in this research?
If you agree to take part in this study, you will be asked to complete a short survey at the beginning
of the study, as well as a second short survey at the end of the study. We expect each survey to
lake about 30-45 minutes. Both surveys ask about your background and views. The surveys also
include an Implicit Association Test (IAT). The IAT measures the strength of associations between
concepts (e.g.. black people, gay people) and evaluations (e.g., good, bad) or stereotypes (e.g.,
athletic, clumsy). The main idea is that making a response is easier when closely related items
share the same response key. We would say that one has an implicit preference for straight people
relative to gay people if they are faster to complete the task when Straight People + Good / Gay
People + Bad are paired together compared to when Gay People + Good / Straight People + Bad
are paired together.I
Language taken from Project Implicit. More information on the IAT can be found here:
littDs://iiiiD]icit.hai-vat-d.edu/iiiiolicit/facis.htiii]
11
The information collected from the TAT and survey will be linked to administrative case data and
other research data. The survey will be completed using a tablet in person, with the research team
at the beginning and end of the study.
In addition, we may provide you with additional information or decision -making aids during the
study, which you are free to use (or not) at your own discretion. You may interact with researchers
hired to explain the additional information or decision -making aids when they visit Oakland
County.
Finally, we may send members of our research team to sit in on some of your courtroom sessions
to observe and learn from your decision -making process. You may interact with these researchers
when they visit Oakland County.
What happens if I say yes, but I change my mind later?
You can leave the research at any time; it will not be held against you. We will dispose of the data
we have collected by deleting the information from our records.
Is there any way being in this study could be bad for me? (Detailed Risks)
There are limited informational privacy risks, such as breaches of confidentiality. We perceive
these risks as minor, since we intend to fully anonymize all results and we will never share your
personal information with any outside party, including Oakland County.
Additionally, the researchers have applied for a Certificate of Confidentiality from the National
Institutes of Health. With this Certificate, researchers may not disclose or use information,
documents, or biospecimens that may identify you in any federal, state, or local civil, criminal,
administrative, legislative, or other action, suit, or proceeding, or be used as evidence, for example,
if there is a court subpoena, unless you have consented for this use. Information, documents, or
biospecimens protected by this Certificate cannot be disclosed to anyone else who is not connected
with the research except, if there is a federal, state, or local law that requires disclosure (such as to
report child abuse or communicable diseases but not for federal, state, or local civil, criminal,
administrative, legislative, or other proceedings, see below); if you have consented to the
disclosure, including for your medical treatment; or if it is used for other scientific research, as
allowed by federal regulations protecting research subjects.
You should understand that a Certificate of Confidentiality does not prevent you from voluntarily
releasing information about yourself or your involvement in this research. If you want your
research information released to an insurer, medical care provider, or any other person not
connected with the research, you must provide consent to allow the researchers to release it.
If I take part in this research, how will my privacy be protected? What happens to the
information you collect?
Efforts will be made to limit the use and disclosure of your personal information to people who
have a need to review this information. We will allow only research staff and the Principal
Investigators to see the original information that include personal identifiers.
12
We plan to publish the results of this study. We will protect the confidentiality of your research
records by fully anonymizing the results. Your name and any other information that can directly
identify you will never be shared in our results, or with any outside party such as Oakland County.
Can I be removed from the research without my OK?
The person in charge of the research study or the sponsor can remove you from the research study
without your approval. Possible reasons for removal include Oakland County leaving the research
study, or other judges in Oakland County leaving the study.
What else do I need to know?
Funding - This research is being funded by J-PAL North America.
Compensation - You will not receive any compensation for your participation in this study.
Who can I talk to?
If you have questions, concerns, or complaints, or think the research has hurl you, talk to Professor
Crystal Yang at Harvard University, available by email at cvan2(&,Iaw.harvard.edu. You can also
contact the research team at the dedicated email address pretrialstudy(i�hks.harvard.edu.
This research has been reviewed and approved by the Harvard University Area Institutional
Review Board ("IRB"). You may talk to them at (617) 496-2847 or cuhs(a,)I1arva1d.edu if.
