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Melissa Alcaraz, Brigham Young University UYCA SUMMER YOUTH COURT CONFERENCE.

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Presentation on theme: "Melissa Alcaraz, Brigham Young University UYCA SUMMER YOUTH COURT CONFERENCE."— Presentation transcript:

1 Melissa Alcaraz, Brigham Young University UYCA SUMMER YOUTH COURT CONFERENCE

2  Three main points I will cover today are:  Why Data Matters  Preliminary Research Results  Recommendations on Data Collection INTRODUCTION

3 WHY COLLECT DATA  State mandate  In order to maintain certification, peer courts must submit standard data set.  Data that is gathered will be used to inform studies and annual reports  This will be used to evaluate and improve peer courts

4  Data can examine answers to important questions, such as:  Who is being referred to peer court most often?  Male/female, racial groups, etc.  What are the most common offenses among youth offenders?  Why? WHY DATA MATTERS

5  Data can examine answers to important questions, such as:  What are their backgrounds?  Income, single parent home, etc.  What do those that graduate from peer court have in common?  Dispositions, background, etc. WHY DATA MATTERS

6  We can discover what is and isn’t working.  Ultimately, data matters because the youth that are involved in peer court matter. WHY DATA MATTERS

7  Data retrieved from the Salt Lake Peer Court  Data was collected during intake.  Used JATRAX system and income surveys  I inputted the data into the Excel spreadsheet  Salt Lake Peer Court  186 Total Referrals  129 Cases NOT active. PRELIMINARY RESULTS

8  Graduated Compliant: 41%  Race: PRELIMINARY RESULTS Race of Youth Offenders (%) American Indian2.33 % Asian0.78 % Black9.30 % Hispanic/Latino48.84 % Middle Eastern0.78 % Pacific Islander1.55 % White36.43 %

9  Gender of those referred  Male: 55.5%  Female: 44.5%  Graduation rate by gender  Male: 46.5%  Female: 35.1%  Most common offense  Truancy: 46.5%  31.7% of these offenders came from single-parent households.  Average length of time in court  127 days  Single-parent Families  32.6% of all youth referred PRELIMINARY RESULTS

10 DATA COLLECTION RECOMMENDATIONS

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12  Creating a code for “Offenses”  Make sure every offense has a different number  Add the list to the coding guide  If a youth offender has multiple offenses, create an additional row(s) and log the additional offenses. DATA COLLECTION RECOMMENDATIONS

13  Common error  “0” vs. missing  Consequences of incorrect data  Accurate assumptions cannot be made  Incorrect data is equivalent to non-data DATA COLLECTION RECOMMENDATIONS

14 QUESTIONS?

15 Melissa Alcaraz melissa.alcaraz@live.com CONTACT INFORMATION


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