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State Bill Analysis CA AB2542
State Bill Analysis: CA AB2542
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Overview:
CA AB2542 is a senate bill authored by Assemblymember Ash Kalra (D-San Jose). This bill, also known as the California Racial Justice Act, was raised as a result of addressing racial discrimination within the criminal justice system based on race, ethnicity, and national background. This bill was coauthored by other senators such as Holly Mitchell, Steve Bradford, and Lena Gonzalez. Primarily AB 2542 was presented to the Senate by the governor to stop racial discrimination in the sentencing system because race and ethnicity had been significant factors that were considered in the state’s justice system that led to many African remain behind bars when compared to whites. The statistics indicate that Blacks had a more significant percentage of people who faced the death sentence than White people who had committed the same crime. This bill was determined to culminate racial bias and discrimination that had raised many cases in the state, sending many innocent Black as inmates. AB 2542 bill was aimed at eradicating racism from the entire criminal justice system and promoting justice and equality for all people despite their difference in color, ethnicity, and national background.
Analysis of Consistency with Bill Author’s priorities:
AB 2542 author is Assemblymember Ash Kalra, the political representative of the 27th California Assembly District. He is an Indian-American political representative in California State, a member of Democratic member, who was known as San Jose in his home for more than thirty-five years. He is known to be the first Indian-American to be elected to serve in California State Legislature after serving as an attorney in the Santa Clara County public defender’s office. As an attorney in Santa Clara County, he created a strong foundation for his legislative priorities. He became consistent and progressive in representing bills to Senate concerned with human well-being for all people despite being from different national backgrounds. This bill (AB 2542) is consistent with Ash Kalra’s legislative priorities because he has been known as a progressive assembly member who has served as an attorney and always worked with top-notch principles for a better life for all people. This bill (California Racial Justice Act of 2020) was authored in the year 2019-2020 legislative session. It addressed the 1987 legal precedent established by the state’s supreme court during McCleskey v. Kemp proceedings. This bill is consistent with his legislative priorities because the bill is directly concerned with defending people’s lives living in California. This is because many people have complaints concerning injustice and state violence in courts and sentencing. Kalra authored the AB 2167 bill that was primarily focused on the establishment of safe alternative incarceration. AB 2167 bill pushed the court to preside over criminal issues and consider alternatives to detention in consideration of diversion programs, probation, and restoration of justice. Additionally, Kalra authored the AB 256 bill that permitted and encouraged those convicted based on racial bias to seek justice in the court of law.
AB 2542 Supporters:
AB 2542 was a critical bill that received support from many senate members and departments because the bill was primarily focused on prohibiting the state from racial-based convictions due to ethnic differences. Since the existing rule allows individuals who were unlawfully imprisoned to prosecute a writ of habeas corpus to be informed of the reason for their imprisonment. Supporters of this bill include the LWV of California, the American Friends Service Committee, the Ella Baker Center of Human Rights, California Coalition for Women Prisoners, among others. Governor Gavin Newsom also supported AB 2542 bill since he claimed that it was aimed at making California an equitable state with a fair judicial process for all people despite their racial and ethnic differences. All AB 2542 supporters claimed that there is a need for reform in the criminal justice system through the trio of racial justice reform bills aimed at eradicating or reducing ethnic, socioeconomic, and racial bias in justice administration, especially the capital (death) penalty. Since they supported the prohibition of racial-based IQ adjustments used as determinants of the defendant’s capital punishment. And as a result, there was a reform that was attained, and criminal case defendants began facing court trials to be proven guilty or not guilty before the death penalty was passed or ruled as a way of addressing racism in court systems.
AB 2542 Opponents:
AB 2542 bill is primarily concerned with the well-being of Blacks in California, received significant opposition from various opponents such as: States senate judiciary Chairwoman Hannah-Beth Jackson, who insisted that any legislation in the states has to concede with the California Court’s jury selection which is based on racial systems. Opponents claimed that this bill would alter the court’s ruling. According to research, court systems were initially discriminatory based on racial, ethnic, and national backgrounds. American Bar Association indicates that AB 2542 received opposition because it could lead to overwhelming in the courts as well as causing more delays in adjudicating criminal cases. Additionally, they claimed the defendant would challenge judges, law enforcers, or attorneys over their charges which is not allowed after the ruling or decision has been made. Racial discrimination is pervasive in California’s criminal justice system; the judiciary opposed this bill because the court feared creating a sense of racism and discrimination in many criminal cases. And the court was afraid of providing too much justice for Blacks due to the ideology that Whites and Blacks were not supposed to be equal.
