Table 1
Wealth measures and their units used in this study.
| WEALTH PARAMETER | MEASURE UNIT |
|---|---|
| Total Object Types (TOT) | represented number of grave good categories |
| Manufacturing time | person-hours (PH) |
| Skill (5 main levels based on years training) | percentage (0.0, 0.4, 2.0, 5.0, 10.0) of person-hours |
| Import value (‘travel’) | travel hours (with 7 km/h) to raw material |
| Scarcity | total number of graves/number of graves with X material |
| Prestige | median of TOT range for each grave good category |
| Estimated meat (from MNI of animal bones) | kg + separate scarcity and prestige bonus |
| Grave depth | cm |
Figure 1
Left: Map of CWC sites in the study region from Šebela 1999 and Kolář 2011. Sites with skeletal remains (black) and sites without skeletal remains, not included in the analysis (white). Right: raw material source data (see larger map with literature and legend in Supplementary Information 3.2, and the raw geodata on https://github.com/mnortoft/QuantWealth) with the study area marked (black square). Maps made in QGIS by the author.
Figure 2
Simplified graph of automated person-hours system. Each material around the centre represents one or several R scripts calculating person-hours depending on their respective chaînes opératoires. Drawn in MindMaple by the author.
Figure 3
Percentage distribution of age groups (79 individuals, left), and sex or gender determination within each age group (69 individuals, right).
Figure 4
Association of each grave good type with TOT. The medians of each category are used as values in the prestige measure.
Figure 5
Biplots from a PCA of manufacturing time, skill, scarcity, travel-hours, prestige, and estimated meat consumption, as well as materials, and individuals. Juvenis and adultus correlate negatively with each other on PC2.
Figure 6
Top: Scree plot showing contribution of all PCs, bottom left, middle and right: scree plots of PCs 1, 2, and 3 respectively.
Table 2
Graves with and without meat (animal bones) vs. age groups, and percentage of graves with meat.
| adultus | infans | juvenis | maturus | |
|---|---|---|---|---|
| With meat | 2 | 5 | 3 | 7 |
| Without meat | 31 | 11 | 4 | 16 |
| With meat % | 6.06 | 31.2 | 42.9 | 30.4 |
Figure 7
Comparison of drop in TOT Gini indices for every addition to the TOT distribution using the highest TOT value as starting point, applied to Moravia (left, TOT 0–10) and Vliněves (right, TOT 0–5). The drops in Gini with the least added TOT is set at a threshold of 5 percent.
Figure 8
Lorenz curves and Gini indices for TOT without correction (left), and with correction (right) for both Vlineves (Vli, red solid curve) and Moravia (Mor, blue dotted curve).
Figure 9
Square root of densities of manufacturing time, skill, scarcity, travel-hours, prestige, and estimated meat consumption.
Table 3
Summaries of the data foundation of the Gini coefficients.
| MIN. | 1ST QU. | MEDIAN | MEAN | 3RD QU. | MAX. | |
|---|---|---|---|---|---|---|
| Total Object Types | 0 | 1 | 3 | 2.93 | 4 | 10 |
| Person-hours | 0 | 4.67 | 19.2 | 48.2 | 34.3 | 1,710 |
| Scarcity | 0 | 1.1 | 4.92 | 10.8 | 11.4 | 164 |
| Skill bonus | 0 | 1.62 | 10.7 | 25 | 26.1 | 509 |
| Travel hours | 0 | 0 | 0 | 14.3 | 20.2 | 186 |
| Prestige | 0 | 3.5 | 8.75 | 11.5 | 15.9 | 47.5 |
| Animal meat | 0 | 0 | 0 | 27.6 | 0 | 397 |
| Grave good normalized sum (0–6) | 0 | 0.12 | 0.31 | 0.53 | 0.74 | 3.5 |
| Grave depth | 2 | 27.5 | 55 | 61.4 | 78.2 | 250 |
Table 4
Gini coefficients based on (corrected) TOT, Grave Depth, and combined grave good value.
| GINI | gini | lwr.ci | upr.ci |
|---|---|---|---|
| Adjusted TOT | 0.368 | 0.34 | 0.407 |
| Grave depth | 0.393 | 0.362 | 0.427 |
| Combined grave good value | 0.559 | 0.52 | 0.615 |
Figure 10
Lorenz curves and Gini indices for Moravian CWC: (normalized sum) of combined grave good value, Ginis for Total Object Types (TOT), Grave depth, and scarcity to compare with the scarcity Gini of 0.69 for Lauda-Königshofen CWC by Grossmann 2021. TOT Gini is the adjusted version.