Nora Wikoff, MSLS, MSW WILL THE REAL NONPARTICIPANTS PLEASE
STAND UP? Exploring selection bias and treatment contamination in
employment programs Slide 2 AGENDA Reentry context in New York
State Knowledge base: work, finances, and crime Aims and research
questions Research findings Practice and research implications
Ongoing and future research Slide 3 REDUCING THE MADNESS OF AN
INCARCERATION SOCIETY* 25% decline in NY prison population
Declining crime rates in NYC Rockefeller drug laws reform Cuomo:
reduce fiscal burden on the state 11 recent, 4 planned prison
closings Reinvest in preventive and rehabilitative services *Cuomo,
2014 Slide 4 PRISON REDUCTION STRATEGIES Council on Community
Re-Entry and Reintegration State council to help nonviolent
offenders $5 million proposed FY14 investment in programs:
Workforce Investment Board: Oneida County TASC Case management and
reentry services Strategies include job training and supported work
Slide 5 JOBS PROGRAM LOGIC MODEL Services Life skills Transitional
jobs Job coaching Job development Supportive services Increased
Employment Income Soft skills Work readiness Stability Increased
Employment Job retention Reduced recidivism Slide 6 WEAK EVALUATION
SUPPORT Programs do not appear to improve work outcomes or reduce
crime Experimental studies: Most jobs programs show modest or null
effects Positive effects observed among: Older former prisoners
High-risk prisoners Slide 7 LABOR FORCE PARTICIPATION Before prison
Rising unemployment High levels of work instability High job
turnover After release Initial boost in formal employment Rates
decline to pre-prison levels within three years Slide 8 LABOR FORCE
NONPARTICIPATION Low opportunity cost to crime Limited job options
available Limited formal work experience Weak labor market skills
High opportunity cost to formal employment Low hourly wage, reduced
leisure time Garnished wages (e.g., child support, legal debts)
Risk detection at workplace Slide 9 RESEARCH QUESTIONS, PART 1 Do
respondents exhibit distinct arrest trajectories before entering
prison? Do participants differ from nonparticipants along prior
arrest trajectories? Do employment programs improve mens post-
release employment and recidivism outcomes? Slide 10 RESEARCH
QUESTIONS, PART 2 Is labor force non-participation associated with
increased recidivism risk? Is labor force participation associated
with higher quality employment? What factors break the association
between employment and reduced offending? Slide 11 RESEARCH AIMS
Examine whether evaluation findings reflect Mens selection into
employment services Contamination from participation in similar
programs Examine whether effects persist after controlling for
Prior criminal record Work experience Participation in programs
that offer overlapping content Slide 12 SERIOUS AND VIOLENT
OFFENDER REENTRY INITIATIVE (SVORI) Target Population: Adult male
prisoners under 35 years old Convicted of violent or serious drug
offenses States designed services to fit local context
Intent-to-treat design Propensity score weights: SVORI service
receipt Slide 13 DATA SOURCES FBI National Crime Information Center
Lifetime adult arrest records Spanning state lines and agency
reporting systems SVORI Evaluation baseline interviews Conducted in
prisons during month before release Demographics, background,
criminal history, prison experiences, physical/mental health Slide
14 DESCRIPTIVE STATISTICS (N = 1,575) VariableDefinitionN / M% / SD
AgeAt release from prison29.6(7.3) Sentence lengthTime served by
date of release2.6(2.6) EducationLess than high school
diploma63340.2 High school diploma22814.5 GED45629.0 Trade
certificate, Some/more college25616.3 Racial/ethnic statusAfrican
American87255.4 Hispanic, Multi-racial, Other18611.8 White51532.7
EmploymentWorked last 6 months before prison1,04066.1 Ever held job
for 2/more years49638.1 Job terminationFired from one job31626.4
Fired from more than one job33928.4 Slide 15 TRAJECTORY MODEL
Predictor variables, final model: Age at each arrest: Linear and
squared terms Indicator of arrests during 10 years before SVORI
term State indicator for prison site Age at release from prison
Lifetime adult arrest record: Natural log transformation Outcome
variable: Predicted probability of group membership Slide 16
PRE-SVORI ARREST TRAJECTORIES Probability of arrest each year Age
at arrest High (38.9%) Middle (45.1%) Low (16.0%) Slide 17 CRIMINAL
HISTORY: TRAJECTORY GROUPS (High) n = 616(Mid.) n = 706(Low) n =
253 N / M% (SD)N / M% (SD)N / M% (SD) Age at first
arrest***15.4(3.4)16.3(4.5)18.4(8.2) Lifetime
arrests***22.7(13.5)11.3(6.5)3.2(2.1) Lifetime
convictions***6.2(5.5)5.0(4.5)2.8(3.3) Times in
prison***1.9(1.6)1.2.(1.3)0.7(1.1) SVORI term: Age at
release***28.8(6.5)30.3(7.3)29.6(8.8) Sentence
length***2.0(1.6)2.6(2.5)3.9(4.1) Parole
violation12424.516427.84220.2 Violent
offense***20233.128640.615662.2 Property
offense*16426.816823.94417.5 Drug offense***26843.923433.23915.5
Slide 18 DEMOGRAPHICS: TRAJECTORY GROUPS (High) n = 616(Mid.) n =
706(Low) n = 253 N / M% (SD)N / M% (SD)N / M% (SD) Education ***
Less than HSD29848.526337.37228.5 High school
diploma7912.910815.34116.2 GED17428.319127.19136.0 Trade