Fiscal Impact:
According to the senate appropriations committee, implementing bill AB 2542 would cost the state significant dollars. Report from the justice department indicated that it awarded $57 million in support for AB 2542 implementation. The amount would be used in implementing justice reforms as passed by the Senate to reform and advance racial equity in the criminal justice system. However, despite being costly, it will help nurture democracy in the state through equal treatment of people who have committed similar criminal offenses in California.
Conclusion:
AB 2542 bill was passed in assembly with 56-18 votes, and it also passed in the Senate with amendment 29-10 votes from the author. I agree with supporters of this bill because of the prohibition of racial, ethnic, and nationalist bias in the criminal justice system. Being an American, either Black American or White, there should be equitability based on the degree justice is practiced regarding the death penalty. This is because Blacks have long been oppressed, and justice has not been served equitably due to racial discrimination. Therefore, there is a need for law enforcement agencies, the judiciary system, and related organizations in criminal sentencing to determine incarceration on fair ground for all people without considering their racial and ethnic, or national background since all people deserve equal rights. The court should also ensure that cases are ruled on fairgrounds, primarily criminal cases, since cells have been overpopulated with Blacks, and most of them have lived behind bars despite being innocent. And as long as AB 2542 is concerned, the state should establish effective ways to how racial discrimination in the criminal justice and the court system should be established to eradicate any form of discrimination practically.
StatCrunch Procedures – Summary (StatCrunch Help)
StatCrunch Procedures – Summary (StatCrunch Help)
Qualitative Data – Frequency or Relative Frequency Bar Graph
With Data:
Graph, Bar Plot, With Data, Select Column(s), Select Type (Frequency or Relative Frequency), Order By: Choose Worksheet, Display: Check the Value Above Bar, Optionally enter Graph Properties, Compute!
With Summary:
Graph, Bar Plot, With Summary, Categories in: Select column with names of categories,
Counts in: Select column with categories frequencies, Select Type (Frequency or Relative Frequency, Order By: Choose Worksheet, Display: Check the Value Above Bar, Optionally enter Graph Properties, Compute!
Qualitative Data – Frequency or Relative Frequency Distribution Table
With Data: Stat, Tables, Frequency, Select Column, Statistics: Choose desired statistic(s) (normally Frequency or Relative Frequency), Compute!
Relative Frequency With Summary: First Create a Relative Frequency Bar Graph as above; then
create the Distribution Table obtaining the Relative Frequencies from the Values above the Bars
Qualitative Data – Pareto Chart
Create a Bar Graph as above; In the Order By: Choose “Count Descending”
Qualitative Data – Pie Chart
Graph, Pie Chart, With Data or Summary, Display: Count and Percent of Total
5. Quantitative Data – Histogram (Frequency or Relative Frequency)
Graph, Histogram, Select Column(s) with Data, Select Type, Bins: Do not enter to use
StatCrunch defaults or enter desired values, Display options: Check the Value Above Bar, Optionally enter Graph Properties, Compute!
6. Quantitative Data – Distribution Table (Frequency or Relative Frequency)
First create a Histogram as above, then from the x-axis of the graph, determine width and starting point of each class, then determine corresponding Frequencies by reading the values above each bar
7. Summary Statistics
Stat, Summary Stats, Columns(s), Select the statistics you want. Select multiple by holding the CTRL key while clicking on a choice, Compute!
Note: for Standard Deviation:
Sample, choose Std. Dev.;
Population, choose Unadj. Std. Dev.
8. Quantitative Data – Mean for Grouped data
Stat, Summary Statistics, Grouped / Binned Data
Bins in: Classes
Counts in: Frequencies
Check Consecutive lower limits for Midpoint’s calculations
Choose the Statistic: mean, std. dev.
