X-Git-Url: https://git.donarmstrong.com/?p=deb_pkgs%2Fscowl.git;a=blobdiff_plain;f=7.1%2Fr%2Fcensus%2Fnam_meth.txt;fp=7.1%2Fr%2Fcensus%2Fnam_meth.txt;h=0000000000000000000000000000000000000000;hp=d5ca8c65d38bef7d1008075a7db739583d34a1d9;hb=b13ea8a082364672c6de2b010e558211ff52ec9a;hpb=01534a94130c1f5a3a230cf4fe18365a235ba271 diff --git a/7.1/r/census/nam_meth.txt b/7.1/r/census/nam_meth.txt deleted file mode 100644 index d5ca8c6..0000000 --- a/7.1/r/census/nam_meth.txt +++ /dev/null @@ -1,236 +0,0 @@ -10/95 - -DOCUMENTATION AND METHODOLOGY FOR FREQUENTLY OCCURRING NAMES IN THE U.S.--1990 - -The Census Bureau has a primary obligation to protect the -confidentiality of individual responses to the Census. As part -of this confidentiality commitment, the Census Bureau does not -currently release individual census questionnaires (or any other -information that could identify an individual) until 72 years -after a Decennial Census was taken. In 1992, the Census Bureau -released the 1920 Census schedules to National Archives. In -fact, the Census Bureau is so concerned about confidentiality -that name has not been entered into the basic internal electronic data -used to tabulate census results. - -However, there have been numerous demands for sunmary data on the -frequency of surnames for genealogical reasons. Similar interest -has arisen for the frequency of first names by sex. This data -set attempts to satisfy these demands while still providing -utmost confidentiality of individual results. - - -BACKGROUND - -In the summer of 1990, immediately following the 1990 Decennial -Census, the United States Census Bureau conducted a large scale -survey to measure undercount in the 1990 Census. This -independent post Census operation (the 1990 Post-Enumeration -Survey--PES) collected items of demographic data (race, sex, age -and NAME) from 377,000 persons living in 165,000 housing units in -5,300 predefined blocks (or block clusters). - -The information acquired from this independent (PES) operation -was matched against actual 1990 Census records for persons living -in those same 5300 blocks plus additional surrounding ring -blocks. The PES blocks plus the surrounding ring--"the Search -Area"--contained 7.2 million census records replete with name. -It is this Search Area data set that provides the impetus for the -three name files at this internet site. - -FILE FORMATS - -In July 1995, the Census Bureau placed abridged summary -information from the Search Area on its internet site. Selected -data from these files have appeared in the print media with the -citation "source--Census Bureau". Since the documentation -accompanying the original release of this information was -sketchy, we are supplying additional explanatory material about -the limitations of these data. - - -Each of the three files, (dist.all.last), (dist. male.first), and -(dist female.first) contain four items of data. The four items -are: - - (1). A "Name" - (2). Frequency in percent - (3). Cumulative Frequency in percent - (4). Rank - -In the file (dist.all.last) one entry appears as: - - MOORE 0.312 5.312 9 - -In our Search Area sample, MOORE ranks 9th in terms of frequency. -5.312 percent of the sample population is covered by MOORE and -the 8 names occurring more frequently than MOORE. The surname, -MOORE, is possessed by 0.312 percent of our population sample. - - -EDITING - -Producing that summary line for the name MOORE required a great -deal of program editing. For example, we immediately realized -that it was necessary to convert the entries MOORE JR, MOORE SR, -and MOORE III in the last name field to MOORE. For purposes of -consistency we also converted entries such as MOORE JONES or -MOORE-JONES to MOORE. - -In addition to those rather simplistic edits, we also examined -each name entry for the possibility of an inversion. (eg: a first -name appearing in the last name field and a last name placed in -the first name area). Consider a 2 person household with the -entries MOORE ROBERT, and MOORE CAROLYN in the name fields. -From our sample name universe, we can empirically determine the -probability that the inversion (ROBERT MOORE and CAROLYN -MOORE) as a far greater probability of being "right" than the -keyed entry. When the probability that the odds of an inversion -attained odds of 10,000 to 1, the inversion was done. - -Many names can be inverted and sound absolutely right. For -example, there is absolutely no reason to suspect that HENRY -THOMAS is wrong and THOMAS HENRY is preferable. However, if -HENRY THOMAS had a spouse listed as HENRY MARTHA and a female -child named HENRY SUSAN, that additional information suffices -to invert the name field for the entire family. - -For first names, we considered concatenating entries but finally -decided against it. Among males the combinations JOHN PAUL and -JOSE LUIS in the first name field were far more frequent than any -other set of spaced names. We could possibly have formed them as -JOHNPAUL and JOSELUIS. As a result the male first names JOHN and -JOSE may be marginally overstated. - -The one name that is most affected by our decision not to -concatenate is the grand old name of MARY. The entries (MARY -ANN, MARY BETH, MARY CATHERINE, MARY ELLEN, MARY FRANCES, MARY -GRACE etc) wind up as MARY. MARY may or may be the most common -first name among American women, but our decision to avoid -concatenation did add a significant number of MARY's. - -Finally, we came to the conclusion that the existence of a single -letter (an initial