• Your questions, concerns, or complaints are not being answered by the research team.
• You cannot reach the research team.
• You want to talk to someone besides the research team.
• You have questions about your rights as a research subject.
• You want to get information or provide input about this research.
13
Signature Block for Adult subject (Judicial Officer)
Your signature documents your permission to take part in this research.
Signature of Subject
Printed Name of Subject Date
Signature of Person Obtaining Consent Date
Printed Name of Person Obtaining Consent
14
EXHIBIT 2
REQUIREMENTS FOR ACCESS TO COUNTY PII
(Personally Identifiable Information)
This Exhibit governs the requirements for Harvard to have access to the Personally Identifiable
Information (PII).
1. DEFINITIONS
1.1 Security Breach means the unauthorized access, acquisition, theft, or disclosure of PII
that was provided by County to Harvard.
1.2 PH has the meaning provided above in the main Agreement.
2. OBLIGATIONS
2.1 Harvard shall not use or disclose PII other than as permitted or required by this
Agreement or as required by law.
2.2 Harvard shall implement administrative, physical, and technical safeguards (including
written policies and procedures) that reasonably and appropriately protect the
confidentiality, integrity, and availability of PII that it receives, maintains, or transmits
from or to the County.
2.3 Harvard shall mitigate, to the extent practicable, any harmful effect known to Harvard of
the use or disclosure of PII in violation of law or this Agreement.
2.4 If Harvard discovers a Security Breach, Harvard shall notify the County without
unreasonable delay, but no later than within forty-eight (49) hours of discovery. For this
purpose, "discovery" means the first day on which the Security Breach is known to
Harvard. The notification to the County shall include the following: (a) describe the
Security Breach in general terms; (b) describe the type of personal information that is the
subject of the Security Breach; (c) identify each individual whose PII has been breached
or has reasonably believed to have been breached; (d) describe in general terms, what
Harvard has done to prevent additional Security Breaches; and (e) provide any other
available information in Harvard's possession that may be necessary to comply with
Security Breach notification laws.
2.5 If the County determines it will provide the notice of the Security Breach to the affected
individuals and/or to governmental authorities, Harvard shall reimburse the County for: (a)
its costs in notifying the affected individuals; (b) the cost of third -party credit and identify
monitoring services to each of the affected individuals with compromised PIT for no less
15
than twenty-four (24) months following the date of notification to each individual; and (c)
costs associated with the Security Breach, including but not limited to any costs incurred by
the County in investigating and resolving the Security Breach, including reasonable fees
associated with such investigation and resolution. Notwithstanding anything to the
contrary, Harvard shall indemnify, reimburse, defend, and hold harmless the County for
any and all claims, including reasonable attorneys' fees, costs, and incidental expenses,
which may be suffered by, accrued against, charged to, or recoverable from the County in
connection with the Security Breach. Harvard shall reimburse County for the applicable
costs described above within thirty (30) days of receipt of an itemization of costs incurred
by the County because of the Security Breach.
2.6 Within ten (10) calendar days of its discovery of the Security Breach, Harvard shall
provide the County with a detailed plan describing the measures Harvard will undertake
to prevent a future Security Breach. The County shall have the right to audit, inspect and
test Harvard's new safeguards put in place because of the Security Breach.
16
Reducine Racial Bias in Bail Decisions
Katherine Baldiga Coffman (Harvard), Will Dobbie (Princeton), and Crystal S. Yang (Harvard)
Motivation: Racial disparities exist at every stage of the U.S. criminal justice system. Compared
to observably similar whites, blacks are more likely to be searched for contraband (Antonovics
and Knight 2009), more likely to experience police force (Fryer 2016), more likely to be charged
with a serious offense (Rehavi and Starr 2014), more likely to be convicted (Anwar, Bayer, and
Hjalmarrson 2012), and more likely to be incarcerated (Abrams, Bertrand, and Mullainathan 2012)
Racial disparities are particularly prominent in the setting of bail: in Philadelphia and Miami -Dade,
for example, black defendants are 3.6 percentage points more likely to be assigned monetary bail
than white defendants and, conditional on being assigned monetary bail, receive bail amounts that
are $9,923 greater.