9. Quantitative Data – Weighted Mean
Stat, Calculators, Custom
Values in: Column containing the data whose average we are seeking Weights in: Column containing the weights
Compute!
10. Box Plot
Graph, Box Plot, Select Column(s), Check both of “Other Options”; On the generated Box Plot: Place the cursor over an outlier to get info about it. Place the cursor over the box plot to get info about the five-number summary.
11. Scatter Diagram (Plot)
Graph, Scatter Plot, Select X Variable column, Select Y Variable column, Display: Points, Optionally enter Graph Properties, Compute!
12. Correlation
Stat, Summary Stats, Correlation
13. Regression
Stat, Regression, Simple Linear, Select Column for X Variable, Select Column for Y Variable. (Optionally: enter Save: Residuals, Predicted values for Y: enter desired x value), Compute!
14. Discrete Probability Distribution: Mean & Std Dev
Stat, Calculators, Custom, Values in: Column containing the Discrete variable X,
Weights in: Column containing the Probabilities for X: P(X), Compute!
Binomial Probability
Stat, Calculators, Binomial
Normal Probability Distribution
Stat, Calculators, Normal
17. Find Areas (Probabilities) Under Normal Curve
Stat, Calculators, Normal, Select Standard or Between, Input the values for Mean and Std. Dev., Select the inequality sign, Input the value for X, Compute!
NOTE: For the Standard Normal Curve, use Mean = 0 and Std. dev. = 1
18. Find X-value under a Normal Probability Curve
Stat, Calculators, Normal, Select Standard or Between, Input the values for Mean and Std. Dev., Select the inequality sign, Input Probability (Area) in the Probability field (rightmost), Compute!
NOTE: For the Standard Normal Curve, use Mean = 0 and Std. dev. = 1
19. Normal Probability Plot (QQ Plot)
Graph, QQ Plot, Select Columns, ADD: Check Correlation Statistics, Other Options: Check Normal Quantiles on Y-axis, Compute!
20. T-Distribution
Stat, Calculators, T
21. Find Areas (Probabilities) Under t-Distribution Curve
Stat, Calculators, T, Select Standard or Between, Input the value for Degrees of
Freedom (n – 1), Select the inequality sign, Input the value for t, Compute!
22. Find t-value under a t-Distribution Curve
Stat, Calculators, T, Select Standard or Between, Input the value for Degrees of
Freedom (n – 1), Select the inequality sign, Input Probability (Area) in the Probability field (rightmost), Compute!
23. Find Areas (Probabilities) of x that is Normally Distributed
Stat, Calculators, Normal, Select Standard or Between, Input the values for Mean
(µx = µ) and Std. Dev. (σx = σn), Select the inequality sign, Input the value for x, Compute!
24. Find Areas (Probabilities) of p that is Normally Distributed
Stat, Calculators, Normal, Select Standard or Between, Input the values for Mean
(µp = p) and Std. Dev. (σp= p(1-p)n), select the inequality sign, Input the
value for X ( p), Compute!
25. Confidence Interval – One Proportion
Stat, Proportion Stats, One Sample, With Summary (or With Data, if available), Input # of successes and observations, Select Confidence Interval Level (leave Method as is), Compute!
26. Confidence Interval – Proportion – Sample Size
Stat, Proportion Stats, One Sample, Width/Sample Size, Confidence Level: enter desired level, Target proportion if given, otherwise enter 0.5, Width (twice the Error)
27. Find Critical Value zα2
Stat, Calculators, Normal, Select Standard, Input Mean = 0 and Std. Dev =1,
Select the inequality sign for ≥, enter the α2 value in the Probability field (rightmost), Compute!
28. Confidence Interval – One Mean
Stat, T Stats, One Sample, With Summary (or With Data, if available), Input Sample Mean, Sample Std. Dev, Sample Size, Select Confidence Interval and Input the Desired Confidence Level, Compute!
29. Confidence Interval – Mean – Sample Size
Stat, T Stats, One Sample, Width/Sample Size, Confidence level: desired level, Std. Dev., Width: twice error, Compute!