school/some coll.6310.214420.44919.3 Race*** African
American39464.237653.310240.3 Hispanic, multi-racial,
other569.18512.04517.8 White16426.724534.710641.9 Worked before
prison***36358.950070.817770.2 Slide 19 GROUP CHARACTERISTICS
High-level group Young, African American high school dropouts
High-rate property and drug offenders Low-level group Older, White
or Hispanic, high school graduates Low-rate violent offenders
Mid-level group Similar demographic profile to low-level group
Slide 20 PARTICIPATION: TRAJECTORY GROUPS (High) n = 616 (Mid.) n =
706 (Low) n = 253 Percentages engaged in each type of
employment-focused program Participation in each type of
program49.758.161.3 Education programs (e.g., GED, literacy,
college classes) 40.746.654.2 Work readiness or job training
programs19.322.524.5 Prison job (work release or prison
industry)6.38.68.7 Participation in more than one program7.39.312.0
Slide 21 PROPENSITY SCORE MATCHING Multilevel logistic regression
model Stata xtmelogit SVORI treatment condition, Prison site
(state) Individual-level characteristics Matching techniques Stata
psmatch2 Radius matching with caliper (.2 SD/ln odds) Common
support condition, ties permitted Slide 22 CRIMINAL HISTORY:
PARTICIPATION Unm.TotalNon.Emp.Educ.Job 2691,304658152515102 Age at
first arrest***16.116.3*16.616.515.617.6 Lifetime
arrests***2.32.3***2.52.2 2.4 Lifetime convictions*** 5.1
5.34.84.95.4 Times in prison***1.31.5***1.71.31.21.5 SVORI term:
Age at release***28.5** 29.8** * 30.928.528.131.5 Sentence
length***4.3***2.2***1.92.52.42.6 Parole
violation15.2***25.327.121.721.628.4 Violent
offense***53.3***38.636.439.743.130.7 Property
offense*25.223.824.425.822.719.8 Drug
offense***26.3**36.336.039.134.538.6 Slide 23 DEMOGRAPHICS:
TRAJECTORY GROUPS Unm.TotalNon.Emp.Educ.Job 2691,304658152515102
Education ******* Less than HSD47.638.737.224.345.026.5 High school
diploma13.414.719.611.27.613.7 GED24.529.926.135.534.838.2 Trade
school/some coll.14.516.617.128.912.621.6 Race****** African
American51.756.258.153.955.542.2 Hispanic, multi,
other20.410.08.811.8 9.8 White27.933.733.134.232.648.0 Worked
before prison*** 56.3***68.167.871.166.284.3 Slide 24 PRISON SITE:
PARTICIPATION Unm.TotalNon.Emp.Educ.Job State site
***2691,304658152515102 Iowa8.111.29.729.610.98.8
Indiana4.811.013.45.310.32.0 Kansas7.03.85.20.72.91.0
Maryland11.816.521.48.610.518.6 Missouri14.83.22.61.33.92.9
Nevada9.29.38.514.510.72.9 Ohio11.83.92.65.35.82.0
Oklahoma5.95.74.76.66.26.9 Pennsylvania4.87.96.45.98.721.6 South
Carolina11.423.722.319.726.028.4 Washington10.33.83.22.64.14.9
Slide 25 LINGERING DIFFERENCES Participants Younger mean age of
first arrest Younger mean age at release Longer mean SVORI prison
term Nonparticipants Higher mean arrest total Higher mean prison
terms More likely to have high school diploma Slide 26 DURATION
MODEL MEASURES Duration models Indicators of three employment
services Indicator of multiple service receipt Demographic
characteristics Indicator for work before prison Criminal history
Slide 27 HAZARD RATIOS: TIME TO FIRST ARREST Slide 28 DURATION
MODEL FINDINGS Shorter time to first rearrest Participation in
multiple employment programs African Americans (ref. White)
Property offender Parole violator Longer time to first rearrest
Older age at release from prison GED or trade certification Slide
29 STRENGTHS AND LIMITATIONS Trajectory model Varying length of
criminal records Unobserved heterogeneity Propensity score model
Lingering observed heterogeneity Unobserved heterogeneity Limited
common overlap Duration model Variation in quality and quantity of
services received Official data: timing and observation Slide 30
PART 2: JOB QUALITY MODEL norawikoff.wordpress.com Slide 31
IMPLICATIONS: RESEARCH Direction of the work-crime relationship
Factors that contribute to labor force exit Low wages, debts,
garnishments, financial strain Factors that increase labor force
attachment Slide 32 IMPLICATIONS: PRACTICE Program design Offer
intensive programs to a select few Use desistance signals to
identify participants Program evaluation Model the selection
process (not cream-skimming) Service delivery Address financial
challenges Slide 33 OTHER RESEARCH SEED for Oklahoma Kids (SEED OK)
Test of universal Child Development Accounts Experimental study
design Better Futures Enterprises (Twin Cities, MN) Social
enterprise providing subsidized housing and supported employment to
homeless men Pay-for-success agreements with nonprofits and
governmental agencies Slide 34 FUTURE RESEARCH: PATHWAYS TO
DESISTANCE Life events and transitions during early adulthood Model
employment and offending trajectories Examine effect of
interventions and programs 7-year follow-up period (84% retention)
Multiple data sources: self-report, official, and collateral
reporters Slide 35 ACKNOWLEDGEMENTS This research is supported by a
research grant from the National Institute of Justice: NIJ Graduate
Research Fellowship Grant Award #: 2013-IJ-CX-0042 Project Period:
11/1/13 7/31/14 Slide 36 CONTACT INFORMATION Nora Wikoff Brown
School of Social Work Washington University in St. Louis
[email protected] [c] 314-703-8731 norawikoff.wordpress.com
