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Mapping Communication from Mingzhou: Networks of Correspondence Hilde De Weerdt University of Oxford Workshop report, “Prosopography of Middle Period China: Using The Chinese Biographical Database,” University of Warwick, December 13-15, 2007

“If an electronic scholarly project can't fail and doesn't produce new ignorance, then it isn't worth a damn.” (John Unsworth)1

1) Introduction 2) Points of Departure 3) Queries 4) Snapshots

a. posts b. associations 5) Extensions 1) Introduction

The title of my presentation reflects the goals and questions I formulated in

anticipation of my use of The Chinese Biographical Database [hereafter CBDB]. A more

appropriate title of this progress report would be “The Problem of Unregistered Mail:

Updating CBDB to Map Correspondence Networks.” Responding to the call of John

Unsworth, who wrote convincingly about the need for reports on failed research among

humanities researchers, I am presenting here a record of the questions and methods that

guided my first foray into the database, a rationale for research on correspondence

networks, a review of the rather unsuccessful results qua content, an examination of the

reasons behind the mixed results, and, finally, reflections on the utility and extensibility

of CBDB in pursuing such work.

1 John Unsworth, “The Importance of Failure,” The Journal of Electronic Publishing 3.2 (1997), http://www.press.umich.edu/jep/03-02/unsworth.html (accessed Aug. 24, 2007).

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2) Points of Departure

The availability of CBDB stimulates the pursuit of new questions in imperial

Chinese history and specifically the employment of new theoretical and methodological

approaches in social and cultural history. The scope of its biographical data, over 30,000

personal names for example, and, even more importantly, the fine granularity of the

information stored in the database make possible multi-factor analyses of social and

cultural developments on both large and small spatial and temporal scales. The typology

of associations drew my attention in particular.2 The wide range of social, political, and

textual relationships the database thereby proposes to track has the potential of effecting

the crosspollination of research on imperial Chinese society and the sociology of social

networks.

The history of social network analysis can be traced back to the 1950s when

sociologists turned to graph theory as one of the mathematical models that fit into the

search for quantitative methodologies. The study of graphs itself goes back to the

mathematician Leonhard Euler (1707-1783) who used graphs to solve a riddle that had

preoccupied the inhabitants of early eighteenth-century Königsberg. In 1736 Euler used a

simple graph consisting of nodes (points) and edges (links between points) to

demonstrate that no single path existed connecting the seven bridges crossing the Pregel

River which cut a small island into the city. Graphs thus demonstrated their potential as

tools that relied on the abstract representation of the connectivity between elements to

answer real-world questions.3

2 The ASSOC_CODES table lists 519 types of association; most of these are part of subject-object association pairs such as “supported” (27) and “supported by” (26). 3 My brief account is based primarily on Mark Newman et al., eds., The Structure and Dynamics of Networks, Chapters One and Two.

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Social network analysis [SNA] developed into a sub-discipline of the social

sciences in the 1970s. The analysis of patterns of social interaction and the study of the

effect of such patterns on individuals, organizations and communities, gained momentum

as advances in computing and graph theory facilitated the analysis of empirical data and

the application of mathematical models in their interpretation. The International Network

for Social Network Analysis, the professional organization of those subscribing to the

methods of SNA established in 1976, still defines the field on the basis of these two

methodological characteristics: 1) the systematic (and computer-assisted) analysis of

empirical data; 2) the theoretical guidance of mathematical models (esp. those derived

from graph theory).4

For historians such characteristics have long been a deterrent. The requirement for

comprehensive data of a high resolution in social network analysis (SNA), as well as

developments internal to the discipline of history such as the turn towards cultural history

at the time when SNA came into its own are the principal reasons behind the low appeal

that SNA has exerted among historians.5 Sociologists, mathematicians, and those deftly

interweaving the social, physical and mathematical sciences, have nevertheless

demonstrated the significance of network analysis in explaining historical phenomena.