perhaps?) appearing in either the first or -last name field would not qualify as a name; but an initial in -one field would not disqualify the other name field. For example -the 19th century financier (J P MORGAN) has a valid last -name but the letter J does not meet these standards for a first -name. MUHAMMED X is an example of a acceptable first name -with an unusable surname. - - -MISSING DATA - -Although the search area contains 7.2 million persons, almost 15 -percent of those persons do not provide enough information to -form a name. In the previous paragraph we provided the situation -where we decided that a single a single letter would not -constitute a name. Other situation are listed below. - - - 1. The respondents did not enter a "name" at the top of page -2 of the 1990 Census form, even though names might have appeared -on the roster of page 1. A name must appear at the top of page 2 -for the name to be keyed. - - 2. The respondent may have inadvertently left sex (gender) -off his or her Census record. In that instance we accept the -last name, but we have no "certain" way of placing the first name -in the male or the female file. We do not assume that JENNIFER -without a sex designator would be female even though common sense -suggests that this is indeed the case. - - 3. A family may have put down a last name for the -householder but not for any other household member. We may have -the following family JOHN SMITH, MARY (blank), JOHN JR -(blank), ROBERT (blank), JENNIFER (blank), SUSAN -(blank). In that family we have a first and last name for -householder John, but first names only for the remaining 5 family -members. - - 4. The keyed name may not follow acceptable form. Some -examples of invalid entries in either the first or last name -field are: BABY GIRL, MR JONES, DR BROWN, FILIPINO -FEMALE. - -Each of these situations are responsible for limiting our -original sample of 7.2 million person records down to its present -size of 6.3 million. The actual number of person records making -up the unabridged files are: - - File Name Valid Records Unique Names - - 1. dist.all.last 6.290,251 88,799 - 2. dist.female.first 3,184,399 4,275 - 3. dist.male.first. 3,003,954 1.219 - -For purposes of both confidentiality and elimination of data -noise we restricted the number of unique names available at this -internet site to the minimum number of entries that contain 90 -percent of the population in that data file. There is an -extremely small chance that an individual with a truly "unique" -name could have been captured in sample, and is far more likely -for surnames than for first names. A second basis for limiting -entries is that a smattering of entries exist because of the -combination of bad handwriting coupled with poor typing. -Consider the entry JOSEHP in dist.male.first. Although JOSEHP -may be a name, it is much more likely that all of the JOSEHP -entries are really miskeys of JOSEPH. - - -LIMITATIONS - -For the names at the top of the distribution, (SMITH, JOHNSON, -WILLIAMS, JONES etc), or (MARY, PATRICIA, LINDA, BARBARA etc) or -(JAMES. JOHN, ROBERT, MICHAEL etc) the data speaks for -themselves. However as the sample thins, one might draw -conclusions about frequency that are not warranted. - -The PES sample intentionally over sampled both Blacks and -Hispanics, and it is likely that the Search Area also contains an -excess of these two groups. Thus the frequently occurring -surnames: GARCIA, RODRIGUEZ, GOMEZ and WASHINGTON as well as -first names: JUAN, JOSE, GUADALUPE and WILLIE might attain higher -rankings than their actual population numbers within the United -States would warrant. - -But the limitations due to sampling are much more noticeable when -looking at rarely occurring names--especially surnames. Consider -a surname appearing 63 (out of 6.3 million entries) times in the -file dist.all.last. Here the frequency would appear as 0.001 -percent, but it is possible that that sample frequency may not be -close to "truth". - -Ignoring clustering, (persons in the same household usually have -the same surname) the coefficient of variation on a number of -that magnitude would be approximately 12 percent. But most -people who do not live alone share a last name with other people -in that household. Thus the 63 persons with that rare name may -be the result of 16 households, which would raise the coefficient -of variation to approximately 25 percent. - -But we are not done. Even in the last years of the 20th century, -families tend to live close to each other, and it is not -impossible to conceive a situation where all Americans with a -certain surname appear in sample. Were that situation to occur -it would be possible to overstate the frequency of that surname -name by a factor of 40. The number 40 arises because the number -of Census records in the sample (6,290,251) is approximately one -fortieth of the United States population. - -The fact that a name doesn't appear in these three files does not -mean that it is non existent, only that it is reasonably rare. - -In conclusion we do realize that misleading frequencies are much -less likely in the files (dist.female first) and -(dist.male.first). Although fathers and one son may share a -first name, brothers almost never share the same first name. - - -ADDITIONAL INFORMATION - -Persons wanting or needing more information about the contents of -these three files can contact David L. Word (dword@census.gov) -301-457-2103 or Randy M. Klear (rklear@census.gov) 301-457-1727. - -