NM Rural Prison Hosting

The construction of prisons and detention centers in rural areas is frequently based on the untested assumption that the facilities will bring jobs. Thus, prisons are often promoted as rural development tools that will create jobs and stimulate rural communities. Numerous regional and national level studies (listed below) demonstrate that rural prison hosting does not produce measurable positive impacts in terms of employment and may actually stagnate economic growth in the prison hosting community.

The 1980’s marked the beginning of the private prison industry, and with it dedicated efforts on the part of the industry to expand incarceration. Most of those new prisons and detention centers were built in rural areas under the belief that the facilities would stimulate rural economies.

Private Prisons in New Mexico

In the 1990’s New Mexico saw one of the nation’s biggest surges in new private prisons. In New Mexico, as in other states, the new facilities were built in rural areas under the untested pretext that prison hosting would drive economic growth by creating jobs. To the right is a map of prisons and ICE detention facilities illustrating which are private and which are public. Presently, New Mexico tops the nation in its reliance on private prisons and is also home to three large privately run ICE detention centers. According to New Mexico Corrections Department, the state has 15 prisons and detention centers representing 12021 incarceration beds. Of those, 7 are private facilities representing 9769 incarceration beds.

Just under 2/3 of all prison beds in New Mexico are managed by private contractors. Within New Mexico the largest private contractors are CoreCivic, MTC, and GeoGroup. These are the United State’s three largest private prison contractors.

Ten of New Mexico’s 33 counties host prisons or ICE detention centers (see table at bottom of this page). Eight of those 10 counties are classified by Office of Management and Budget (OMB) as nonmetro, rural counties. Slightly more than 2/3 of New Mexico’s incarceration beds are located in rural counties. What follows below is a discussion of unemployment rates in the five largest rural and one metro prison or ICE detention hosting counties.

NameCountyTypeManagerCapacity
Central New Mexico Correctional FacilityValencia PrisonState: NMDC1287
Cibola County Correctional CenterCibolaICEPrivate: CoreCivic1129
Guadalupe County Correctional FacilityGuadalupe PrisonPrivate: GeoGroup610
Lea County Correctional FacilityLeaPrisonPrivate: GeoGroup1266
Northeast New Mexico Detention FacilityUnionPrisonState: NMDC625
Northwest New Mexico Correctional CenterCibolaPrisonPrivate: CoreCivic823
Otero County Prison FacilityOteroPrisonPrivate: MTC1420
Otero County Processing CenterOteroICEPrivate: MTC1089
Penitentiary of New MexicoSanta FePrisonState: NMDC906
Roswell Correctional CenterChaves PrisonState: NMDC340
Southern New Mexico Correctional FacilityDona AnaPrisonState: NMDC752
Springer Correctional CenterColfax PrisonState: NMDC424
Torrance County Detention FacilityTorranceICEPrivate: CoreCivic910
Western New Mexico Correctional FacilityCibolaPrisonState: NMDC440

Methods

To better understand the impacts of prison hosting on jobs, unemployment rates in New Mexico’s rural prison hosting counties are compared to all adjacent non-prison-hosting rural counties. Unemployment data were obtained from the U.S. Bureau of Labor Statistics and cover a period from 1991-2019. Statistical comparisons of significant differences in unemployment rates between prison hosting and non-prison hosting counties are based on the independent paired sample t-test, except where assumptions of normal distribution and equal variance are not met. The Shapiro-Wilk normality test is applied to evaluate if the samples are normally distributed. If they are not, then the Mann-Whitney rank test of significance is applied in lieu of the t-test. The Levene test of equal variance is applied and if the samples are normally distributed but have unequal variances a Welch t-test is applied.

All statistical comparisons were performed in Pyton 3.8.3 using the SciPy library. Graphs were created with the Plotly library. Code and computations are documented in a Jupyter Notebook available for review upon request.

Otero County

Otero County has the largest number of private prison beds of any New Mexico county. Otero County hosts two facilities, a federal prison and an ICE detention center. These facilities have a combined capacity of 2509 incarceration beds all of which are privately managed by Management and Training Corporation. Otero County is located in the state that leads the nation in its reliance on private prisons, the county has the largest number of prison beds in the state, and all of those incarceration beds are privately managed. Therefore, if private prison hosting has a positive economic impact on rural communities, it should be evident in Otero County.