Racial disparities are perhaps unsurprising given that bail judges must make on -the -spot judgments
with limited information. Typical bail hearings in many jurisdictions last less than five minutes
and often involve defendants being videoconferenced into the courtroom from the local jail. These
institutional features make bail decisions particularly prone to the kind of inaccurate stereotypes
or categorical heuristics that can generate racial bias (e.g., Fryer and Jackson 2008; Bordalo et al.
2016) and poor decision -making (e.g., Klemberg et al. 2018). Indeed, we find in prior work that
bail judges are racially biased against black defendants, with substantially more bias among both
inexperienced and part-time judges (Arnold, Debbie, and Yang 2018). We also find suggestive
evidence that this racial bias is driven by bail judges relying on inaccurate stereotypes that
exaggerate the relative danger of black defendants.
In this project, we are interested in partnering with state courts to identify interventions that
can help improve decision -making and reduce racial disparities and bias at the pre-trial
justice stage.
Our Interventions: Reducine Stereotvnical Thinkine & Providine Individualized Feedback
We have designed two types of interventions aimed at reducing racial bias in judicial decision -
making. The first is an intervention that directly confronts racial bias and attempts to slow down
and systematize judicial decision -making. We describe the components of this intervention below:
Information Provision on the Distribution of Risk by Race: The first part of our
intervention is to simply provide information to judges on the actual distribution of risk
of pretrial misconduct by race. The goal of this first part is to reduce bias in judges'
beliefs about differences in defendant risk by race by providing accurate information
on true differences. In particular, we aim to correct mistaken beliefs which can arise if
judges erroneously assume that black defendants are far riskier compared to white
defendants than supported by data. We will create accessible, engaging materials, such
as a two- to three -page informational handout, that provide descriptive statistics of
predicted risk by race using historical data. If possible, this information will be based
on historical data from the judge's own local area; if not possible, we plan to use
nationally representative data instead. This information would be delivered at the very
beginning of the intervention. This approach will be low-cost and highly scalable.
What research supports this type of intervention? Past work, including Arnold, Dobbie,
and Yang (2018), suggests that biased beliefs about differences in risk by race could be
an important factor in explaining racial bias in bail decisions. In their work on
stereotyping, Bordalo et al. (2016) show that individuals' perceptions of a group are
shaped by particularly salient differences relative to some reference group. In the case
where two groups are distributed quite similarly over outcomes, as in the case of
differences in risk by race, individuals often put too much weight on unlikely but highly
diagnostic tail outcomes, leading them to exaggerate the mean difference between the
groups. By providing accurate information on the trite distributions and emphasizing
the similarity in the distributions through statistics on the mean, median, and modal
outcomes for each group, we aim to reduce bias in beliefs.
Our plan is to work closely with partner districts and expert bail judges to develop these
materials. We have developed an initial prototype of an informational handout, attached
here as Exhibit 1. On the first page, we will show the distribution of predicted risk
(probability of rearrest and/or failure to appear prior to case disposition conditional on
release), conditional on the initial crime and other observable demographics of
offenders, by race. We are also structuring this information such that it emphasizes the
high degree of similarity by race. Specifically, we will not only present highly similar
distributions of predicted risk by race, but also very similar surnmary statistics at
different points in the distribution (2511, percentile, median, mean, 751" percentile).
We will also show the distribution of perceived risk (the probability distributions of
risk that judges must believe in order to justify the observed racial gap in release rates)
next to the distribution of predicted risk. This distribution of perceived risk will show
that judges exaggerate the risk of black defendants relative to white defendants
compared to the predicted risk distribution. This comparison between predicted and
perceived risk is meant to highlight to judges that their actions are based on incorrect
beliefs.
