2012 slds p-20w best practice conference 1 a ggregate r eporting and d ata d isclosure a voidance t...
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2012 SLDS P-20W Best Practice Conference L OUISIANA 3TRANSCRIPT
2012 SLDS P-20W Best Practice Conference 1
AGGREGATE REPORTING AND DATA DISCLOSURE
AVOIDANCE TECHNIQUES Monday, October 29,2012
Kim Nesmith, Louisiana Department of EducationAdrian Peoples, Delaware Department of Education
Baron Rodriguez, Privacy Technical Assistance Center
2012 SLDS P-20W Best Practice Conference
• Louisiana Process and Types of Suppression
• Delaware Public Reporting Rules and Strategy
• Contact Information and Resources
OVERVIEW
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LOUISIANA
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• Determining a “n” size
• Determining a percentage threshold
• Limiting student Level Reports and establishing MOUs
FIRST STEPS
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• Determining what is most important
• Determining how to handle complementary suppression
NEXT STEPS
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• If you can “back into a number”, the suppression is not effectiveo When only one number in a row or column is
suppressed and the total is present
o When all suppressed numbers are 0s and the total is present
o If numerator, denominator, and percentage are all present
COMPLEMENTARY SUPPRESSION
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N SIZE EXAMPLE
Scholarship School Name Enrollment by GradeK 1 2 3 Total
School A 16 8 8 6 38School B 15 0 0 0 15School C 3 0 0 0 3School D 62 20 13 15 110School E 3 1 0 1 5School F 31 22 8 15 76School G 14 14 15 12 55TOTAL 144 65 44 49 302
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N SIZE EXAMPLE
Scholarship School Name Enrollment by GradeK 1 2 3 Total
School A 16 <10 <10 <10 38School B >=10 <10 <10 <10 15School C <10 <10 <10 <10 <10School D 62 20 13 15 110School E <10 <10 <10 <10 <10School F >=30 >=20 <10 >=10 76School G 14 14 15 12 55TOTAL 144 65 44 49 302
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PERCENT EXAMPLE
LEA Name
All Students Special Ed.Dropouts Total Rate
Dropouts Total Rate
District A 61 2,499 2.4% 12 265 4.5%District B 10 1,210 0.8% 2 94 2.1%District C 45 5,919 0.8% 6 457 1.3%District D 34 1,167 2.9% 3 93 3.2%District E 7 388 1.8% 4 41 9.8%District F 23 409 5.6% 2 22 9.1%
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PERCENT EXAMPLE
LEA Name
All Students Special Ed.Dropouts Total Rate
Dropouts Total Rate
District A 61 2,499 2.4% 12 265 4.5%District B >10 >1,210 <1% <10 >90 2.1%District C >40 >5,910 <1% <10 >450 1.3%District D 34 1,167 2.9% <10 >90 3.2%District E <10 >380 1.8% <10 >40 9.8%District F 23 409 5.6% <10 >20 9.1%
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• Talking with the requestor
• Creative solutions
MAINTAINING TRANSPARENCY
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DELAWARE
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Rule of X• Delaware masks all data for a particular
demographic if its group size is less than or equal to X
• 15 for Assessment, Enrollment, Teacher Quality
• 40 for Accountability
5/95 Rule• If demographic performance is calculated
to be either at or below 5% OR at or above 95%, Delaware masks the data.
DELAWARE PUBLIC REPORTING RULES
2012 SLDS P-20W Best Practice Conference
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Database
Data
Application
STRATEGY: LEVEL OF IMPLEMENTATION
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Data
Level of Maintenance
Database
Application
MAINTENANCE GRADIENT
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Data Suppression• DO NOT SHOW data to any constituent group
(e.g. public, administrators, teachers, etc.)• DO NOT ALLOW aggregate data to be used as
input to any data-driven decision-making
Effect Suppression• SHOW data to appropriate constituent group
(e.g. public, administrators, teachers, etc.)• DO NOT ALLOW aggregate data to be used as
input to any data-driven decision-making
STRATEGY: DATA VS. EFFECT SUPPRESSION
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IMPLEMENTATION EXAMPLE: DATABASE LEVEL/DATA
SUPPRESSION
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IMPLEMENTATION EXAMPLE:DATABASE LEVEL/DATA
SUPPRESSION
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IMPLEMENTATION EXAMPLE: APPLICATION LEVEL/EFFECT
SUPPRESSION
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BIGGEST PITFALL: INCONSISTENT
IMPLEMENTATIONPolicy
Accountability Assessment Enrollment Teacher Quality
• Small constant team• Long history
• One point of contact• Both policy and data
• Multiple transient contractors
• Newcontractor
• Bringing new reports to the public
2012 SLDS P-20W Best Practice Conference
• PTAC State-by-State analysis of public reports:
2PM today in the Burnham room. Please send a representative from your state to receive your sealed copy!• Case Study 5: Minimizing Access to PII…• Data De-identification: A Glossary of Terms
RESOURCES/SESSIONS
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Frequently Asked Questions:
1. If I am only publishing aggregate data tables, do I still need to be concerned about disclosure avoidance?
2. What issues should educational agencies and institutions consider to successfully balance privacy protection requirements with data disclosure requirements?
3. Is public reporting of data for small groups (“small cells”) the same thing as a disclosure?
4. What standard is used to evaluate disclosure risk? 5. Does the U.S. Department of Education require
educational agencies and institutions to use specific data disclosure avoidance techniques?
6. And many more…
PTAC GUIDANCE FAQ’S
2012 SLDS P-20W Best Practice Conference
Contact information:Adrian Peoples, [email protected] Nesmith, [email protected] Baron Rodriguez, [email protected]
For more information on Aggregate Reporting:Resource 1: Presentation: Protection of Personally Identifiable Information through Disclosure Avoidance TechniquesResource 2: PTAC Privacy Toolkit – Case Studies, etc.Resource 3: Tech Brief #3: Statistical Methods for Protecting Personally Identifiable Information in Aggregate Reporting (DRAFT; Dec 2010)
CONTACTS & ADDITIONAL RESOURCES
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