30. Find Critical Value tα2Stat, Calculators, T, Select Standard, Degrees of Freedom (n-1),
Select the inequality sign for ≥, enter the α2 value in the Probability field (rightmost)
31. Confidence Interval – Variance or Standard Deviation
Stat, Variance Stats, One Sample, With Summary (or With Data, if available), Input Sample Variance, Sample size, Select Confidence Interval and Input the Desired Confidence Level, Compute!
32. Find Critical Value χ1-α22 and χα22Stat, Calculators, Chi-Square, Select Between, Degrees of Freedom (n-1), enter the (1−α) value in the Probability field (rightmost), Compute!
Hypothesis Testing – One Population Proportion
Stat, Proportion Stats, One Sample, With Summary (or With Data, if available)
Hypothesis Testing – One Population Mean
Stat, T Stats, One Sample, With Summary (or With Data, if available)
Hypothesis Testing – One Population Variance, Standard Deviation
Stat, Variance Stats, One Sample, With Summary (or With Data, if available)
Hypothesis Testing – Two Populations Proportions
Stat, Proportion Stats, Two Samples, With Summary (or With Data, if available)
Hypothesis Testing – Two Means: Dependent (Paired) Samples
Stat, T Stats, Paired, Good idea to Save differences by clicking on the check box
Hypothesis Testing – Two Means: Independent Samples
Stat, T Stats, Two Samples, With Summary (or With Data, if available)
Hypothesis Testing – Goodness of Fit
Stat, Goodness-of-Fit, Chi-Square test
40. Hypothesis Testing – Test of Independence
Stat, Tables, Contingency, With Summary:
In the Select Columns area, choose the Columns containing the values of the Column Variable
In the Row Labels, choose the column containing the name of the Row Variable
In the Display area choose “Expected Counts”
In the Hypothesis tests area, choose “Chi-Square test for independence”
41. Hypothesis Testing – Test the Homogeneity of Proportions
Same procedure as for Test of Independence
42. Comparing Three or more Means (ANOVA)
Stat, ANOVA, One Way, Choose the columns containing the three or more samples.
43. Two-Way Analysis of Variance (ANOVA)
In column var1, enter the level of factor A; in column var2, enter the level of factor B; and in column var3, enter the value of the response variable. Name the columns.
Stat, ANOVA, Two Way, Select the column containing the values of the response variable from the pull-down menu “Responses in:”,
Select the column containing the row factor in the pull-down menu “Row factor in:”,
Select the column containing the column factor in the pull-down menu “Column factor in:”, Select the “Plot interactions” box for Interaction Plots and “the Compute Tukey HSD” box to conduct Tukey’s test, To save residuals to draw a normal probability plot, highlight Residuals under Save:, Compute!
Start-Up Phase
Start-Up Phase Test-Phase
Number of Months & Date Range___2_ Months (or weeks)From: _____January____ To: _February_______ Number of Months & Date Range___3_ Months (or weeks)From: ___March_______ To: ________May____
Major Objectives
1) Understand and Write Business Plan
2) Design/Build Product (or Service)
3) Organize business
4) Build organization
5) Operationalize Major Objectives
1) Learn Market Preferences
2) Test Market
3) Build Customer Base/Following
4) Exposure5) Generate revenue
Specific Activities (Checklist)
1. Raise capital
2. Identify reliable suppliers
3. Identify target market location
4. Identify market gap
5. Introduce product to market
6. Monitor competition
7. Buy assets eg blending machines
8. Specific Activities (Checklist)
1. Get customer feedback
2. Grow marketing strategies
3. Employ more staff
4. Create variety of products
5. Identify new target markets
6. Open a new branch
7. Expand social media platforms
8.
Detailed Expenses
1. Rent
2. Electricity
3. Supplies
4. Transport & travel
5. Repair & maintenance
6. Miscellaneous
7.
8. Detailed Expenses
1. Employee salaries
2. Rent
3. Electricity
4. Transport & Travel
5. Repair & maintenance
6. Miscellaneous
7. Supplies
8. Telephone & internet
Total Anticipated Budget
$ 4,000.00 Total Anticipated Budget
$ 8,000.00
Anticipated Working Capital Needed
$ 2,080.00 Anticipated Revenue & Profit/LossRevenue: $ 400.00Profit/Loss: $ 5,500.00