The line graph below shows the unemployment rate for Otero County along with adjacent counties classified as nonmetro by OMB: Eddy, Lincoln, and Sierra counties. The black vertical annotation lines on the line graph represent major private prison hosting events: the establishment of the federal prison in 2003 and the ICE detention center in 2008.

Otero compared to Eddy

For the period between 1991-2019, a t-test indicates that the rural prison hosting county of Otero (M=6.15, SD=1.3) did not experience significantly lower unemployment than the non prison hosting county of Eddy (M=5.67, SD=1.7); t(56)=1.22, p=0.22. From 1991 to the establishment of OCPF in 2002, a t-test found that Otero (M=6.86, SD=1.35) and Eddy (M=7.1, SD=1.26) counties had no significant difference in unemployment rates; t(24)=-0.45, p=0.65. From the period after the establishment of OCPF in 2003 to 2019, a t-test found that Otero County (M=5.66, SD=1.01) exhibited significantly higher unemployment than Eddy County (M=4.66, SD=1.16); t(30)=2.66, p=0.01. From the period after the establishment of OCPC in 2008 to 2019, a t-test found that Otero County (M=6.01, SD=0.87) exhibited significantly higher unemployment than Eddy County (M=4.73, SD=0.87); t(20)=3.03, p=0.01.

Otero compared to Lincoln

For the period between 1991-2019, a t-test shows that Otero County did experience nearly significantly higher unemployment than Lincoln County (M=5.49, SD=1.46); t(56)=1.85, p=0.07. From 1991-2002, before the establishment of OCPF, a t-test found no significant differences in unemployment rates between Otero and Lincoln counties; t(24)=1.55, p=0.14. After the founding of OCPF in 2003, a t-test found no significant difference in unemployment rates between Otero and Lincoln counties; t(30)=1.17, p=0.25. After the founding of OCPC in 2008, a t-test found that between Otero (M=6.01, SD=0.87) and Lincoln (M=5.71, SD=0.87) counties there was still no significant difference in unemployment; t(20)= 0.74, p=0.47.

Otero compared to Sierra

A Shapiro-Wilk test shows that from 1991-2019 unemployment rates in Sierra county are not normally distributed rendering a t-test inappropriate; W(28)= 0.90, p= 0.01. For this time period, a Mann-Whitney test shows that between Otero (Mdn=6.1) and Sierra (Mdn=5.5) counties there was no significant difference in unemployment; U= 66, p=0.2

Between 1991 and 2003, unemployment rates in Otero and Sierra appear normally distributed while a Levene test found they had unequal variance; F(28, 28)= 4.15, p= 0.05. For this time period, a Welch t-test found Otero County (M=6.86, SD=1.35) had significantly higher unemployment rates than Sierra County (M=4.65, SD=0.82); t(24)=4.83, p<0.001. From the period after the establishment of OCPF in 2003 to 2019, a Levene test found that Otero and Sierra counties had unequal variance; F(15, 15)= 11.73, p= 0.00. A Welch t-test found that Otero County (M=5.66, SD=1.01) had a significantly lower unemployment rate than Sierra County (M=7.09, SD=2.16); t(30)=-2.47, p=0.02. For the period after the founding of OCPC in 2008 to 2019, a Levene test again found unequal variance in unemployment rates between Otero and Sierra counties; F(10, 10)= 4.38, p= 0.05. For this time period, a Welch t-test found that Otero County (M= 6.01, SD= 0.87) had significantly lower unemployment than Sierra County (M=8.02, SD=0.87); t(20)= -3.42, p<0.001.

Counties1991-20191991-2002 before OCPF2003-2019 after OCPF2008-2019 after OCPC
Otero-EddyNo Sig DifNo Sig DifOtero Sig HigherOtero Sig Higher
Otero-LincolnNo Sig DifNo Sig DifNo Sig DifNo Sig Dif
Otero-SierraNo Sig DifOtero Sig HigherOtero Sig LowerOtero Sig Lower

The post-OCPF and post-OCPC comparisons between Otero and Sierra counties might superficially be taken as an indication that these facilities lowered relative unemployment rates in Otero County, but closer inspection indicates that is not the case. The line graph comparing unemployment rates over time indicates the differences in unemployment rates between the two counties only started to diverge significantly after 2012 which is four years after the establishment of OCPC. The significant differences in unemployment rates between the two counties are largely due to a very steep rise in unemployment that occurred in Sierra County between 2009 and 2010.

