Trends in Sentencing of Federal Drug Offenders: Findings From U.S. District Courts 2002–2017

2020 ◽  
Vol 51 (1) ◽  
pp. 84-108
Author(s):  
Alexander Testa ◽  
Jacqueline G. Lee
Keyword(s):  
Ordinary Least Squares ◽  
District Courts ◽  
Least Squares Regression ◽  
Prison Sentence ◽  
Criminal Sentencing ◽  
Drug Offenders ◽  
Race Ethnicity ◽  
Substantial Heterogeneity ◽  
Over Time ◽  
Sentencing Outcomes

This study uses 16 years (2002–2017) of federal criminal drug sentences from the U.S. Sentencing Commission (USSC) to examine trends in two criminal sentencing outcomes: whether a defendant received a prison sentence and the length of a prison sentence. Logistic and ordinary least squares regression analyses were used to assess criminal sentencing outcomes. Moderation analyses are conducted to assess variation in sentencing for specific drug offenses over time. Results demonstrate that sentencing for federal drug crimes has become less severe over time. However, there is substantial heterogeneity in sentencing across different drug types, with pharmaceutical opioid cases receiving the least leniency over time regarding the incarceration decision and methamphetamine cases experiencing the lowest reduction in the length of prison sentences from 2002 to 2017. Finally, our analysis stratified by race/ethnicity suggested that there is heterogeneity in sentencing outcomes for federal drug offenders, conditional on racial and ethnic background.

scholarly journals An intersectional approach to race/ethnicity, sex, and age disparity in federal sentencing outcomes: An examination of policy across time periods

2016 ◽  
Vol 17 (1) ◽  
pp. 97-116 ◽  
Author(s):  
Jeffrey S Nowacki
Keyword(s):  
United States ◽  
Ordinary Least Squares ◽  
Sentence Length ◽  
Least Squares Regression ◽  
Federal Sentencing ◽  
Race Ethnicity ◽  
Time Periods ◽  
Changing Role ◽  
Sentencing Outcomes

Approaches to intersectionality stress the importance of recognizing multiple, intersecting inequalities. As such, recent sentencing research has examined the changing role of extra-legal characteristics on United States federal sentencing outcomes in the aftermath of recent policy changes (e.g. United States v. Booker), but scholarship has less often examined these characteristics at the intersections of race/ethnicity, gender, and, especially age. This article uses an intersectional approach to examine the influence of these characteristics net of legally relevant characteristics. Using ordinary least squares regression procedures, the author examines the role of the joint effects of extra-legal variables on sentence length decisions across four distinct time periods. Net of control variables, results indicate that young black men are the group most likely to receive the longest sentences, but interesting differences between other groups also emerge.

scholarly journals Bikes or Bust? Analyzing the Impact of Bicycle Infrastructure on Business Performance in San Francisco

2019 ◽  
Vol 2673 (12) ◽  
pp. 277-289
Author(s):  
Raleigh McCoy ◽  
Joseph A. Poirier ◽  
Karen Chapple
Keyword(s):  
San Francisco ◽  
Business Performance ◽  
The United States ◽  
Ordinary Least Squares ◽  
Grocery Stores ◽  
Least Squares Regression ◽  
Mode Shift ◽  
Bicycle Infrastructure ◽  
The Impact ◽  
Over Time

Transportation agencies at the local, state, and federal levels in the United States (U.S.) have shown a growing interest in expanding bicycle infrastructure, given its link to mode shift and safety goals. These projects, however, are far from universally accepted. Business owners have been particularly vocal opponents, claiming that bicycle infrastructure will diminish sales or fundamentally change the character of their neighborhoods. Using the case of San Francisco, this research explores the relationship between bicycle infrastructure and business performance in two ways: change in sales over time, and a comparison of sales for new and existing businesses. An ordinary least squares regression is used to model the change in sales over time, isolating the effect of location on bicycle infrastructure while controlling for characteristics of the business, corridor, and surrounding neighborhood. Through a series of t-tests, average sales for businesses that pre-date bicycle infrastructure and for those that opened after the installation of such projects are compared. Ultimately, the research suggests that location on bicycle infrastructure and changes in on-street parking supply generally did not have a significant effect on the change in sales, with a few exceptions. Businesses that sell goods for the home or auto-related goods and services saw a significant decline in sales when located on corridors with bike lanes. New and existing businesses generally had similar sales, though not across the board. New restaurants and grocery stores had significantly higher sales than their existing counterparts, suggesting bicycle infrastructure may attract more upmarket businesses in those industries.

