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Article Review
Bradner, K., & Schiraldi, V. N. (2020). Racial inequities in New York parole supervision. Columbia University, Justice Lab. 1-24. DOI: https://doi.org/10.7916/d8-f4sf-0s28.
Summary
The article “Racial Inequities in New York Parole Supervision” by Bradner & Schiraldi (2020) explores the racial and ethnic inequities in practices of parole supervision in New York. The text shows that the scope and conditions surrounding New York’s parole supervision practices have substantial impacts on individuals serving sentences. Specifically, the conditions relating to parole supervision in New York are reported to hinder the freedom of offenders, encourage incarceration, and can deter the community reintegration process necessary for successful reentry after leaving prison. Therefore, the article strives to examine the racial and ethnic inequities on parole violations and revocation in New York, and also provide further context through the review of existing studies on inequalities that exist in supervision practices countrywide.
Focusing on the three points mentioned above, the report outlines the findings by Justice Lab analysis that demonstrate that New York’s people of color go through disparate burdens at all these points. As such, the report indicates that Black and Latinx people are more prone to parole supervision compared to white people, and supervision disparities are worse in men than women on a national scale. It is also evident that the detainment of black and Latinx people for parole in the New York City jails is at a higher rate unlike the rate of white people, the rates of blacks are higher the those of Latinx people. Supervision disparities for males are reported to be at a higher rate compared to men where the rates of men from the colored background are more likely to experience supervision disparities for prison incarceration in the New York City State prisons. The research finding for the article shows that people of color in New York are exposed to disparate outcomes at a profoundly higher level compared to the reported national averages. From the review of existing research, the article found that being on parole for a longer duration increasingly puts people of color at a disadvantage, and as such, they are more likely to be unfairly charged with violations as well as receive severer punishments.
As such, the report recommends several approaches to aid in reforms on the parole system to prevent or mitigate disparities relating to parole supervision in the New York City State prisons. Notably, policy change is the key recommendation that is believed to trigger positive effects for Black and brown people. The article cited the Less Is More Act which is intended to enact the proposed policy recommendation. More importantly, the article deduced that there is high feasibility on parole reforms in New York that would significantly address the sources of racial and ethnic disparities that are deeply rooted in the City’s parole supervision. As such, legislative actions should be taken to mitigate the challenges associated with discrepancies in parole supervision that directly affects the lives of the violators and the community at large. The report shows that Black and brown people as well as the already underserved communities will continue to suffer from the disparities in parole supervision if the policy changes fail to take place.
Discussion
The article conducts in-depth research on the conditions of parole supervision and the possible impacts on the people of color and the already vulnerable underserved communities in the New York City State prisons. The article utilizes extensive and reliable sources of data to support their findings and make feasible recommendations. From the report findings, the people of color are disproportionately more likely to experience violation charges and receive harsher punishment due to the fact that they remain on parole for longer, unlike the white people (Bradner & Schiraldi, 2020). Furthermore, there is a constant increase in the number of people under parole supervision countrywide in the past years, with a reduction in probation populations and the number of individuals under community corrections supervision. The high number of persons under parole supervision increases the possibilities of disparities within the system, and often, the most disadvantaged groups are the people of color. Therefore, “There are three points at which racial inequities in parole supervision practices can be readily observed in the likelihood of experiencing parole supervision, in the likelihood of being charged with a violation, and in the likelihood of incarceration for a violation.”
The fact that people on parole are expected to adhere to certain rules or conditions such as dissociating with people with criminal records and avoiding substance abuse means that failure to adhere will result in re-incarceration, an offense referred to as technical violation. Re-incarceration can result in severe punishment such as sentencing to an extended time in state prison. Therefore, the article deduced that people of color are more likely to be charged for technical violations as a result of the existing racial and ethnic disparities in the parole supervisions, particularly in New York (Bradner & Schiraldi, 2020). The rules and conditions set for parole supervision are the notable aspects that encourage the persistence of disparities since they obstruct the people under supervision and their families from living normal lives. For instance, anyone who is under supervision cannot engage freely with the community due to conditions such as not being allowed to live with supportive family or friends with criminal records or work overnight in well-paying jobs because they are not allowed to violate curfew hours. All these pose a lot of difficulties in rehabilitating offenders towards re-entering society after a prison sentence.
Furthermore, the existing racial and ethnic discrimination on the people of color along with conditions of parole supervision are contributing aspects that worsen systemic racial inequities. For instance, New York is reported to have lower parole supervision rates countrywide but it has the highest rate of re-incarceration (Bradner & Schiraldi, 2020). The report utilizes reliable statistics from credible sources to show that the people of color constitute the largest population of persons on parole and are being held for new charges. This relates to the fact that a larger population of the Black and brown communities are prone to violence, increasing the risk of being incarcerated and re-incarcerated. Therefore, the presence of disparities in parole supervision will mean that most people who will be charged with technical violations are people of color. Furthermore, the longer one is under parole supervision means they are likely to violate parole rules, and as such, increases the risk of being re-incarcerated. It is, therefore, clear that parole supervision practices have profound impacts on offenders and people within their surroundings, and especially people of color and already-vulnerable underserved communities. As such, the recommendations suggested in the article regarding the need for policy reforms on the parole system in New York will bring positive impacts and even justice to the disadvantaged population.