From 1991 until 2012, a Welch t-test shows that Otero County (M=6.27, SD=1.46) still had significantly higher unemployment rate than Sierra County (M=5.2, SD=1.65); t(42)=2.21, p=0.03. From 2003 when OCPF was established to 2008 when OCPC was established, unemployment in Otero County (M=4.75, SD=0.81) was significantly higher than Sierra County (M=3.9, SD=0.51); t(10)=2.17, p=0.05. It is only from from 2012-2019, four years after the establishment of OCPC, that the unemployment rate in Otero County (M=5.86, SD=0.63) was significantly lower than Sierra County (M=8.4, SD=1.24); t(12)=-5.16, p<0.001. Given the late date of this change in unemployment rates it seems unlikely that the significant differences in unemployment that begin after 2012 are explained by rural prison hosting in Otero County in 2008. Moreover, the 2011-2012 increase in unemployment rates in Sierra County are gradually dropping and recently approaching levels seen in Otero County. This recovery is taking place without reliance on prison hosting.

Counties1991-20122003-2008 after OCPF before OCPC2012-2019
Otero-SierraOtero Sig HigherOtero Sig HigherOtero Sig Lower

In 2000, before the founding of the two facilities, Otero county had lower unemployment that Eddy County. By the founding of the prison in 2003 Otero county had a higher unemployment rate than Eddy County. After the establishment of the prison, unemployment in both counties declined as part of an overall state trend. However, unemployment in Eddy county declined faster and further than it did in Otero County. By 2005 unemployment in Otero County was higher than either Eddy or Lincoln counties. This trend continued through the establishment of the Otero County Processing Center (OCPC) in 2008. By 2014, unemployment in Otero County (6.3%) was ⅓ higher than Eddy County (4.4%). Unemployment rates in Otero County remain higher than either Eddy or Lincoln counties.

The establishment of the two private incarceration facilities in Otero County were not followed by marked improvements in employment rates compared to adjacent nonhosting rural counties. Over time, despite having the state’s largest investment in rural prison hosting, all of it managed by a private for profit company, Otero County has not shown lower unemployment than adjacent counties that are not hosting prisons. The large presence of prison facilities in Otero county has not produced significantly positive results on unemployment when compared to adjacent rural counties that do not host prisons. In fact compared to Otero County, Eddy county achieved greater improvements in unemployment rates without hosting any prisons. Thus in Otero County, the presence of the prisons seems to have negligible positive impact on overall county wide employment rates.

Cibola County

Cibola County has the second largest number of private prison beds of any New Mexico county. Cibola county hosts two prisons and one ICE detention facility comprising 2392 incarceration beds. One of the prisons was temporarily closed and reopened as an ICE detention facility. Together the two private facilities, both managed by CoreCivic, make up 1952 incarceration beds, which is 82% of the county’s incarceration bed space.

The line graph below shows the unemployment rate of Cibola County along with adjacent nonmetro counties, as classified by OMB. The black vertical lines represent major private prison hosting events: first the county prison’s establishment in 1993, the acquisition and expansion of the prison by the private company Corrections Corporation of America (later rebranded as CoreCivic), as well as the closure of the prison and its reopening as an ICE detention facility.

For the period between 1999-2019, after the expansion of CCCC, a t-test found that Cibola County (M=8.2, SD=2.65) did not experience significantly lower unemployment than Catron County (M=8.89, SD=2.7);t(56)=-0.98, p=0.00). Between 1999-2019, a Shapiro-Wilk test found that unemployment rates in McKinley county are not normally distributed; W(8)= 0.97, p= 0.89. For this same time period, a Mann Whitney rank test found no significant difference in the unemployment rates between Cibola County (Mdn=6.8) and McKinley County (Mdn=7.0); U=162, p=0.07. During the period between 1999-2019, a t-test found that Cibola County experienced significantly higher unemployment than Socorro County (M=6.28, SD=1.61); t(56)=3.33, p=0.002.

