moving a large human service department from check-only-one to check-all-that-apply (cata) race and...
TRANSCRIPT
Moving a Large Human Service Department from Check-only-one to Check-all-that-apply (CATA) Race and Ethnicity Options
2014 Annual Educational Conference
What We’ll Cover Today• Introduction
• Assumptions, terms• What are we measuring?• Multi-racialism
• Saga of our human services department moving from check-only-one to check-all-that-apply
• Details, details• Asking the questions• Storing the data• Data analysis and presentation
• Questions, discussion
WHAT ARE WE MEASURING?Beginning Assumptions, Defining and measuring race, Multi-racialism
Your Race
Your Races and Ethnicity
Your Origins
Beginning Assumptions• Just about everything about the
measurement of race/ethnicity/origin is controversial.
• The measurement of race/ethnicity/origin is evolving.
• Measurement of race/ethnicity/origin is a technology, process, a function in service of policy.
• Race is a political, social and cultural creation. Both the determination of race and its measure have a very unsavory past and a tortured present.
Terms…• Phenotype: How closely a person reminds
people of one of the big five races or ethnicity.
• Race: A grouping of people based on phenotype who originated in an insular geography.
• Ethnicity: a cultural grouping within a race. • National origin: The country or continent
where you or a close blood relative or perhaps an ancestor was born.
Carl Linnaeus, 1735,The Four Races• Americanus: reddish, choleric, and erect; hair
black, straight, thick; wide nostrils, canty beard; obstinate, merry, free; paints himself with fine red lines; regulated by custom.
• Asiaticus: sallow, melancholy, stiff; hair black; dark eyes; severe, haughty, avaricious; covered with loose garments, ruled by opinion.
• Africanus: black, phlegmatic, relaxed; hair black, frizzled; skin silky; nose flat; lips tumid; women without shame, they lactate profusely; crafty, indolent, negligent; anoints himself with grease; governed by caprice.
• Europeaeus: white, sanguine, muscular; hair long, flowing; eyes blue; gentle, acute, inventive; covers himself with close vestments; governed by laws.
2010 Census Choices
History of Multi-racialism• Rape of female African slaves by white
slave owners and other whites, resulting in the “browning” of enslaved Americans.
• After emancipation, racial purity emphasis along with Jim Crow; legal separation of the races.
• 1890 Census, first “multi-racial” count: white, black, mulatto, quadroon, octoroon. Also Chinese, Japanese or [East] Indian.
• Early twentieth century Eugenics movement.
Multi-racialism, continued• Loving case, 1947
• “Almighty God created the races white, black, yellow, malay and red, and he placed them on separate continents. And but for the interference with his arrangement there would be no cause for such marriages. The fact that he separated the races shows that he did not intend for the races to mix.”
• 1967 – last state miscegenation legislation struck from the books.
• Hispanic ethnicity: Hispanic and …
MOVING A LARGE HUMAN SERVICES DEPARTMENT TO CHECK-ALL-THAT-APPLY
What are the facilitators and barriers to implementation of CATA in your
organization?Why should your organization
measure race?
What Human Services Needs to Measure• Equal, equitable and appropriate access to
services• Is there unequal access to services or
service outcomes by people on the “wrong” side of the color line?
• Are we serving the needs of immigrant populations?
• Rates of service penetration in distinct race/ethnic/origin communities.
• Interest in emerging populations we cannot see.
• Interest in special needs of race/ethnic/origin populations.
2010: The Stars Align
County Health Department
Equity Initiative: Equity and
Empowerment Lens
Coalition of Communities
of Color Report
External Motivators
Relatively new Human Services
DepartmentDirector and R&E Analyst
Internal Motivators
Division Directors not
opposed
Provided rationale and language to articulate need
IT Services not
opposed
2010• Creation of a work group: the “Visibility
Initiative”• Charter from director to all data staff in all
human service divisions• Emphasis on collaborative and incremental
• Job One: Mapping of data systems, potential for change• “What we can change, what we can’t
change, and know the difference.”
2011- 2012• Job Two: List of races, ethnicities, and
origins• The “granularity” question• Eventually, took Coalition of Communities
of Color advise – reflection of our county population
African Native American or Alaska Native Asian Native Hawaiian or Pacific Islander Black/African American Slavic Latino/Hispanic White Middle Eastern Decline to Answer
2012-13: Implementation• Department policy statement (not
countywide policy)• Once again, collaborative and incremental
• Job Three: Training for roll-out• Oregon Hospital Association, nice video• Emphasis on…
• Client self-identification• Use of the already-set groups (no “Other”,
no write-ins)• When to use “Prefer not to answer”
“If we discover inequities, then we’ll be expected to do something about it.”
Future of the Visibility Initiative• What do we do with the data?• How do we coordinate with the State of
Oregon?• Monitoring and insuring implementation
over time• What about other demographic variables?