For example, in his influential theoretical explanation of the small world phenomenon,

Duncan Watts outlines how the structural and dynamical properties of network types can

help explain how and why epidemic disease has spread or how information was

4 Lin Freeman, “The Study of Social Networks,” http://www.insna.org/INSNA/na_inf.html (accessed Aug. 24, 2007). For a repositioning of SNA within the broader context of anthropological and sociological approaches to networks, see Hannah Knox, et al., “Social Networks and Spatial Relations: Networks as Method, Metaphor and Form,” CRESC Working Paper Series, no. 1, 2005. 5 Cf. Charles Wetherell, “Historical Social Network Analysis,” International Review of Social History 43 (1998), Supplement, 125.

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disseminated.6 The theorizing of networks as dynamical systems in “the new science of

networks” may enhance its explanatory appeal to social historians who tend to be more

interested in how changes in the behaviors and relations among individuals or groups

affect larger groupings rather than in the static structural properties of groups per se.

While the data-driven modeling of social networks has so far not found many

advocates among historians, the same cannot be said for the justification of network

models of social historical explanation as a whole. During the last three decades Charles

Tilly has argued in numerous articles and books that relational analysis is necessary for

explaining a variety of social and political historical phenomena ranging from collective

violence to democratization (and de-democratization), migration, inequality, and the

negotiation of political identities.7 Focusing on contentious politics and social change in

modern history, Tilly calls for mechanism- and process-based explanations and argues

that relational mechanisms (those shaping connections among individuals, groups and

interpersonal networks) are especially salient in accounting for divergent histories of

social and political change across the modern world. Relational explanations diverge

from competing explanations in history and the social sciences which he groups under a

small number of metatheories: 1) dispositional accounts focusing on generalized attitudes

and behaviors of individual or collective actors; 2) systemic theories situating aspects of

social and political life in larger entities consisting of interdependent elements such as

societies, cultures or mentalities; 3) covering law thinking aiming at empirically deduced

6 Watts, Small Worlds, esp. Chapter Six; also Mark Newman et al., eds., The Structure and Dynamics of Networks, Chapter One. 7 For a recent representative articulation of Tilly’s relational model of history, see the collection of essays in Identities, Boundaries, & Social Ties.

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generalizations that fully describe the dependent variables determining events; and, its

opposite, 4) skepticism, disavowing the possibility of generalization.8

In contrast to the first three ontologies of explanation in the social sciences,

mechanism-based explanations have no holistic ambitions. They select historical episodes,

seek to identify categories of events (mechanisms) and combinations of such categories

of events (processes) which have changed relationships among social entities, but deny

that the analysis of mechanisms and processes can abstract laws of social change. While

Tilly gives credit to environmental (those relating to the external settings of social life)

and cognitive mechanisms (those relating to individual and collective perceptions), and

declares the relationship among these and relational mechanisms an open question,9 it is

clear that he gives pride of place to relational explanations: “Categories … do not consist

of mental constructs but of socially negotiated boundaries and changing relations across

those boundaries.”10 Or, “If social construction occurs, it happens socially, and not in

isolated recesses of individual minds.”11

There are some challenges here for historians working on the social, political and

intellectual lives of imperial Chinese elites. Can major transitions in imperial history such

as the reorientation towards local society in the twelfth century, the spread of Neo-

Confucianism, and the economic and cultural rise of the south be explained by or

correlated to changes in social network ties at regional and/or empire-wide scales? Can

outstanding questions such as the level of political organization and the nature of political

8 Ibid., esp. 14-16, 24-29, 103-104. 9 Ibid., 43. 10 Tilly (Identities, Boundaries, & Social Ties, 100) is here describing and endorsing what he calls a relational theory of inequality evidenced in the work of Craig Muldrew (The Economy of Obligations: The Culture of Credit and Social Relations in Early Modern England) and others. 11 Tilly, Identities, Boundaries, & Social Ties, 59.

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participation be answered by systematically investigating and mapping associations

among elites of various kinds? My interests in intellectual history and in the

dissemination of political information led me to a pilot project designed to trigger a larger

investigation into the history of correspondence networks.

Why investigate networks of letter-writing? Mapping the frequency and distance

of correspondence across time will result in findings regarding the connectedness and

centrality of particular places, individuals or groups of individuals. Taking account of the

status (degree-holder, non-degree holder, bureaucratic ranking and actual post) or kinship

relations of individuals in plotting letter writing may result in new findings regarding

patterns of social and political interaction among (groups of) elites. When letters are

differentiated by genre and content, conclusions can be drawn regarding what types of

information spread at what times, to what extent, among whom, and in which directions.

