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					The Use of First Names to Evaluate Reports of Gender and Its Effect on the Distribution of Married and Unmarried Couple Households
Martin O’Connell and Gretchen Gooding Fertility and Family Statistics Branch US Census Bureau

Poster presented at the Annual Meeting of the Population Association of America, Los Angeles, CA, March 30-April 1, 2006. This report is released to inform interested parties of ongoing research and to encourage discussion. The views expressed on statistical, methodological, or technical issues are those of the authors and not necessarily those of the U.S. Census Bureau.

Classifying Unmarried Couple Households
 Household classification depends on reports of relationship and gender.



Sex is usually the best reported item on surveys1, but reports of names may sometimes seem inconsistent with reports on gender.
Distribution of coupled households in Census 2000:
Three Types of Coupled Households
1% 8%



60 million coupled households

Married Couple Opposite-Sex Unmarried Couple Same-Sex Unmarried Couple
91%



1

Less than 1 percent had inconsistent responses on the Census 2000 Content Reinterview Survey.

Why Study Reponses to Names and Gender?
 Minor errors in reporting gender can have a substantial impact on the overall estimates of unmarried couple households.
 The 1996 Federal Defense of Marriage Act instructs federal agencies only to recognize opposite-sex marriages.  "In determining the meaning of any Act of Congress, or of any ruling, regulation, or interpretation of the various administrative bureaus and agencies of the United States, the word 'marriage' means only a legal union between one man and one woman as husband and wife, and the word 'spouse' refers only to a person of the opposite sex who is a husband or a wife."  Current Census Bureau editing programs assign reported same-sex ―married‖ couples to same-sex ―unmarried‖ couples.

 With several states issuing marriage licenses to same-sex couples, the issues of collecting, processing, editing, and presenting estimates of same-sex couples will become more important, especially when examining estimates for specific states and cities.

What This Project Will Examine—
   Can a person’s first name be used to verify reports of gender? How accurate is the reporting of names? What would be the effect on different household estimates when using a person’s name to alter reports of gender? How sensitive would these estimates be to changes in responses of gender?



2004 American Community Survey
 To address these issues, two data sources are used in this presentation : First, the 2004 American Community Survey (ACS). This survey will be used to illustrate differences in the reporting of gender for specific names by:
 Major Census divisions  Age cohorts

 



The 2004 ACS selected a nationwide sample of 838,000 households. Starting in 2005, it consisted of 3 million households in the yearly sample.



2004 Test Census of New York
 Second, the 2004 Test Census of New York. We will examine—
 The likelihood that a person’s name is male or female  Age and race differences in reporting masculine or feminine names  The gains or losses to different types of households if first names are used to verify/change reports of gender



The 2004 Test Census of New York was conducted in the county of Queens. Overall, there were 130,756 households. The test census consisted of 60,244 ―coupled households.‖
7% 2%



Married Couple Opposite-Sex Unmarried Couple Same-Sex Unmarried Couple 91%

2004 Test Census Items on Name, Relationship, and Gender

Common Errors in Collecting Names
 Inconsistencies in the collection of names on forms may result from the following types of errors:
     Scanning errors of forms Keying errors of names Respondent/enumerator misspellings Illegible handwriting Transposing first and last names—e.g., Mary Thomas written as Thomas Mary  Concatenating names—e.g., Jack’s son as Jackson  Names with non-alphabetic characters (e.g. *, @, $, 4) (Spaces and hyphens are accepted)

Are All Names Created Equal?
 The same name may be correctly reported as being a different sex for several reasons:
 Geographical  Ethnic/cultural  Different age cohorts

Gender of Some Names May Change Over Time While Others May Remain the Same
100 90

80

70

Percent Reporting Male

60 John 50 Morgan Leslie Elizabeth 40

30

20

10

0 <10 10-19 20-29 Age Cohort in 2004 30-39 40+

Source: U.S. Census Bureau, American Community Survey 2004.