On the second page, we will provide additional summary information on predicted risk
for some of the most common types of offenders that bail judges encounter, such as
first-time non-violent offenders. For these buckets of crimes, we will state what the
most likely risk level is for a defendant of each race, based on historical data (likely to
be low, and nearly identical by race, in most districts given past evidence on this issue).
Again, this information will highlight the near identical predicted risk for black and
white defendants across different subsamples.
Finally, we will present a simple diagram to show j udges what the racial gap should be
based on predicted risk compared to what it is in actuality. Because of the nearly
identical distributions of predicted risk for black and white defendants, the racial gap
in release should be substantially smaller than what we observe in practice. This type
of information may prompt judges to move towards greater racial parity in release rates
in the future.
Generalized Benchc•ards: In the second component of our intervention, we will provide
additional decision assistance at the time of the bail decision to each judge. We plan to
provide judges with a simple "benchcard" that is meant to prompt them to consider
different areas important to the bail decision -making process, even giving them
potential questions to ask. In prior work, Russell and Summers (2013) provided six
laminated cards to judges injuvenile preliminary protective hearing cases that included
a checklist of all persons who should be present at the hearing, a checklist of tasks to
ensure that key parties and witnesses are present, a checklist on the important factors
to consider the petition/complaint, an extensive list of questions to ask and assess, and
a set of questions aimed at protecting against institutional bias. Russell and Summers
(2013) find that a substantial and persistent fall in racial when judges are given these
benchcards. We anticipate providing a relatively similar set of questions to bail judges,
which we will form in consultation with practicing bail judges in each jurisdiction.
Importantly, these benchcards do not provide judges with information on the specific
case. As a result, this is a very low-cost intervention.)
Our plan is to again to work closely with partner districts and expert bail judges to
develop our benchcard. We have developed an initial prototype of this benchcard,
attached here as Exhibit 2. Notice that our benchcard asks judges to systematically
consider a range of important factors relevant to the bail decision. For example, we
first ask a series of questions about the defendant's offense and past criminal history,
as well as the defendant's risk of flight and danger to the public. We then ask the judge
to consider the consequences of pretrial detention on the defendant by shifting their
focus to employment, child custody, and physical/mental/substance abuse issues. We
also present the judge with a series of questions about the options for release, beginning
with the least restrictive non -cash alternatives. For judges who are thinking about cash
bail, we ask the judge to evaluate the financial situation of the defendant and assess
whether the defendant can afford to pay the assigned cash bail.
Finally, we will directly prompt judges to recall decision they have made for similar
defendants in the recent past, focusing them on a comparison set defined by risk factors
such as crime committed and previous offenses, rather than demographics like race.
This creates a clear reference set for the judge, increasing the likelihood of consistent
decisions over time. We believe that the idea of a prompted comparison set promises
to be effective given work by Bohnet et al. (2016) that shows that joint evaluation, or
evaluating a candidate relative to other similar candidates rather than in isolation,
reduces bias and improves decision quality. Not only does this type of intervention
allow judges to focus on common features across defendants, but by placing defendants
"side -by -side," it decreases the amount of moral wiggle room for discriminatory
behavior. That is, it will make it harder to justify, to oneself or to an outside observer,
different decisions by race when that difference is so starkly apparent. In addition,
comparison sets may foster re -categorization of defendants on characteristics other than
race.
' See here for additional information on the Russell and Summers (2013) benchcard:
http://www.ncjfcj.org/sites/defatilt/files/CCC%2OBench%2OCard%201nsertsfmal.pdf
Our second intervention aims to leverage the power of our de -biasing intervention by providing
individualized feedback to judges over time.
Individualized Feedback: We will provide judges with individualized feedback on their
past performance, including their own release rates and their own type I errors (rate of
pretrial misconduct conditional on release). We would start by providing historical
information but would also provide updated information as the experiment progresses. This
treatment aim therefore gives judges a chance to see if their changed behavior maps to
improved outcomes. This is a standard practice used in other settings such as using teacher
value added to evaluate teachers (Harris 2008), surgeon report cards for medical
professionals (Dranove et at. 2003), school report cards for failing school districts (No
Child Left Behind Act 2001), and so on.
