The purpose of this data collection was to provide data on the height of slaves and indentured servants in the colonial and antebellum periods of United States history. Data were taken from newspaper advertisements describing the runaways. Variables include the state in which the advertisement was published, the year of the advertisement, the first and last names of the runaway slave or indentured servant, and his or her race, sex, age, height, place of birth, legal status (whether he or she was a convict or in jail at time of advertisement), profession, and knowledge of the English language.
Original Release Date
2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions.
2006-01-12 All files were removed from dataset 5 and flagged as study-level files, so that they will accompany all downloads.
1992-05-12 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:
- Standardized missing values.
2001-06-05 Part 6, White Male Indentured and Convict Servant Height Measurements, and Part 7, White Male Indentured and Convict Servant Height Descriptors, have been added to this data collection. The codebook was updated with documentation for the new data and is now available as a PDF file. Also, SPSS data definition statements are now available for all data files, and SAS data definition statements are available for Parts 6 and 7 only.
Data in this collection are available only to users at ICPSR member institutions.
This study is provided by ICPSR. ICPSR provides leadership and training in data access, curation, and methods of analysis for a diverse and expanding social science research community.