Methodological Issues
 Considerations when using a first name to override reported sex responses:
 Develop an objective/statistical indicator with a variable range  Define acceptable levels for altering a sex response—e.g. should name be ―male‖ 50%, 90%, 99% of the time to override a response of ―female‖  Evaluate impact of procedure on estimates for all couple types—anyone can make a mistake  Indicator should be sensitive to geographical variations  Indicator should be usable in large scale processing applications

2004 Test Census of New York First Name Index
 On each person’s record, there is a first name index:
 Based on millions of observations in the 2000 Census of New York State name dictionary  Index = (people with that name who were male)/(all people)  Index ranges from 0 to 1000  A high value, e.g. 990, means 990 out of every 1000 people with that name in 2000 reported themselves as male—a very masculine name  A low value, e.g. 50, means that only 50 out of every 1000 people were reported as male—or that 950 were female—a very feminine name



For consistency purposes for this presentation:
 Index scale reverses for females  A value of 990 for females now indicates that 990 out of 1000 people with that name in 2000 reported themselves as female  Index scale for males unchanged

First Name Index Characteristics
 The majority of men (50%) and women (59%) had first names very strongly associated with their sex (Index = 990–1000). Only 1% had first names that were inconsistent with their reported sex (Index <= 10).





However, there are some shortfalls in the applicability of this index for the total population:
 11% of people did not report their names  7-8% had first names that could not be found in the dictionary  Using first names to invalidate sex responses may not cover large segments of the population

Coverage and Properties
 For men in the 2004 Test Census:
 Name not reported or not in dictionary higher for • Men 15 to 44 • Chinese, Korean, Asian Indian men  Highest percent of men with first name indices 990-1000 • Older men • Whites and Blacks  Percent of men with first name indices 100 or less • About 1% for all ages • About 2% for Korean, Asian Indian men



Similar patterns were found for women.

Percent of Males With First Name Index 100 or Less
0-14 15-29
0.9 0.8 0.8 0.8 0.6 0.7 0.7 0.9 1.4 1.3 0.4 0.2 1.5
1.3 1.3 1.3

0.3 0.3 0.3 0.3
0.2

0.2 0.2 0.2
1.1

Age

30-44 45-64 65+ White Black

0.3 0.1 1.1 0.3 0.1
0.3 0.4
1.3 1.4

Race1

Chinese Korean Asian Indian

0.2 0.4

0.7 0.3
2.0

2.3

Index values
1

0-10

11-50

51-100

Includes specified race in combination with other races.

Note: An index less than 100 indicates that 900 out of every 1000 people with this name reported that they were female in Census 2000. Source: U.S. Census Bureau, Test Census of New York, 2004.

First Name Index: Characteristics of Coupled Households
 For couples in the 2004 Test Census:
 Name not reported or not in dictionary • Lowest for opposite-sex unmarried couples • Highest for same-sex couples  Couples with first name indices 990-1000—indicating high agreement between reported sex in 2004 and gender orientation of name • Highest proportion for opposite-sex unmarried couples • Lowest proportion for same-sex couples, especially for male partners and female householders  Couples with first name indices 100 or less—indicating low agreement between reported sex in 2004 and gender orientation of name • About 1% for married couples and opposite-sex unmarried couples • Data suggests that errors in marking sex item may affect 8-16% of male same-sex couples and 10-27% of female same-sex couples.

Percent of People Not Reporting First Name or First Name Not Found in Names Dictionary
Male- Opposite Male -Sex Married Couples Couples Couples
Husband Wife Male Female Householder Partner Householder Partner 9.3 9.9 6.7 6.8 12.2 16.4 11.3 17.9 No report 9.3 4.4 4.8 7.9 8.5 11.1 11.6 5.1 17.3 7.1 20.6 7.7 Not in dictionary 25.6 23.5 17.2 18.4

Source: U.S. Census Bureau, Test Census of New York, 2004

FemaleFemale Couples

Percent of People With First Name Index Over 500
Female- Male- Opposite Female Male -Sex Married Couples Couples Couples Couples
Husband Wife Male Female Householder Partner Householder Partner
7.5 5.6 2.5 2.2 12.5 18.6 12.6 13.9 12.1 37.3 47.3 38.3 48.3 60.9 53 57.5 66.6 73.5 18.2 57.4 60.6 51.2 79.4 77.7