This feedback mechanism, which we believe is mostly missing from the current pretrial
system, might allow judges to learn if their initial heuristics/stereotypes are in fact accurate
and allow them to adjust their decisions moving forward. For example, judges may be
surprised to learn that not many defendants commit new crimes conditional on release,
revising their beliefs on the distribution of risk. Without this type of feedback, judges will
only regularly interact with defendants who have committed pretrial misconduct, which
can lead to distorted views on the riskiness of individuals who are released.
In addition, if we provide feedback in relative terms, judges who are "underperforming"
relative to others in the court may be more eager to change their behavior. This would be
in line with past work that has shown that providing social comparison information can
motivate under -performers (see Perez-Truglia and Troiano (2016) on taxes and Allcott
(2009) on energy use). This feedback provision may also increase the perceived meaning
and impact of their work, providing further motivation (Ariely et al. 2008).
As with our other interventions, our plan is to work closely with partner districts and expert
bail judges to develop these report cards, which we anticipate providing to judges on a
monthly basis. We have developed an initial prototype, attached here as Exhibit 3. On the
first page, we will show the judge's release and misconduct rates over the past month, as
well as three points of comparison for the j udge. The first point of comparison is the judge's
own historical data, facilitating self -comparisons. The second point of comparison is all
other judges in the same area, facilitating relative comparisons. The third and final point
of comparison is "best judges" in the same area, where we define best judges as the 25
percent of judges who have the highest release rates and the lowest pretrial misconduct
rates. These best judges are the highest -performing judges given that they simultaneously
release more defendants and have lower rates of pre-trial misconduct than the average or
typical judges in the area. On this first page, we will also provide concrete steps that the
j udge can take to improve his or her performance on these outcomes, with those steps based
on what we observe among the highest -performing judges in the area. For instance, we
may provide individualized tips to each judge relative to the best judges, such as
"Compared to you, the best judges impose ROR 10 percent more among first-time
misdemeanor defendants, one of the lowest -risk groups." These concrete tips can help
translate the relative comparisons into actionable steps.
The second page of our report card shows the judge's release rate "gap" for white and
nonwhite defendants over the previous month. We will construct this measure by
considering all cases the judge has handled over the previous month, and estimating the
difference in release after controlling for important crime and defendant characteristics.
Like the performance measures reported on the first page, we will provide points of
comparison based on the judge's own historical data to facilitate self -comparisons over
time. We will also again provide concrete steps that the judge can take to decrease his or
her release rate gap, in particular by comparing the judge's own racial gap to that of best
judges in the local area. For example, a concrete tip might be "Compared to you, the best
judges have no racial gap in ROR rates among first-time misdemeanor defendants, one of
the lowest -risk groups."
Impact Evaluation
We will conduct a randomized controlled trial (RCT) to identify the causal impact of our
interventions on racial disparities in bail settings. To maximize our statistical power, we plan on
using a within -subject design, enabling each judge within our sample to serve as his or her own
"control" group.
For all judges, at the beginning of our full-scale project, we will provide very basic awareness
training on bias in bail decisions (e.g., existing DOJ video or Race: The Power of an Musion,
Episode: "The House We Live In", as used in Russell and Summers (2013)). The goal is to prime
judges to be more receptive to the interventions. We will also administer a baseline Implicit
Association Test (IAT) to all judges, as the IAT has shown to be highly correlated with measures
of bias and stereotyping behavior in the real world (Glover, Pallais, Pariente 2017, Carlana 2018).
In addition, we will collect baseline demographic information and survey measures of bias.
Our plan for randomization is to randomize all judges within our sample into our interventions
over time. We will randomize the timing of the roll -out across judges in order to identify the causal
impact of our interventions. All judges will begin as part of the control group, receiving no
additional intervention. Between 6 — 10 months after the beginning of the experiment, judges will
begin to be randomized into either receiving our de -biasing intervention or our feedback
intervention. The timing of this roll -out will be randomized at the individual level. This will allow
us to identify the causal impact of each of these interventions in isolation. Then, to maximize
statistical power and to investigate the interactive effects of the two interventions, each participant
will eventually be randomized to receive the other intervention, in addition to one they were
already receiving. This research design is illustrated below.