When the prison was first founded in 1993, Cibola County experienced higher unemployment than the two adjacent rural non-prison hosting counties of Catron, McKinley, and Socorro. After the opening of the prison, unemployment in Cibola went down as part of an overall state trend. By 1996, unemployment in Cibola county was higher than the year prior to the prison’s opening. In 1992, the year prior to the prison’s acquisition by CCA, unemployment was declining but after the prison was acquired by CCA the rate of decreasing unemployment slowed. In 2017, after the facility was reopened under an ICE detention contract unemployment again declined as part of an overall state trend. However, notably the rate of decline in unemployment in Cibola county was slower than either of the three adjacent rural non-prison counties or the state average. By 1999, despite a heavy investment in prison hosting Cobila had a higher unemployment rate than either Catron or Socorro counties.

Counties1999-2019
Cibola-CatronNo Sig Dif
Cibola-McKinleyNo Sig Dif
Cibola-SocorroCibola Sig Higher

For Cibola County, hosting the state’s second largest number of prison beds did not produce significant positive impacts on unemployment and when compared to Socorro County appear to have resulted in significant negative outcomes.

Valencia County

Valencia County has the third largest number of prison beds in the state. Valencia County hosts the 1287 bed Central New Mexico Correctional Facility (CNMCF) which is managed by NM Corrections Department. CNMCF was established in 1939 and expanded over time. It is the largest prison in the state.

Valencia is adjacent to one rural non-prison hosting county, Socorro. From 1991 to the present, comparing unemployment rates between the prison hosting county of Valencia (M=6.05, SD=1.61) and Socorro (M=6.28, SD=1.61) shows no significant differences in unemployment rates; t(56)=-0.55, p=0.58.

Lea County

Lea County has the fourth largest number of incarceration beds and the third largest number of private prison beds of any county in New Mexico. Lea County hosts the 1266 bed Lea County Correctional Facility (LCCF) managed by GeoGroup. LCCF was established in 1998. Lea county is adjacent to two rural non-prison hosting counties: Eddy and Roosevelt. The line graph below shows unemployment rates over time for these three counties. The black vertical annotation line shows the establishment of LCCF in 1998.

From 1991-2019, t-test comparing Lea (M=5.42, SD=1.66) and Eddy (M=5.67, SD=1.7) counties shows no significant difference in unemployment rates; t(56)=-0.58, p=0.56. During the period before LCCF was established (1991-1997), t-test shows that unemployment in Lea County (M=5.76, SD=0.88) was significantly lower than Eddy County (M=7.7, SD=0.99); t(14)=-3.87, p=0.002. During the period after LCCF was established (1998-2019), t-test found unemployment in Lea County (M=5.31, SD=1.85) was not significantly different than Eddy County (M=5.03, SD=1.32);t(40)=0.58, p=0.56. In fact in 1997 the year prior to hosting LCCF, unemployment in Eddy County (4.8%) was higher than Lea County (6.3%) while in 1999 the year following the hosting of LCCF in Lea County (9.2%) unemployment rose faster and was higher than unemployment in Eddy County (8%). Thus since the hosting of LCCF in Lea County, Eddy County without hosting any private prison beds, achieved comparable unemployment rates to Lea County.

From 1991-2019, t-test shows that Lea County (M=5.42, SD=1.66) has a significantly higher unemployment rate than Roosevelt County (M=4.63, SD=0.97); t(56)=2.19, p=0.03. Prior to the establishment of LCCF (1991-1997), there was no significant difference in the unemployment rates of Lea (M=5.76, SD=0.88) and Roosevelt (M=5.2, SD=0.54) counties; t(14)=1.42, p=0.18. After the establishment of LCCF (1998-2019) the unemployment rate of Lea County (M=5.31, SD=1.85) was nearly significantly higher than Roosevelt County (M=4.45, SD=1.02); t(40)=1.9, p=0.06. The lack of significant difference is likely due to the highly fluctuating rates of unemployment during this period in Lea County. It is noteworthy that for Lea County the year with the highest unemployment rate (9.92%) was in 1999 whereas two years prior in 1997 the unemployment rate in Lea County (4.8%) was nearly as low as Roosevelt County (4.3%). Thus, in the period immediately following the establishment of LCCF unemployment in Lea County more than doubled while in Roosevelt County is dropped by 0.9%.