5.1 2.1 4.5 2.3 4.8 1.8 4.7 2.4 3.6 2.0 5.4 4.3 0.5 8.8

86.4 86.0

Index values

501-899

900-949

950-989

990-1000

Note: An index greater than 500 indicates that more than half of the males/females with this name reported they were male/female in Census 2000. Source: U.S. Census Bureau, Test Census of New York, 2004

Percent of People With First Name Index 100 or Less
Female- Male- Opposite Female Male -Sex Married Couples Couples Couples Couples
Husband Wife Male Female Householder Partner Householder Partner
5.9 3.6 0.9* 1.1* 0.8* 1.0* 5.1 1.8 0.8 13.4 18.3 0.9 10.4 7.7 2.4 0.5 16.3 7.7 0.7 26.7

Index values

0-10

11-50

51-100

*Total percent for index values 0-100. Note: An index less than 100 indicates that 900 out of every 1000 males/females with this name reported that they were of a different sex in Census 2000. Source: U.S. Census Bureau, Test Census of New York, 2004.

Using First Names To Edit Sex Responses:
 How willing are you to accept a first name over a sex response?
 The lower the index level of a respondent’s first name, the more frequently that name was associated with the opposite sex • Index 0-10 = 99% of people with that name were of the opposite sex in Census 2000 • Index 0-50 = 95% were of the opposite sex • Index 0-100 = 90% were of the opposite sex  By using different index ranges • Respondents can be reassigned their sex on basis of first names • Different levels of name ―acceptance‖ produce changes in estimates of household types



Who’s sex can change?
 Anyone—reassignment rules apply to all people in all household types  Regardless of sex or living arrangement, anyone can mistakenly mark a form

Estimates of Married and Unmarried Couple Households After Reassigning Sex of Respondent at Different First Name Index Levels
Distribution after sex reassignment at different index levels 0-10 0-50 0-100 60,244 60,244 60,244 54,692 54,537 54,349 4,103 4,092 4,076 1,449 1,615 1,819 831 935 1,043 618 680 776

Household type Total Married couples Opposite-sex couples Same-sex couples Male partners Female partners

Original distribution 60,244 55,026 4,112 1,106 664 442

Note: Sex of respondent in Census 2004 Test was reassigned to opposite sex if their first name index was in this range. Source: U.S. Census Bureau, Test Census of New York, 2004.

Estimates of Same-Sex Couples After Reassigning Sex, by First Name Index Level and Transfer Source
1,819 1,615 1,449 1,106

543 28 541

758 49 515 293 0-50 level

956

664

68 507 288 0-100 level

442 Original distribution

337 0-10 level

Source of same-sex couples:

Female Same-Sex Couples Opposite-Sex Couples

Male Same-Sex Couples Married Couples

Source: U.S. Census Bureau, Test Census of New York, 2004.

Results of Model Simulation
 Overall results for same-sex couple estimates:
 An increase from 1,106 to 1,449 using most conservative index level (0-10)  Increases continue to 1,819 at 0-100 level

 

Less than 1% decline in opposite-sex couples. Married-couples experience greatest loss:
 From 55,026 to 54,349 using 0-100 index level  Although low index levels are reported by a small percentage of married couples • Magnitude of this population produces relatively large additions to the same-sex population



Net increase in same-sex couples to 1,819 at 0-100 level:
 Loss of 311 from original sample  Offset by transfer of 956 married couples and 68 opposite-sex couples

Summary
 First names offer the potential to edit/verify reports of sex on questionnaires. Problems to face if considering this option:
 Not all population groups report names  Geographical/cultural differences in gender of names  Choosing the degree of uncertainty in deciding if a name is ―Male‖ or ―Female‖





Using 2004 Test Census of New York data and Census 2000 names dictionary:
 Objective first name index was developed  Reassignment of sex was made at different levels of acceptance  Model simulation showed losses to same-sex couples greatly offset by gains to this population from married couples



Conclusion: using first names to invalidate reported sex response will yield more same-sex couples than originally reported.

Contact Information
Fertility and Family Statistics Branch Phone: 301-763-2416 • Martin T. O’Connell E-mail: Martin.T.Oconnell@census.gov Gretchen E. Gooding E-mail: Gretchen.E.Gooding@census.gov

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