2014• National Association of Counties award for
innovation
CHOICES: COLLECTING THE DATA
Let’s collect some data.
• Overview• CATA or yes/no forced choice?• Equal status vs. roll-up?
Collecting CATA Data
Asian-AmericanChineseFilipinoJapaneseKoreanVietnameseNative HawaiianGuamanian or
ChamorroSamoan
• Web-based surveys• Wonky alternative:
Dropdown multiple selection boxes
• Multiple boxes, multiple selection
Collecting CATA Data
• Web-based surveys• Wonky
alternative: slider bars that represent percent of each race/origin
Collecting CATA Data
• Paper Survey• Considerations
• “Real estate”• Confusion if asking both CATA and COO
questions• Radio buttons and check boxes
Asking CATA Questions
• Phone interviews• Too many options! Alternative:
• Ask as yes-no questions• Ask for self-report and then extrapolate
• In-person interviews• Show the CATA questions and have the
interviewee complete or point to the relevant options
• Ask for self-report and extrapolate
Asking CATA Questions
Training of Those Asking CATA Questions • Visibility Initiative put a great deal of time
into training and roll-out • Content
• Rationale• How we got here• County becoming more diverse• Missing crucial data by using check-only-one
Training, continued• Consistency insures better data• Address questions, concerns:
• Client resistance or questions• Worker resistance or questions• FAQs
• On-line training
CHOICES: STORING THE DATAHow many characters do you have to
work with?How old and creaky are your data
systems?Is there anyone still around with the knowledge to change your system?
Storage of CATA Data• Old systems
• Possibly less flexible• Possibly only one field
• Only one or two digits assigned to the field• Can’t change, or too much trouble to
change?• If new or developing system
• No problem, as long as there is the political will to do so
• Old system• Only one field, opportunity to use many
digits• Reduce responses to 1 = checked and 0 =
unchecked• Number is as long as number of options• Ex.: Eleven options, three races/origins
selected: 00100101000.• Wonky alternate, one field, many digits
• Place more common selections early on in the list
• Use prime numbers to count number of items (2,3,5,7,11,13,17, …)
• Multiply selection by the prime associated with it.
Storage of CATA Data
• Old data system• Only one field, only about four digits
• Assume a maximum number of respondent choices of race/ethnicity/origin (Say, 4 choices)
• Label race/eth/orig options 1 to x• Record choices in four digits, e.g., 3125
Storage of CATA Data
Key:1 = African2 = Asian3 = Black4 = Latino5 = Middle East6 = Native Am.7 = Native Hawaiian8 = Slavic
x
x
x
Response above: “1360”
CHOICES: DATA ANALYSIS AND PRESENTATION
What do we need to know?
Overview• Analytic Challenges
• “Rolling up” multi-racial respondents into a single race to suit funders
• Small cell size for multi-racial respondents• The dangers of rolling up to a single “multi-
racial” or “other” response• The “greater than 100%” challenge
Analysis of CATA Data• Office of Management and Budget, 2000
1. Include those who indicated membership in one of the five single race categories: White, American Indian/Alaskan Native, Black/African American, Native Hawaiian/Other Pacific Islander, and Hispanic/Latino
2. Include the four most prevalent double race combinations
1. Native American/White2. Asian/White3. African Am./White4. Native Am./African Am.
3. Include all other combinations that represent more than one percent of the sample population.
Analysis of CATA Data• Multiple group assignment
• Each respondent is fully counted in each group checked
• Inflates categories• The “More than 100%” challenge
• Wonky workaround: Assignment of understood fractions (e.g., .5 Asian and .5 White for respondents checking White and Asian)
• No more “multiracial”• Lots of validity concerns
Descriptive Presentation of client populations
Race/ethnicity/ origin
Unduplicated
Alone or in Combination
% Unduplicate
d
% Alone or in
Combination**
White 45 48 39% 41%Black 33 38 28% 33%
Asian-Am. 25 28 22% 24%Am. Ind/AK
Native 8 14 7% 12%Nat. Haw/PI 5 7 4% 6%
Total 116 * 100% **Does not sum.
** Denominator = 116
COO vs. CATA Presentation
Race/Ethnicity
Black, 18%White, 42%
Slav ic, 8%
African
Imm., 1%
Nativ e
Amer, 5%
Pac
Islander, 4%
Asian Amer,
2%
Multi-racial,
5%Hispanic,
15%
0% 10% 20% 30% 40% 50%
African
Asian
Haw aiian-Pacific Islander
Slav ic
Nativ e American
Hispanic
Black
White
Presentation of CATA Data
Asian/White = 45%
Black/AmInd = 10%
Black/White = 45%
Simple graphical presentation:Bar within piePie within pie
Questions? Comments? Discussion?