Counties1991-20191991-1997 before LCCF1998-2019
Lea-EddyNo Sig DifLea Sig LowerNo Sig Dif
Lea-RooseveltLea Sig HigherNo Sig DifLea nearly Sig Higher

Torrance County

OMB does not classify Torrance County as rural, but it is the fourth largest private prison hosting county in New Mexico. Torrance County hosts 910 bed Torrance County Detention Facility which is managed by CoreCivic. Corrections Corporation of America (CCA), now CoreCivic, owned TCDF since 1990. From 1990-1997, the facility contained 286 incarceration beds. In 1997, CoreCivic expanded the facility to 910 incarceration beds more than tripling the capacity. In 2017, the facility was closed briefly and reopened as an ICE detention facility.

Given the large number of private prison beds hosted in Torrance County comparisons in unemployment rates will be made with the adjacent rural counties that do not host prisons. Torrance County is adjacent to three rural non-prison hosting counties: Lincoln, San Miguel, and Socorro.

From 1991-2019, a Levene test found that unemployment rates in Torrance and Lincoln counties had unequal variance; F(28, 28)= 6.96, p= 0.01. For this time period, a Welch t-test found that Torrance County (M=7.38, SD=2.24) had significantly higher unemployment rates than Lincoln County(M=5.49, SD=1.46); t(56)= 3.82, p< 0.001.

From 1991-1996, prior to the expansion of TCDF, a t-test found that between Torrance (M=8.0, SD=1.21) and Lincoln (M=7.18, SD=1.27) counties there was no significant difference in unemployment; t(12)=1.14, p=0.28. From 1997-2019, the period after TCDF’s significant expansion, a Levene test found that Torrance and Lincoln counties had unequal variance; F(21, 21)= 12.41, p< 0.001. For this time period, after the expansion of TCDF, a Welch t-test found that Torrance County (M=7.22, SD=2.43) had significantly higher unemployment rates than Lincoln County (M=5.04, SD=2.43); t(42)= 3.87, p=0.00.

From 1991 to 2019 , a t-test comparing unemployment rates between Torrance (M=7.38, SD=2.24) and San Miguel (M=7.66, SD=2.02) counties found no significant difference; t(56)= -0.49, p=0.63. From 1991-1996, prior to the expansion of TCDF, a t-test found that Torrance County (M=8.0, SD=1.21) had significantly lower unemployment than San Miguel (M=9.97, SD=1.79); t(12)=-2.23, p=0.05. Notably, in 1991 San Miguel County’s unemployment rate was 11.4% while in Torrance County it was 8%. From 1997-2019, the period after TCDF’s significant expansion, a t-test found no significant difference in unemployment rates between Torrance (M=7.22, SD=2.43) and San Miguel (M=7.05, SD=1.62) counties; t(42)=0.28, p=0.78. By 2007 unemployment in Torrance rose higher than San Miguel and has remained higher since.

From 1991-2019, a t-test found that unemployment rates in Torrance County (M=7.38, SD=2.24) were significantly higher than Socorro County (M=6.28, SD=1.61); t(56)=2.15 , p=0.036. From 1991-1996, prior to the expansion of TCDF, a t-test comparing Torrance County (M=8.0, SD=1.21) to Socorro (M=8.25, SD=0.54) found no significant difference in the rate of unemployment; t(12)= -0.46, p= 0.65. From 1997-2019, the period after TCDF’s significant expansion, a Shapiro-Wilk normality test test found that unemployment rates in Torrance do not appear normally distributed; W(21)= 0.89, p= 0.02. A Mann-Whitney rank test found that unemployment rates in Torrance County (Mdn=6.7) were significantly higher than Socorro County (Mdn=5.3); U= 184.50, p= 0.04.

