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Person Given Name Mask




Person Given Name Mask

This mask shall generate given names, such as "Anne", "John", "William", etc.

The longest given name is 11 characters.

Every generated name consists of only alphabetic characters. In other words, there are no hyphens or apostrophes.


Select from

At least one of Male or Female checkboxes must be selected.

The Common names only checkbox will select the more commonly used names. If this box is not selected then less frequently used or exotic names shall also be included.

The Weighting fields represent a probability ratio to be used whenever the given name gender must be guessed. This will occur when either:

a) 'Attempt to match original gender' option is not selected; or..

b) 'Attempt to match original gender' option is selected using the 'Guess' parameter AND the actual given name's gender is unisex or unknown.

For example, if the Male Weighting is 1 and the Female Weighting is 2 then the Male:Female ratio shall be 1:2. This is an approximate probability of the gender of the given name that shall be returned by the mask whenever an original name's gender must be guessed.

The valid range of each Weighting value is from 1 to 1,000,000.

Some other weighting examples:

2:5  (2 male names for every 5 female names)

100:96 (100 male names for every 96 female names)

1:1000000 (1 male name for every 1,000,000 female names)

Please note that these weightings are probabilities (approximations) and do not guarantee that the exact ratio of name genders will be generated. 


Case of new names

Specifies the case of the masked values to be generated.

For example, "James" is in Title Case, "JAMES" is in Upper Case and "james" is in Lower Case.

Note:  The case of the original name is not relevant for the selection of the masked name. For example, if the original name is "jane" and the masked value is "Sally", then the masked value for "Jane" and "JANE" shall also be "Sally" (assuming that Deterministic mode masking is used.)


Attempt to match original gender

If this option is selected then FileMasker shall first lookup every name in an attempt to identify its gender and to then generate a masked given name value of the same gender. This is generally reliable, particularly for given names in the United States; however, it is not perfect because a great many given names are used by both genders. Please refer to 'Unisex given names" below.

Any non-alphabetic characters in a name shall be ignored for the purposes of the lookup.

If this option is not selected and both Male and Female names are specified in the 'Select from' panel then the probability of the masked given name gender shall be determined by the Weighting. This applies to both deterministic and random modes.


Replace multiple given names with only first given name

If a field contains more than one name then you can choose to have either an equal number of masked names generated or to have only a single name generated for the first original name.

As an example, consider the original given names in a field are "Adam John".

If this option is not selected then the masked result could be "Fred Billy"; however, if this option is selected then in this example only "Fred" would be the masked result.


Data source information

The given name value are principally based on information returned from the United States census of the year 2000. FileMasker has categorized these names into male, female and unisex. Please refer to the subsection "Unisex given names" below.

The FileMasker Person Given Name Mask returns:

800 of the most popular male given names. If Common Names option is used then only the most popular 329 male names are used. The longest name is 11 characters.

2,000 of the most popular female given names. If Common Names option is used then only the most popular 355 female names are used. The longest name is 11 characters.


Unisex given names

Strictly speaking, there are a great many names that are unisex in the sense that a name is used by both men and women and are recorded as such in a census.

However, using such a simple interpretation would classify an unrealistically high number of unisex names. For example, in the United States census of 2010, 82 of the 100 most common male given names (James, John, Robert, etc) are also recorded as female given names.

Therefore FileMasker categorizes a name as belonging to a gender if the frequency of use by a gender is at least double of the other gender.



If you want the masked results to be the same for each run on the same input, then all settings for this mask must remain the same for each run.

Also note that different names may be generated for the same name if it appears in a different case, unless the 'Ignore case of original string' option in the Determinism tab is selected.






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