Presentation is loading. Please wait.

Presentation is loading. Please wait.

1 Kinship and Complexity Advances in Kinship Analysis Douglas R. White October 24, 2008 Kinship Computing & Complexity: Cohesion, Class, and Community.

Similar presentations


Presentation on theme: "1 Kinship and Complexity Advances in Kinship Analysis Douglas R. White October 24, 2008 Kinship Computing & Complexity: Cohesion, Class, and Community."— Presentation transcript:

1 1 Kinship and Complexity Advances in Kinship Analysis Douglas R. White October 24, 2008 Kinship Computing & Complexity: Cohesion, Class, and Community

2 2 0. Outline I Consequences and causes of Structural Endogamy (marriage cycles forming bicomponents) II Constituent elements of Structural Endogamy (census and overlaps of marriage cycles) III Mappings onto Networks and further findings IV Unsolved problems V Conclusions: Tying it all together

3 3 1. Define a graph that represents how marriages form cycles (P-graphs and P-systems)

4 4 Data and Representation: P-graphs link parents (flexible & culturally defined) to offspring They are constructed by showing: Each individual a line Each gender a different type of line Each couple (as) a node A marriage node includes the husband and wife as an embedded graph i.e., a P-system

5 5 2. This representation captures independent nuclear families, networks of marriage between them how families form descent groups marriages within and between them

6 6 3. Now link this representation to actual marriage network data

7 7 Data and Representation: Building Kinship Networks P-graphs link pairs of parents (flexible & culturally defined) to their decedents P-graphs can be constructed from standard genealogical data files (.GED, Tipp), using PAJEK and a number of other programs. See: http://eclectic.ss.uci.edu/~drwhite for guides as to web-site availability with documentation (& multimedia representations)

8 8 4. What are the properties of how marriages form cycles? they form bicomponents = maximal sets of nodes, in which each pair is connected in two or more independent ways

9 9 This is a bicomponent with no cut-point and with two+ independent paths between every node pair. By Menger’s theorem, these are equivalent. It has 8 independent cycles m-n+1 m=24 edges (parent-child) n=17 nodes (couples)

10 10 This is a bicomponent with no cut-point and with two+ independent paths between every node. It’s also ORDERED, by a time dimension, through generations. It has 8 independent cycles m-n+1 m edges n nodes FZDD FZDFZ MZDMBD MMZDD ZDDD Generation 5 And 8 corresponding named cycles WB

11 11 Ancestral generation 1 Generation 2 Generation 3 Generation 4 FZDD FZDFZ MZD MBD MMZDD ZDDD Generation 5 The 8 constituent marriage cycles of the bicomponent (PART II) WB

12 12 Mapping data onto networks Migration Residence Wealth owned Heirship --- PART III Kin Behaviors Kin Terms & Products in relation to marriage By structural endogamy By generation time-series, patrilineages, matrilineages By viri-sides, uxori-sides Analyses of such data can be crossed:

13 13 e.g., Data about kin behavior (III) Kin behaviors mapped by kin type/kin term –Avoidance –Sexual Prohibition –Respect –Informality –Joking –Privileged sexual relation Associated expectations –(additional features for a given society)

14 14 5. Bicomponents (I), as maximal sets of marriages, each pair connected in two independent ways,…... identify the boundaries of structural endogamy (& so - define a new term). This talk will focus on the consequences and causes of these units – part of the implicate order of structural endogamy.

15 15 The idea of consequences is that structurally endogamous units define the local boundaries of one or more implicate order groups that gain cohesion or are the cause of cohesion, such as: religious groups, social class, ethnicities, stayers versus migrants, endo-clans, factions, regions of exchange, etc. The consequences may run from or to structural endogamy as implicated in the actions or activities of those inside or outside the group.