Counties1991-20191991-19961997-20192007-2019
Torrance-LincolnTorrance Sig HigherNo Sig DifTorrance Sig Higher
Torrance-San MiguelNo Sig DifTorrance Sig LowerNo Sig DifTorrance Higher
Torrance-SocorroTorrance Sig HigherNo Sig DifTorrance Sig Higher

Guadalupe County

Guadalupe county hosts the 610 bed Guadalupe County Correctional Facility (GCCF) which is managed by GeoGroup. GCCF began operation in 1999. Guadalupe county is adjacent to four rural non-prison hosting counties: De Baca, Lincoln, Quay, and San Miguel.

From 1991-2019, a Shapiro-Wilk normality test indicates that unemployment rates in Guadalupe and De Baca counties do not appear normally distributed. For this period, a Mann-Whitney rank test indicates that Guadalupe County (Mdn=7.9) had significantly higher unemployment rates than De Baca County (Mdn=4.7); U=54.4, p<0.001. For the period from 1999-2019, after the establishment of GCCF, a Mann-Whitney rank test indicates that Guadalupe County (Mdn=7.4) had significantly higher unemployment rates than De Baca County (Mdn=4.7); U=30.30, p<0.001.

From 1991-2019, a Mann-Whitney rank test indicates that Guadalupe County (Mdn=7.9) had significantly higher unemployment rates than Lincoln County (Mdn=5.7); U= 110.50, p= 0.001. For the period from 1999-2019, after the establishment of GCCF, a Mann-Whitney rank test indicates that Guadalupe County (Mdn=7.4) had significantly higher unemployment rates than Lincoln County (Mdn=4.5); U= 46.00, p< 0.001

From 1991-2019, a Mann-Whitney rank test indicates that Guadalupe County (Mdn=7.9) had significantly higher unemployment rates than Quay County (Mdn=6); U= 145.00, p< 0.001. For the period from 1999-2019, after the establishment of GCCF, a Mann-Whitney rank test indicates that Guadalupe County (Mdn=7.4) had significantly higher unemployment rates than Quay County (Mdn=5.9); U= 114.00, p< 0.001

From 1991-2019, a Mann-Whitney rank test found no significant difference in unemployment rates between Guadalupe (Mdn=7.9) and San Miguel (Mdn=7.6) counties; U= 332.50, p= 0.09. From 1999-2019, after the establishment of GCCF, a t-test found no significant difference in unemployment rates between Guadalupe (M=7.41, SD=1.53) and San Miguel (M=6.84, SD=1.53) counties; t(38)= 1.23, p=0.23. Between 1999-2010, t-test shows that Guadalupe County (M=7.36, SD=1.25) had significantly higher unemployment rates than San Miguel County(M=6.23, SD=1.39): t(22)=2.10, p=0.05.

Counties1991-20191999-20191999-2010
Guadalupe-De BacaGuadalupe Sig HigherGuadalupe Sig Higher
Guadalupe-LincolnGuadalupe Sig HigherGuadalupe Sig Higher
Guadalupe-QuayGuadalupe Sig HigherGuadalupe Sig Higher
Guadalupe-San MiguelNo Sig DifNo Sig DifGuadalupe Sig Higher

