TEAMWORK

1
TEAMWORK
2
Discovery Grant Learning Seminar 1
Data Sources and Analysis

• Priscilla F. Canny, Ph.D.
• Peg Oliveira, Ph.D.
• CT Voices for Children
• February, 2002

3
Overview

• Importance of data
• Community Toolbox
• Indicators of child well-being
• Actual data census, SSP, town spreadsheets
• Data sources
• Data tips, cautions, limitations
• Data analysis and interpretation

4
Why Collect Data?

• Everyone wants it now
• Funders
• Media
• Public officials
• Legislators
• Parents
• Community programs for planning

5
Data Drives Public Policy

• Over the last decade, there has been a marked
  shift in the content of public discussions about
  children and families. Discussions are now much
  more likely to be based on research and
  statistical facts rather than ideology and
  rhetoric. News stories and policy discussions
  are more likely to rely on objective facts
  regarding the status of child and family
  well-being.

William P. O'Hare KIDS COUNT Coordinator The
Annie E. Casey Foundation
6
Two Local Examples of Data-Driven Success

• New Haven
• Early childhood education initiative
• Asthma initiative
• New Britain

7
Mary Ellen Powell New Britain Foundation

• The report has provided us with baseline data
  that we did not have before.
• It has been a guiding force for us in grantmaking
  decisions we have made a number of grants that
  address directly findings from the report.
• The report has also been a catalyst for several
  initiatives we are about to embark upon including
  the Discovery Grant, an asthma initiative and a
  possible oral health initiative.
• The United Way has established a special task
  force of its board to identify additional
  initiatives to implement based on the findings of
  the report.
• The report has also been used by non-profit
  organizations. Several have quoted statistics
  from the report in proposals to us and other
  funders aimed at addressing the needs of children
  and youth. We feel confident saying that a
  number of these organizations have secured
  funding as a result of having this information
  from the report.

8
Usefulness of Data

• Are there any other other communities here that
  have gathered data and interpreted it for
  community planning needs? comments?
• What have you done in your community?

9
Why Collect Data?Community Toolbox

• Information provides knowledge
• Information demonstrates credibility
• Information leads to change
• Information is power
• Information is a tool

http//ctb.ku.edu
10
Why Collect Data Power

• Data is a powerful tool with which to
• Make decisions on issues affecting children and
  families
• Define and understand baseline, current situation
• Prioritize and plan for the future, identify
  areas where action is most needed, set goals,
  measure progress towards goals
• Monitor progress on childrens issues over time
• Inform the policy making process

11
Why Collect Data Tool for Collaboration

• Gets everyone around the table
• Helps develop buy in
• Facilitates data collection

12
Indicators of Child Well BeingTab 4

• National, state, local examples
• Rationale for key indicators of child well-being

13
Indicators of Child Well-Being

• Demographic
• Economic
• Infant and child health
• Education
• Safety and Security

14
Demographic Indicators

• Age
• Gender
• Race and ethnicity
• Maternal education, language
• Context of childrens lives

15
Economic Security Indicators

• Household income (per capita income)
• Poverty
• Eligibility for free and reduced price meals
• Good annual proxy for child poverty
• Public Assistance
• Unemployment

16
Infant and Child Health Indicators

• Prenatal care
• Infant mortality
• Low birthweight
• Immunizations
• Injuries
• Asthma
• Obesity

17
Education Indicators

• Early childhood education
• availability, cost and utilization of child care
• Preschool attendance
• CMT scores
• Dropout rates

18
Safety and Security Indicators

• Child abuse and neglect
• Juvenile violent crime rates
• Family violence

19
Sources of Data

• Public records
• Local data
• Surveys
• Focus groups
• Individual interviews
• Inventories of resources/assets

20
Census DataTab 5

• Census data
• factfinder.census.gov
• Short form (demographics) available-in packet
• SF3 and 4 (economics, education, employment) this
  summer and fall (2002)
• Yearly estimates (CPS) not done for towns, and
  barely valid for state (demographics, poverty)

21
(No Transcript)
22
(No Transcript)
23
Town DataTab 7
24
Existing Data Sources

• Review data sources pages
• (Tab 8)

25
Where to Call for ECE Data
26
Some Data May Not Be Available

• Mental health indicators
• How many children are read to
• Are children ready for school
• Are schools ready for children
• Percent of children who demonstrate age
  appropriate developmental skills
• Quality of child care
• Others?

27
Data Cautions

• Timeliness of data
• Example State Health Department, 2000 Census
  Data
• Quality of data
• Ask questions
• Who and how collected ( preschool)
• Comparability of data
• Example FRPM- definitions change
• Example Data from two different sources
• per capita income

28
Estimates ofPer capita income
CPEC-1998 personal income-BEA
DECD- 1998 money income-census
29
Data Collection CautionsEven Existing Data Can
Be Difficult to Collect

• Often state and local officials either too busy
  or unwilling to give data-- worried it will be
  misunderstood, defensive

30
Limitations of Existing Data

• Census
• Race/ethnicity
• Not 1990, 2000 not ready
• Self-report
• Child poverty
• No annual estimates for towns
• TANF
• Obsolete definition

31
Look Behind the Numbers

• Example 1. Fighting in a school in Colorado
• Example 2 Branford drop out rate
• Example 3 Variation among schools

32
Child Indicators New Haven Suburbs 1998
11

21

4

1. adjusted for 1996 population 2. based on
eligibility for free and reduced price lunch 3.
percent meeting state goal region 5 Amity
High School
33
Example 2Branford Dropout rate1997-2001
34
Example 3 Variation Among SchoolsManchester
School Poverty
35
Example of Presentation of Data Manchester
School Poverty
36
Data Interpretation and Analysis

• Comparisons
• Town with itself, within town (eg schools,
  neighborhoods), with other towns, with state,
  with nationjudgment by each variable
• Danger of small numbers (lt10), small samples
  (lt100) unreliable 3 year averages
• Other variables that could have an impact on
  changes in data (eg changing economics)

37
Data Analysis, Interpretation and Prioritizing

• SWOT analysis
• How to interpret negative versus positive
• What is your philosophy glass half full, glass
  half empty
• Denial, defensiveness
• Bring multiple sources of data together and
  interpret

38
From Data to Action

• Gathering information is only putting the pieces
  of puzzle on the table
• Need to put the puzzle together
• Need to look at data
• Get everyone around the table and discuss what
  the data shows

39
Future workshop?
40
Future Workshops

• Data tips 201
• Count your data
• Compute your data
• Compare your data
• Present your data
• Examples of how to present data
• Hands-on tutorials accessing data on the Internet

41
Expanded Notebook

• More town data health, early childhood
  education, crime, safety
• A Guide to Using Data for Effective Advocacy
• A Community Toolbox Assessing Community Needs
  and Resources
• A Guide to Creating Community Report Cards

42
Website www.ctkidslink.org