16 16 E.g., Measuring boundaries of structural endogamy Male Descent Female Descent Same person (polygamy) Lot married to his daughters Structurally endogamous Canaanite Marriages in the narrative of the Patriarchs (White/Jorion) Abram Sarai Abram Hagar Ishmael Jacob and Esau are included in the main unit of structural endogamy

17 17 6. This Middle-Eastern Example shows for marriages with relatives by common descent (here, same patrilineage) and membership in a founding religious group (Judiasm). So … by way of contrast:

18 18 7. Apply marriage bicomponents to a European town (here, no blood marriages) How do marriage cycles and structural endogamy have consequences in this case? Relinkings are marriages that reconnect 1 or more families

19 19 with heirship THE NEXT SLIDES WILL TREAT THESE Feistritz, Austria – structural endogamy by affinal relinking

20 20 Feistritz, Austria – structural endogamy by affinal relinking (no blood marriages) 8. There are consequences but not that heirs marry heirs – its THOSE IN THE BICOMPONENT WHO DO RELINK BECOME THE HEIRS Attribute endogamy = e.g., heirs marry heirs Pearson’s R =.15

21 21 Feistritz Austria – structural endogamy 9. This is social class constituted by marital relinking The Time DimensionThe Time Dimension 1970 1520

22 22 Feistritz Austria – structural endogamy by affinal relinking 10. BUT IS IT JUST RANDOM CHOICES THAT CREATE THE MARRIAGE BICOMPONENT IN THIS TOWN? OR IS THIS BEHAVIOR TARGETED AND INTENTIONAL?

23 23 Feistritz Austria – structural endogamy (i.e., bicomponent) with heirship 11. Pearson’s R =.54

24 24 12. Here is a test of randomness as “non-intentional behavior” for each generation For each generation, permute the marriages randomly

25 25 For example, take these three generations and permute the red lines so existing marriage and child positions are occupied

26 26

27 27

28 28

29 29

30 30

31 31 Random in all higher generations 3+ 13. Comparing Feistritz actual to simulated rnd relinking frequencies:- Relinking frequency >> random back 1 and 2 generations, those where there is most knowledge & availability

32 32 14. We look next at Arabized Turkish Nomads, similar in structure to the Canaanites, and show how a similar implicate order of structural endogamy applies to how lineages are linked into clans, and consequences for those who stay and those who leave the clan.

33 33 Turkish nomads Names of members all members Black=patri- Descent lines Blue=female lines

34 34 Turkish nomads SCALING All known members but many have emigrated dotted= female lines Black=patri- descent lines

35 35 Turkish nomads: Relinking only (Structural Endogamy) Stayers in the community ~ cohesive core Relinking +yes no 160 14 Stay 18 71 Leave Pearson’s R =.73 Dotted=female lines Black=patri- Descent lines

36 36 15. Cycles within Structural Endogamy (II) A Turkish Nomadic Clan as prototype of Middle Eastern segmented lineage systems: The Role of Marital Cohesion A power-law decay of marriage frequencies with kinship distance FFZSD FFBSD:10-11 FZD:14 MBD:16 FBD:31 M M =206/x 2 Raw frequency (power law preferential curve) # of Couples # of Types Results: Rather than treat types of marriage one by one: FBD, MBD etc., we treat them as an ensemble and plot their frequency distribution FFZSD FFBSD FZD MBD FBD # of couples # of kin types

37 37 Cycles within Structural Endogamy (II) log-log A Turkish Nomadic Clan as prototype of Middle Eastern segmented lineage systems: The Role of Marital Cohesion types of marriage are ranked here to show that numbers of blood marriages follow a power-law (indexical of self-organizing preferential attachments) while affinal relinking frequencies follow an exponential distribution

38 38 16. We look next at the Omaha, where chiefly elites are stratified and do not relink with other social strata. Their structural endogamy is fragmented early on into factions and decays in later generations.

39 39 Omaha Genealogies – Chiefs and Siblings – no relinking of chiefly lines:- disconnected ELK CLAN

40 40 Omaha – top 4 generations - structural endogamy weak Five disconnected components in the top four generations: sizes 643, 46, 38, 29, 15 Bicomponents of sizes 141, 4

41 41 Omaha – all generations – structural endogamy

42 42 Omaha – 8 generations – disintegration

43 43 Omaha – loss of structural endogamy Omaha Bicomponent relinking marriages Non- relinked singles Total Genera tion Levels 1 early 8 late 12941.40%4158.60%70 25032.90%10267.10%152 36022.60%20577.40%265 43612.70%24887.30%284 5188.70%18891.30%206 6715.60%3884.40%45 7317.60%1482.40%17 814.80%2095.20%21 Relinking marriages decrease in later generations 1234567812345678

44 44 17. The age-bias simulation problem (IV – Unsolved) The current random-simulation of marriage solution assumes that persons in the same structural generation have a uniform age distributions, a biased assumption. But if there are Hu-Wife age differences, then successive WiBr linkages generate younger and younger men in the same structural generation, as seen for the actual Alyawarra case where ages are known, next slide.