Relevant literature on the economic impacts of rural prison hosting

Beale, Calvin L. “Prisons, Population, and Jobs in Nonmetro America.” Rural Development Perspectives 8, no. 3 (1998): 16–19. https://naldc.nal.usda.gov/download/IND20388150/PDF.
Beale, Calvin L. “Rural Prisons: An Update.” Rural Development Perspectives 11, no. 2 (2001): 25–27. https://wayback.archive-it.org/5923/20120225132818/http://ers.usda.gov/Publications/RDP/RDP296/RDP296d.pdf.
Huling, Tracy. “Building a Prison Economy in Rural America.” In Invisible Punishment: The Collateral Consequences of Mass Imprisonment, edited by Marc Mauer and Meda Chesney-Lind, 221–39. New York: New Press, 2003.
King, Ryan S, Marc Mauer, and Tracy Huling. “Big Prisons, Small Towns: Prison Economics in Rural America.” Washington D.C.: The Sentencing Project (TSP), 2003. https://www.sentencingproject.org/publications/big-prisons-small-towns-prison-economics-in-rural-america/.
Besser, Terry L., and Margaret M. Hanson. “Development of Last Resort: The Impact of New State Prisons on Small Town Economies in the United States.” Journal of the Community Development Society 35, no. 2 (2004): 1–16.
Tootle, Deborah M. “The Role of Prisons In Rural Development: Do They Contribute to Local Economies?” Department of Agricultural Economics Working Paper. Baton Rouge, LA: Louisiana State University, 2004. http://realcostofprisons.org/materials/Prisons_as_Rural_Development.pdf.
Lawrence, Sarah, and Jeremy Travis. “The New Landscape of Imprisonment: Mapping America’s Prison Expansion.” Washington D. C.: Urban Institute Justice Policy Center, 2004. https://www.urban.org/sites/default/files/publication/57971/410994-The-New-Landscape-of-Imprisonment.PDF.
Hooks, Gregory, Clayton Mosher, Thomas Rotolo, and Linda Lobao. “The Prison Industry: Carceral Expansion and Employment in US Counties, 1969-1994.” Social Science Quarterly 85, no. 1 (March 2004): 37–57. https://doi.org/10.1111/j.0038-4941.2004.08501004.x.
Blankenship, Susan E., and Ernest J. Yanarella. “Prison Recruitment as a Policy Tool of Local Economic Development: A Critical Evaluation.” Contemporary Justice Review 7, no. 2 (June 2004): 183–98. https://doi.org/10.1080/1028258042000221184.
Yanarella, Ernest J., and Susan Blankenship. “Big House on the Rural Landscape: Prison Recruitment as a Policy Tool of Local Economic Development.” Journal of Appalachian Studies 12, no. 2 (Fall 2006): 110–39. http://libezp.nmsu.edu:2048/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=33322541&site=ehost-live&scope=site.
Gilmore, Ruth Wilson. Golden Gulag: Prisons, Surplus, Crisis, and Opposition in Globalizing California. American Crossroads 21. Berkeley: University of California Press, 2007.
Holley, William T. “Assessing the Impact of Prison Siting On Rural Economic Development.” Doctoral Dissertation, Gorge Mason University, 2008. http://hdl.handle.net/1920/3351.
Barry, Tom. “A Death in Texas: Profits, Poverty, and Immigration Converge.” News. Boston Review, November 1, 2009. https://bostonreview.net/us/death-texas.
Hooks, Gregory, Clayton Mosher, Shaun Genter, Thomas Rotolo, and Linda Lobao. “Revisiting the Impact of Prison Building on Job Growth: Education, Incarceration, and County-Level Employment, 1976-2004.” Social Science Quarterly 91, no. 1 (2010): 228–44.
PLN. “New Mexico Spends $20 Million in Federal Stimulus Money to Fund Prison Jobs.” Prison Legal News (PLN) 22, no. 9 (September 2011): 24–24. https://www.prisonlegalnews.org/news/2011/sep/15/new-mexico-spends-20-million-in-federal-stimulus-money-to-fund-prison-jobs/.
Bonds, Anne. “Building Prisons, Building Poverty: Prison Sitings, Dispossession, and Mass Incarceration.” In Beyond Walls and Cages: Prisons, Borders, and Global Crisis, edited by Jenna M. Loyd, Matt Mitchelson, and Andrew Burridge, 129–42. Geographies of Justice and Social Transformation 14. Athens: University of Georgia Press, 2012.
Loyd, Jenna M., Matt Mitchelson, and Andrew Burridge, eds. Beyond Walls and Cages: Prisons, Borders, and Global Crisis. Geographies of Justice and Social Transformation 14. Athens: University of Georgia Press, 2012.
Perdue, Robert Todd, and Kenneth Sanchagrin. “Imprisoning Appalachia: The Socio-Economic Impacts of Prison Development.” Journal of Appalachian Studies 22, no. 2 (Fall 2016): 210–23. https://doi.org/10.5406/jappastud.22.2.0210.
Meagher, Tom, and Christie Thompson. “So You Think a New Prison Will Save Your Town?” The Marshall Project, June 6, 2016. https://www.themarshallproject.org/2016/06/14/so-you-think-a-new-prison-will-save-your-town.
Ruth, Julie. “GOP Backed-Privatization Brings Rural America To Its Knees.” Rantt, October 5, 2017. https://rantt.com/gop-backed-privatization-brings-rural-america-to-its-knees/.
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