The nature of the plotted networks may also help explain the reach and speed of

particular types of information. Results obtained regarding changes in frequency, distance,

genre and content can also be correlated to known events and developments in the capital

or in the provinces. Networks of correspondence could also be compared to networks

resulting from other types of associations, especially those involving the exchange of

writing, in order to determine the weakness or strength of ties and the role of different

types of associations in the formation of social boundaries. More so than other types of

writing, letters describe personal and direct interactions.

Such expectations about the possibility to do systematic research on

correspondence networks on a macrohistorical scale are based on the knowledge that

imperial Chinese elites included large numbers of letters in their collected works, a

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tradition that can be traced back to the times when individual collections were first

printed in substantial numbers in the eleventh and twelfth centuries and that continued

throughout imperial times. These letters frequently contain information regarding the

addressee, and time or place of writing. The inspiration for such an undertaking came to

me when reviewing the table of association codes. It includes the following types of

association by correspondence (Table 1):

c_assoc_pair c_assoc_desc c_assoc_desc_chn c_type1_desc c_subtype1_desc

280 Corresponded with

(暫時保留,待日後

分入 429, 430, 431, 432) Writings Correspondences

391 Congratulatory note sent to 向 Y 致賀 Writings Social Formalities

390

Congratulatory note received from

從 Y 處收到賀詞 (occasion) Writings Social Formalities

430 Sent letter to 致書 Y Writings Correspondences

429 Received letter from 收到 Y 的書簡 Writings Correspondences

432 Replied to letter from 答 Y 書 Writings Correspondences

431 Received reply from 收到 Y 的答書 Writings Correspondences

434 Sent official letter to 致 Y 啓 Writings Correspondences

433

Received official letter from 收到 Y 的啓 Writings Correspondences

436

Replied to offical letter from 答 Y 啓 Writings Correspondences

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435

Received official reply from 收到 Y 的答啓 Writings Correspondences

Table 1. Correspondence association types from the table of association codes in CBDB.

3) Queries

For the pilot I set out to obtain data on correspondence from and to Mingzhou 明

州 Prefecture (renamed Qingyuan 慶元 in 1195; I will use Mingzhou throughout for the

sake of brevity). Mingzhou, now Ningbo, lay in the southern part of Hangzhou Bay and

was connected by water to the Southern Song capital Lin’an. It became a major center of

domestic commerce during the Song Dynasty and was an important node in the foreign

trade with Korean, Japanese and South East Asian territories.12 Local families and

officials posted to the prefectural and county administrations invested some of the wealth

generated in Mingzhou in educational and other cultural institutions. Consequently,

Mingzhou natives gained unprecedented success in the civil service examinations and

became highly visible at the court and in empire-wide politics.13 As a first test case, Song

Dynasty Mingzhou offers the advantage of relatively ample documentation; its

experience of significant economic and cultural change, and economic and political ties

to a wide variety of places may also result in interesting findings regarding changes in the

networks maintained by local officials and native literati over the course of the Song

Dynasty. This choice was also in part motivated by the larger research efforts devoted to

12 Shiba Yoshinobu 斯波義信, Sōdai Kōnan keizaishi no kenkyū 宋代江南経済史の研究 (rev. ed.; Tōkyō : Kyūko Shoin, 2001), part 2. 13 Cf. Linda Walton, “Education, Social Change, and Neo-Confucianism in Sung-Yuan China: Academies and the Local Elite in Ming Prefecture (Ningpo)” Ph.D. dissertation, (University of Pennsylvania, 1978); Richard Davis, Court and Family in Sung China 960-1279: Bureaucratic Success and Kinship Fortunes for the Shihs of Ming-chou (Durham: Duke University Press, 1986); Lee Sukhee discusses government schools in his ongoing dissertation project (Harvard University) on local government and elite interactions in Mingzhou.

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the history of Ningbo in the international project “Maritime Cross-Cultural Exchange in

East Asia and the Formation of Japanese Traditional Culture: Interdisciplinary Approach

Focusing on Ningbo”14; my report is thus also intended as a contribution to this larger

project.