45 45 Systemic age differences of wives and husbands compli- cates generational simulation: Alyawarra of Australia G2 G3 G4 G5 G6 G7 G8 G1 G2 G3 G4 G5 G6 G7 Key: Vertical black lines male descent, red dots, females: the generations are sloped (pink and blue) in a P-graph.

46 46 18. Solutions to the simulation problem (Problem here is that “same generation” WiBr chains are not a group of contemporaries but stretched in time) Simulation for Alyawarra and similar examples can be done considering male and females to have different average generational time, α and ß, where Δ= ß-α is the average age preference Δ ± ε for a younger spouse. We can get ß/α ratios without knowing actual ages. Varying α, ß, ε, these parameters define marriage-age probability distributions for simulations where wives can come from different generations. E.g., given section rules for marriage in Australia, different parameter ranges, generate varying distributions of marriage types and configurations of successive and branching WiBr chains.

47 47 Daughters are moving to husbands in groups that are “adjacent” in a flow of directed (asymmetric, “generalized”) exchange. The flow of personnel, however, like a terracing model, also has constrained alternative flows. All these elements allow more generalizable probabilistic modeling.

48 48 That is Inside the structurally endogamous group we have A “random” distribution of simulated types of marriage, constrained by age-bias parameters and section rules and the Compared to the actual distribution of types of marriage And that actual distribution might be a function of the age-biases. An implicate order relation between the macro parameters of the structural endogamy group and its micro patterns of marriage-type frequencies, e.g. MBD, FZD, MMBDD, etc.

49 49 Advances and Benefits Network Visualization of Kinship Variables for testing theory The coherent probabilistic approach that is needed can include not only comparisons against the null hypothesis, as shown, but bootstrap inferential methods for testing complex models of kinship structure, given discrete constraints where they occur (strict Australian section rules, or incest prohibitions).

50 50 V Conclusions: Tying it all together – B ack to II: Constituent Elements of Structural Endogamy Ethnographers characterize marriage systems by “rules” of preferential behavior. This may be sufficient for some societies, E.g., which cousin marriages are favored over others. Networks show a much broader range of marriage behaviors in most cases, e.g., Australia, East Asia, Africa. There are complex distributions of behavioral frequencies – e.g., power laws for blood marriage frequencies (Middle East) or for broad in-law relinking cycles (Europe) – and demographic constraints and factors like relative marriage ages that alter marriage probabilities. A coherent probabilistic approach is both possible and needed. Why is this important? Because structural endogamy and cohesion has huge social consequences that need to be properly understood.

51 51 afterword Local structure -- ranging from marriage- type rules and frequencies to the appearance of nuclear families as autonomous -- may be part of an implicate order of wholeness within structural endogamy. Though not explored, structurally endogamous groups could be part of a larger implicate order.

52 52

53 53 It’s also ORDERED, by a time dimension, through generations. Ancestral generation 1 Generation 2 Generation 3 Generation 4 FZDD FZDFZ MZD MBD MMZDD ZDDD Generation 5 The 8 constituent marriage cycles of the bicomponent (PART II) WB

54 54 Larger view Local structure, ranging from marriage rules to the appearance of nuclear families as autonomous, may be part of an implicate order of wholeness within structural endogamy, and structurally endogamous groups part of a larger implicate order.

55 55 18. Solutions to the simulation problem (Problem here is that “same generation” is not a group of contemporaries but stretched in time) With known ages of marriage data, simulation for Alyawarra and similar examples can be done considering marriages “filled” sequentially in time, 1-by-1, from marriageable-age probability distributions. Where actual ages are unknown, can they be estimated from successive WiBr chains and guesstimates from ethnographers of average Hu-Wife age differences?


Download ppt "1 Kinship and Complexity Advances in Kinship Analysis Douglas R. White October 24, 2008 Kinship Computing & Complexity: Cohesion, Class, and Community."

Similar presentations


Ads by Google