Abstract
Previous studies have examined extralegal variables that influence sentencing outcomes. In this study, we examine the role of location on sentencing outcomes. Using data from the Minnesota Sentencing Guidelines, we hypothesize that rural counties are more likely to sentence individuals to prison compared to urban counties. With the growth of community alternatives and decarceration, we believe urban areas will utilize community-based sanctions more whereas rural areas have limited alternatives or barriers to accessing them and thus, will rely on incarceration. Controlling for legal and extralegal factors, the findings illustrate how sentencing practices differ by location as it relates to the use of community alternatives, jail incarceration, and state prison. The implications offer insights into what may explain these differences.
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Notes
As an illustrative example, according to the 2015 standard sentencing grid (see Appendix X), a defendant convicted of an offense that falls into the 9th offense seriousness category and with a criminal history category of 4 would have (a) a presumptive state prison sentence, (b) a presumptive sentence of 88 months of incarceration, and (c) eligibility for a sentence between 75 and 105 months without being considered a departure.
1 case was coded as receiving both a stay of imposition and a stay of execution. 4 cases were coded as not receiving a stayed sentence but receiving a conditional sentence to a local jail (a local alternative). 43 cases were coded as not receiving a stayed sentence but receiving “intermediate sanctions” – outside of a stay of imposition, execution, or prison commitment.
Given that we control for presumptive sentence and criminal history, we do not control for custody status. Custody status is taken into account when determining both the presumptive sentence and criminal history. Thus, to avoid “triple counting” it’s effect, we exclude it from the current analysis.
In the MSGC codebook, the plea measure is described as “Plea Entered? Yes/No.” This led us to investigate whether this mean that a plea deal happened or whether it was just the verbalization of a plea. To look into this, we went to the MSGC annual reports in which are based on the data in this study. In the 2015 MSGC Annual Report, they state that “97% of felony convictions were obtained without a trial.” This matches the “plea” variable in the MSGC Monitoring dataset which suggested that 3.38% of cases had a “Not Guilty Plea” entered and thus settled via some sort of adversarial process (i.e. summary judgement, bench trial, jury trial).
There is disagreement in the sentencing literature about whether to control for departures in multivariate models. While some studies do include departure controls (Albonetti, 1991; Doerner & Demuth, 2010; Feldmeyer & Ulmer, 2011), recent legal research has advocated against it (Fischman & Schanzenbach, 2011; Starr & Rehavi, 2012). Specifically, recent research argues that by controlling for departure status, temporal ordering is not kept and that the decision to depart is not separate from the disposition decision. While we recognize this disagreement this study aligns with the more recent literature and does not include a control for departure status.
The OMB classification scheme breaks counties into 6 categories: Large Central Metro, Large Fringe Metro, Medium Metro, Small Metro, Micropolitan, Noncore. Our measure codes the former four metro counties as urban and the latter 2 micropolitan/noncore counties as rural. 27 counties were classified as urban and 60 counties were classified as rural.
In other words, not surrounding the Twin cities. Minneapolis/St. Paul account for roughly 55% of the citizens in Minnesota and 51% of the cases sentenced under the Minnesota Sentencing Guidelines from 2009 to 2015 (United States Census, 2019; MSGC, 2015).
No interclass correlation coefficient is offered because logistic regression models do not estimate level 1 variance components (see Byrk & Raudenbush, 1992. However, the following are the confidence intervals for the between-district variance components. Level 2 variance component from unconditional logistic regression model examining state prison [0.04,0.08]. Level 2 variance component from unconditional multinomial logistic regression model examining odds of a state prison sentence [0.05,0.14], or intermediate sanction [0.48,1.09], compared to a conditional jail sentence respectively.
When breaking down the descriptive statistics between counties surrounding the Twin cities and not, we find identical patterns. Counties outside of the Twin Cities area use conditional jail (64% v. 66%) and state prison (24% rural v. 27% urban) sentences marginally less than counties surrounding the Twin Cities. Furthermore, intermediate sanctions are more relevant in non-Twin Cities counties (13%) compared to their Twin Cities counterparts (8%). In terms of counties caseload characteristics, counties outside the Twin Cities process more White defendants (71% compared to 45%), less Black defendants (11% compared to 43%), and more drug cases (30% v. 22%) compared to Twin Cities counties.
The reader should note that these findings align with the descriptive analysis above showing that rural counties rely less heavily on conditional jail sentences than urban areas (see Table 1).
The primary two differences when you take intermediate sanctions out of the reference category are: (1) the effect of multiple offenses fell to insignificance and (2) the effect of Sentencing Year 2010 became positive and significant.
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Ruhland, E.L., Holmes, B. An examination of sentencing outcomes in rural and urban locations. Am J Crim Just 48, 701–722 (2023). https://doi.org/10.1007/s12103-022-09678-5
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DOI: https://doi.org/10.1007/s12103-022-09678-5