Sentencing Outcomes in U.S. District Courts

2016 ◽  
Vol 63 (2) ◽  
pp. 137-165 ◽  
Author(s):  
Travis W. Franklin
Keyword(s):  
Educational Attainment ◽  
General Pattern ◽  
Sentence Length ◽  
District Courts ◽  
Current Analysis ◽  
Focal Concerns ◽  
Race Ethnicity ◽  
Extralegal Factors ◽  
Focal Concerns Theory ◽  
Sentencing Outcomes

Numerous studies have examined the influence of offender characteristics on sentencing outcomes, yet little attention has been afforded to offenders’ educational attainment. The focal concerns theory provides reason to suspect that greater educational attainment may insulate offenders from the effects of criminal stereotypes linked to extralegal factors, including race/ethnicity, age, and sex. The current analysis employs a sample of 115,674 federal offenders to test this assumption on the in/out and sentence length decisions. Results of the in/out models demonstrate a general pattern where the effects of several extralegal factors (i.e., race, ethnicity, age, sex, and detention) are reduced, and in some cases fully moderated, by offenders’ educational attainment. This pattern, however, is not apparent during the sentence length decision.

Developmental Heterogeneity in Social Support Among Juvenile Offenders: Relevance of Social Support Withdrawal for the Dulling of Maturational Decline in Offending

2019 ◽  
Vol 66 (5) ◽  
pp. 712-733
Author(s):  
Thomas W. Wojciechowski
Keyword(s):  
Social Support ◽  
Juvenile Offenders ◽  
Least Squares ◽  
Ordinary Least Squares ◽  
Least Squares Regression ◽  
Group Assignment ◽  
Research Questions ◽  
Trajectory Group ◽  
Pathways To Desistance ◽  
Over Time

Social support is a highly relevant predictor of offending. Despite this, little research has examined how this construct develops over time and how withdrawal of social support may result in “late bloomer” offending. This study used the Pathways to Desistance to data to test hypotheses related to these research questions. Group-based trajectory modeling was used to identify trajectories of social support, and ordinary least squares regression was used to determine the relevance of trajectory group assignment for predicting differences in offending between adolescence and adulthood. Results indicated that withdrawal of social support resulted in a dulling of the maturational decline in offending frequency typically observed following adolescence. Implications are discussed.

Religion in America—1972–2006: Religious Affiliation, Attendance, and Strength of Faith

2010 ◽  
Vol 106 (3) ◽  
pp. 875-890 ◽  
Author(s):  
Kevin J. Flannelly ◽  
Kathleen Galek ◽  
Jackson Kytle ◽  
Nava R. Silton
Keyword(s):  
Religious Affiliation ◽  
General Social Survey ◽  
Ordinary Least Squares ◽  
African American Female ◽  
Least Squares Regression ◽  
Religiously Affiliated ◽  
Religious Services ◽  
Strength Of Faith ◽  
Changes Over Time ◽  
Over Time

The present study used data from the General Social Survey, collected between 1972 and 2006 ( N = 45,463) to analyze changes over time in three aspects of religion among American adults: religious affiliation, frequency of attending religious services, and strength of faith. The last two measures were analyzed only for survey participants who had a religious affiliation. Ordinary least-squares regression confirmed a significant decrease in religious affiliation over time, after controlling for socio-demographic variables that are known to be associated with religion. A significant decrease in attending religious services was found among those survey participants who were religiously affiliated. As expected, participants who were African American, female, older, and from the South were more religious according to all three measures. No effect of birth-cohort was found for any religious measure. The results are discussed in the context of Stark and Bainbridge's 1996 theory of religion.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

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