Grave markers from St. Michael'ss Cemetery in Pensacola, Florida, were studied for evidence of ethnicity and acculturation. The 1,447 grave markers dating from 1870 to 1939 were used to test two hypotheses: 1) the grave markers for ethnic groups represented in the cemetery during the project's time period have identifiable sets of burial attributes; and 2) changes in the visible ethnic attribute sets show evidence of the acculturation of ethnic groups over time. Physical attributes pertaining to grave markers, and personal characteristics (e.g. sex, age) for the individuals inscribed upon the markers were collected for analysis. Historical sources were used to assign ethnicity to each marker by determining the ancestry of the individuals memorialized. Grave marker attributes for ten ethnic groups were examined. The statistical results indicate a correlation of ethnicity with marker attributes. Central Europeans had the most identifiable preferences including large markers, vertical markers, floral design motifs, and headstone molding. Other observable ethnic patterns include the use of family markers, non-marble materials, horizontal markers, relationship wording, and religious symbolism. Spatial analysis illustrates that ethnic markers were dispersed across the cemetery; this lack of segregation in the graveyard may be due to acculturation. However, the diachronic changes in burial identifiers cannot be clearly ascribed to the acculturation of immigrants. Use of marble materials and the height of markers diminished for all ethnic groups. Changes in the memorialization industry were likely contributing factors to differences in attribute selection over time. Therefore, while ethnic burial identifiers are statistically visible in the cemetery landscape, attribute changes are not exclusively caused by acculturation.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-5026 |
| Date | 01 January 2009 |
| Creators | Giroux, Amy |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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