Control stage
Dp,-Biasing Intervention
De -Biasing, Intervention & Individualized
Feedback
Individualii:ed Feedback
De -Biasing Intervention & Individualized
Feedback
We envision that each judge will remain in each phase of the experiment for approximately 8
months on average, with variation between 6 — 10 months to allow for randomized timing of the
roll -outs.
Both during and after the intervention, we will work with court administrators to obtain data on
bail decisions and pre-trial misconduct rates (both new crime and failure to appear), in the
aggregate and separately by defendant race. After the study is complete, we will compare racial
disparities in bail decisions and pre-trial misconduct rates among each of the treatment groups and
the control group. We will also incorporate post -intervention surveys into our study in order to
better understand how judges interpreted and utilized the intervention they received.
Team of Researchers: Our team of researchers is well-equipped to accomplish this project.
Collectively, we have vast expertise in field experiments and lab experiments. We also have years
of experience working with both survey and administrative data. All three researchers have
research agendas devoted to understanding bias and stereotyping in a variety of settings. We also
have support from our respective institutions at Harvard and Princeton, where we can access pre-
existing lab settings for our study.
Exhibit 1: Preliminary Facts about Pretrial Misconduct Risk
Actual Risk Perceived Risk
White and Nonwhite Defendants White and Nonwhite Defendants
0
m
ii
N
White
Nonwhite -
25th P.
0.11
0.13
Median
0.18
0.20 —
75th P.
0.27
0.31
4 .6
Nonwhite White
White
Nonwhite
25" P.
0.11
0.24
Median
0.18
0.32
751h P.
0.27
0.42
a 1 co-
o
w
N
r
Nonwhite White
KEY TAKEAWAY
• Actual risk is nearly identical for white and non -white defendants
® But judges misperceive nonwhite defendants to be 10% riskier on average
80%
75%
69%
70%
65%
61%
3
tscYy:
as'il
-
Using Predicted Risk
Using Perceived Risk
OWhites
uu Nonwhites
® The racial gap in release should only be 4% based on actual risl<
• But the observed racial gap is 1.4%, 250% larger than justified
8
RMrmrtui I . R ►.
Vefenclants withoutpriors
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
82% 80%
84%
78%
.i
+a ;
r 9
N� v�
fs
Using Predicted Risk Using Perceived Risk
❑Whites mNonwhites
e The racial gap in release should only be 2% based on actual risk
• But the observed racial gap is 6%, 200% larger than justified
"ILTZMATMALIMUMIMM
defendants charge+ with a misdemeanor
80%
70%
60%
50 %
40%
30%
20%
10%
0%
74% 71%
76%
69 %
Using Predicted Risk Using Perceived Risk
❑ Whites t, Nonwhites
® The racial gap in release should only be 3% based on actual risk
® But the observed racial gap is 7%, 133% larger than justified
R
� w
Exhibit 2: Preliminary Arraignment Hearing Bencheard
ASK YOURSELF, AS A JUDGE:
• What are the nature and circumstances of the offense? Was the offense
committed while the defendant was awaiting trial for a prior charge?
• Does the defendant have a past criminal record or any outstanding warrants?
• What is this defendant's risk of failing to appear for a required court
appearance? Does the defendant have a past history of failing to appear for
court appearances?
• What is this defendant's risk of endangering the public? Does the defendant
have a past history of committing a new crime while on bail for a prior
charge?
• Does the defendant have strong ties to family or the community that may
mitigate these risks?
• Is the defendant cuff ently employed, and could detention lead to job loss?
• Does the defendant have any children/dependents, and could detention affect
these childcare responsibilities?
• Does the defendant have any physical, mental, or substance abuse issues,
and could detention affect these issues?
• What are the non -cash alternatives that are available in this case? What is the
least restrictive of these non -cash options that would ensure the defendant's
appearance at court and protect the public?
