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?