References
Bradner, K., & Schiraldi, V. N. (2020). Racial inequities in New York parole supervision. Columbia University, Justice Lab. 1-24. DOI: https://doi.org/10.7916/d8-f4sf-0s28.
HOMEWORK 8
Homework 8
Single-Sample T-Test
When submitting this file, be sure the filename includes your full name, course and section. Example: HW8_JohnDoe_510B01
Be sure you have reviewed this module/week’s lesson and presentations along with the practice data analysis before proceeding to the homework exercises. Complete all analyses in SPSS, then copy and paste your output and graphs into your homework document file. Answer any written questions (such as the text-based questions or the APA Participants section) in the appropriate place within the same file.
Part I: Concepts
Questions 1–8; Answer the questions in the spaces provided.
Part I: Questions 1-7
Fill in the highlighted blanks with the best word or words. 2 pts each / 14 total
1) A researcher reports the results of a single-sample t-test as t(19) = 1.80. The degrees of freedom for this t-test are _______, which means there were _______total participants in the researcher’s sample.
2) Based on the previous scenario with a one-tailed test and a p level of 0.05, the critical t value is _______, meaning the researcher should _______ the null hypothesis.
3) As the sample size gets larger, the _______ distribution begin to look more like the _______ distribution.
4) The number of scores that are free to vary when you are estimating a population parameter from a sample is called the _______.
5) You use a t-test when you know the population _______ but not the population _______.
6) If t (12) = 0.79, the 0.79 represents _______.
7) If you have 8 scores, the degrees of freedom for the scores is (numerical value): _______.
Part I: Question 8
1 pt per answer = 9 pts total
8) Calculate the critical degrees of freedom and identify the critical t value for a single-sample t test in each of the following situations. Then, state whether the null hypothesis would be accepted or rejected:
8A) Two-tailed test, N = 12, t = 1.85, p = .10 df= Answer critical t = Answer
Accept or Reject Ho: Answer
8B) Two-tailed test, N = 18, t = 1.85, p = .05 df= Answer critical t = Answer
Accept or Reject Ho: Answer
8C) One-tailed test, N = 27, t = 1.85, p = .01 df= Answer critical t = Answer
Accept or Reject Ho: Answer
Part II: SPSS Analysis
Module/Week 8 Exercise File 1
Open the “Module/Week 8 Exercise File 1” document (found in the course’s Assignment Instructions folder) in order to complete these exercises. Part II: Exercises 1-3 (16 pts)
Use file: Homework8DataFile
The memory scores for 15 fictional patients with dementia are entered in the “Homework8DataFile” SPSS document (found in the Assignment Instructions folder).
Higher memory number indicates better memory performance.
Using these data, run 2 single-sample t-tests to compare the dementia patients’ mean memory score to the following population values:
Population memory scores
Age-matched controls: = 12.2
Patients with traumatic brain injury (TBI): = 8.1
For each test, paste the output and write a Results section in current APA style
As demonstrated in the presentation and in the textbooks.
There will be 2 sets of output and 2 results sections using this data set
1 for each test involving a different population mean.
1) Using the “explore” tab, run descriptive statistics on the dementia patients’ memory scores (make sure to include the mean and confidence interval). 2pts
Answer: SPSS output of descriptive statistics
2A) Population of age matched controls: = 12.2. 2pts
Answer: SPSS output of the t-Test
2B) Calculate the effect size for the one-sample t test as shown in the Green and Salkind textbook, Lesson 22.2 using the formula: d = Mean Difference / SD. Show all work. 2pts
Answer
Work
2C) Write a results section in current APA style describing the outcome.
All homework results sections must follow the example given in the SPSS presentation and in the textbook. Results sections are multiple sentences (a single paragraph) and must include the APA-formatted statistical statement within a sentence. 3pts
Answer
3A) Population of patients with TBI: = 8.1. 2pts
Answer: SPSS output of the t-Test
3B) Calculate the effect size for the one-sample t test as shown in the Green and Salkind textbook, Lesson 22.2 using the formula: d = Mean Difference / SD. Show all work. 2pts
Answer
Work
3C) Write a results section in current APA style describing the outcome. See (2C) for details. 3pts
Answer
Part III: SPSS Data Entry and Analysis
Data provided below.
Attitudes Toward
Technology Scale Scores
21
23
20
18
17
20
24
21
19
17
20
Part III: Question 1A-E
11 pts
Do elderly people have less positive attitudes toward technology than people in general?