• What are the financial resources of the defendant? If I assign cash bail, is the
assigned bail amount too high for the defendant to pay?
• Have I made any assumptions about the cultural identity, gender, and
race/ethnicity of this defendant?
• In the past, what conditions have I assigned for similar defendants of the
same race? Of a different race?
Exhibit 3: Preliminary Individualized Feedback on Arraignment Decisions
Best Judges 70.0%
All Judges dMIOWS9.0%
June 1, 2019— September 1, 2019. This Is based on the otherjudges In
your a rea with a similar caseload. Best judges are the 25% of judges who
have the highest release rates and lowest pretrial misconduct rates.
Great
Good
Average or Below Average
10 fewer releases
compared to the best judges
Compared to you, the best judges impose ROR 10 percent more among first-time
misdemeanor defendants, one of the lowest -risk groups.
Compared to you, the best judges are 5 percent less likely to impose money bail among first-
time misdemeanor defendants, one of the lowest -risk groups.
Here's your white-rionwhite gap in release rates
White Defendants 69.0%
Gap 8.Opp
June 5, 2019 — September 5, 2019. This is based on your awn release rates.
Great
Good
Average or Below Average
8% higher
compared to racial parity
Ti" ark your progress in white nonwhite gap in release rates
Y
Aug
Sep
Oct
Nov
Dec
'rips, from the best jl.lciges
Compared to you, the best judges have no racial gap in ROR rates among first-time misdemeanor
defendants, one of the lowest -risk groups.
Compared to you, the best judges have only a 5 percent racial gap in money bail rates among first-
time misdemeanor defendants, one of the lowest -risk groups.
The three outcomes we are measuring
Release Rates
This measure is defined as the fraction of defendants who are released pretrial.
FTA Rates
This measure is defined as the fraction of released defendants who fail to appear to
their court date.
White -Nonwhite Gap in Release Rates
This measure is defined as difference in release rates for the white and non -white
defendants.
ire uentl aslted qut�stior�s
How do we compare you to other judges?
In both comparisons to "All Judges" and "Best Judges," we compare you to other judges in your local area who see a
similar caseload during the relevant time period. A similar caseload means that these otherjudges saw a similar
distribution of cases (e.g. felony vs. misdemeanor, first-time vs. repeat offender).
How do we define "Best Judges"?
We define best judges as the 25%of judges who have the highest pretrial release rates and lowest pretrial
misconduct rates in your area.
How do we define release rates?
We define release rates as the fraction of defendants who are released pretrial.
How do we define FTA rates?
We define release rates as the fraction of released defendants who fail to appear to their court date.
How do I stop receiving reports?
Call 1-888-888-8888.
We're here to help
person n princeton.edu
Y 1-888-888-8888
Resolution #20654 December 7, 2020
Moved by Gingell seconded by Luebs the resolutions on the amended Consent Agenda be adopted..
AYES: Gingell, Hoffman, Jackson, Kochenderfer, Kowall, Kuhn, Long, Luebs, Markham,
McGillivray, Middleton, Miller, Nelson, Powell, Quarles, Spisz, Taub, Weipert, Woodward, Zack,
Gershenson. (21)
NAYS: None. (0)
A sufficient majority having voted in favor, the resolutions on the amended Consent Agenda were adopted.
4Ad','?E7Vl T HIS Sl)t.LfTiON
CHIEF DE7 U TY COUNTY FXKUTIWE
ACTING PURSIJANTTO MCL 45 rw59A (1)
STATE OF MICHIGAN)
COUNTY OF OAKLAND)
I, Lisa Brown, Clerk of the County of Oakland, do hereby certify that the foregoing resolution is a true and
accurate copy of a resolution adopted by the Oakland County Board of Commissioners on December 7,
2020, with the original record thereof now remaining in my office.
In Testimony Whereof, I have hereunto set my hand and affixed the seal of the Circuit Court at Pontiac,
Michigan this 71' day of December, 2020.
I' �` 9
Lisa Brown, Oakland County