A social psychologist assessed the attitudes of 11 elderly people using a scale where a lower score indicates a less positive attitude overall. The mean on this scale for the general population is 23.1. The data for the participants are shown in the table to the left.
Using SPSS, conduct a single-sample t-test to answer the social psychologist’s research question.
1A) Paste appropriate descriptive statistics table here (must include mea annd confidence intervals) 2pts
Answer: SPSS output of descriptive statistics
1B) Paste one sample t-test output here for = 23.1 / 2pts
Answer: SPSS output of the t-Test
1C) Using the directions in Part II, calculate the effect size. 2pts
Answer Work
1D) Paste appropriate SPSS graph to show the distribution of elderly attitudes 2pts
Answer: SPSS graph
1E) Write a results section in current APA style describing the outcome. Refer to earlier directions for details of what is expected. 3pts
Answer:
Part IV: Cumulative
Data provided below for respective questions. Part IV: Question 1 (Non-SPSS) (3 pts)
Age at onset of dementia was determined in the general population to be = 69.5 and = 2.8.
Use this information to answer the following:
1A) Based on the data above, what is the z score for the age of 65? (1pt)
Answer Work:
1B) Based on the data you have and the z table, what percentage of people might start to show signs of dementia at or before age 65? (2 pts)
Answer
Part IV: Question 2-7 (Non-SPSS)
2 pts each / 12 pts total
Fill in the highlighted blanks with the best word or words. 2 pts each / 14 total
2) If you have a known population mean and standard deviation to compare to one sample, you can perform a _______.
3) A probability of 0.35 converts to a percent of _______.
4) If a researcher concludes that their intervention had no effect when in fact it did, they make a _______error.
5) The _______ hypothesis states that there is an average (nonsignificant) difference between populations.
6) The three measures of central tendency are the _______, _______, and _______.
7) If there is one scale independent variable and one scale dependent variable use a _______ or a _______.
Submit Homework 8 by 11:59 p.m. (ET) on Friday of Module/Week 8. Remember to name file appropriately.
Done!
Homework 3 Professor Ozer
Homework 3: Professor Ozer
October 29th
Question 1
Which of these countries has the most stable voter turnout rate? Why?
United States of Coconut has the most stable voter turnout rate. For this country the variation between elections is smaller, that is 2 standard deviations about the mean hence more stable compared to the other countries with 10 standard deviations about the mean.
b. Calculate the 95% confidence interval for each country. Please report them in the
following format: [lower bound, upper bound]
A 95% confidence limit refers to 2 standard deviations about the mean.
Country Upper bound Lower bound
Ozeristan 58.76 41.24
Democratic Republic of Fisher 68.76 51.24
United States of Coconut71.75 68.25
Does the evidence support Hypothesis 1? Why or why not?
The evidence rejects hypothesis 1 since from the evidence the Democratic Republic of Fisher has a higher mean voter turnout on average that the Ozeristan considering they have a similar standard deviation and sample size used is the same size.
Does the evidence support Hypothesis 2? Why or why not?
The evidence supports hypothesis 2 since the United States of Coconut has a higher mean voter turnout on average than the other two countries.
What would happen if we increased the sample size to 10 elections? 100 elections?
Considering the sample is a representation of the general population, the mean voter turnout and standard deviation will remain the same, same values as before. The initial sample is a representation of the general population thus the results remain unchanged.
Question 2
a. What does it mean for something to be “statistically significant”?
It means that the activity did not occur by accident and hence the probability of that event occurring is usually low (p<0.5) and hence when it occurs it is not by chance.
b. What does it mean for something to be “substantively significant”?
It means the event or activity has a size large enough to have meaning that is the event does not only have a low probability of occurring but also has a size that could have an impact on a study/research.
c. If something is statistically significant, does that mean its also substantively
significant? Why or why not?
No. any event can be statistically significant as long as it had a low probability of occurring (p<0.5) but for it to be substantively significant it must also possess a size large enough to have meaning. Thus, all substantively significant events are statistically significant but not all statistically significant events are substantively significant.
d. Why are null findings still important and relevant?
Null findings and hypothesis, in general, are still important and relevant as they provide the researcher with a description to test and hence the experiment has a guiding tool. They are very important especially in novel experiments where the researcher does not know what to expect.
Question 3
Calculate a difference of means test.
Using the formulas;
Results
Difference -25
Standard error 2.121
95% confidence limit -29.1833 to -20.8167
t-statistic -11.785
DF 198
Significance level P<0.0001
b. Is there a statistically significant difference between the two groups (p<.05)? Why?
There is a statistically significant difference between the two means since the p-value is below 0.05. hence the null hypothesis is rejected.
Bonus question! (.5 points)
Who/what are you going as for Halloween?
I am thinking about going as myself but have not yet decided, still have a Lilo and stitch costume theme (Disney characters) at the back of my head