As a first step towards constructing a correspondence network centered on

Mingzhou during Song times I set out to compile a table of individuals who were resident

in Mingzhou at a given point in time either as natives of the area or as officials posted

there. Several issues presented themselves right from the start. First, users performing

simple queries on the tables should be aware that complete information for higher-level

jurisdictions can only be retrieved if the lower-level ones are also explicitly included in

the query. Thus, in my search for biographical address and post data for Mingzhou, I

included its subordinate counties (Cixi慈溪, Dinghai定海, Fenghua奉化, Changguo昌國

Yin鄞, and Xiangshan象山). In published format, forms can be designed to link highe

lower jurisdictions automatically (or show a list of included jurisdictions, and, better still

allow the user to pick the subordinate jurisdictions they would like to include)

,

r to

,

nd

hen

15 a

thereby avoid oversights by unsuspecting users. Michael Fuller, for example, linked

jurisdictions in the Lookatnetworks form--this is apparent from the results obtained w

selecting Mingzhou from the list shown below in Figure 1. This is a model to be

considered in future search interfaces.

14 For an overview and progress reports, see http://www.l.u-tokyo.ac.jp/maritime/english/index.html (accessed Aug. 25, 2007). 15 The latter suggestion would also allow users to narrow their search temporally or to take into account changes in administrative boundaries to the extent the information contained in the database allows. There are several entries for individual jurisdictions to reflect changes in nomenclature or boundaries.

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Figure 1. Screenshot of LookatNetworks form used to generate networks to the second degree for Mingzhou individuals.

Second, the biographical address codes in their current form and their use in

registering biographical data raise some questions. How are categories such as “actual

residence,” “moved to,” “household registration” and “basic affiliation” used? The latter

is rather vaguely defined as “a single place for indexing purposes” requiring “judgment

based on information in the other fields.”16 In the biographical address data table the vast

majority of entries is assigned the latter code without further indication of the rationale

behind the choice of place. Temporal data for moves are also typically absent. Maybe a

consistent choice (native or registration place) for basic affiliation should be adopted;

other information such as actual residence and work places can be obtained separately.

Third, confusion can arise (and did arise in my experiment) when geographical

information is obtained from both the biographical and post data tables. The geographical

address field goes by the same name in both tables (“c_addr_id”). Even though the values

in both fields use the same address code, the fields represent different information 16 BIOG_ADDR_CODES table, address note for address type 1.

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(residential as opposed to office-related geographical information) and may thus be better

identified separately to avoid the confusion of fields in result tables.

The results of my initial query for individuals living or working in Mingzhou

during Song times are a first indicator of the relative strengths and weaknesses of CBDB

in the version shared with the participants in this symposium. I retrieved 1188 records for

individuals “from” Song Mingzhou17 and 2 records (Table 2) for individuals with

postings in the yamens of the prefecture and its counties.

c_personid c_name c_name_chn c_office_id c_addr_id c_posting_id

37700 Wang Zhiyuan 王致遠 946 12771 4647

37718 Kong Mengdou 孔夢斗 793 12767 4680

Table 2. Results for postings in Mingzhou during the Song period in CBDB. These two records index Wang Zhiyuan’s tenure as county magistrate of Cixi and Kong

Mengdou’s appointment to prefectural vice-magistrate (tongpan) in Qingyuan. Tenure

dates are not listed in the database. The main biographical data table does not list dates

for Wang Zhiyuan and gives the birthyear for Kong Mengdou (1245). I will discuss some

of the reasons behind the relative wealth of persons whose main geographical association

is with Mingzhou and the relative dearth of information on postings in the next section.

Step two in my experiment to construct a Mingzhou correspondence network

based on the CBDB was to query the associations by correspondence of the individuals

listed as working or living there. Using the association types listed in Table 1 above,18 no

17 This number excludes records with Tang and Yuan county addresses. 18 This list does not exhaust the association types that could fall under a broad definition of “correspondence.” Such association types as “sent departure note to” and “received departure note from” could be included (and would yield slightly different results since four records document instances of the exchange of departure notes involving Mingzhou men). I did not incorporate this type in my search criteria since departure notes are in the database broadly defined and cover a variety of genres including poems.

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records registering correspondence among Mingzhou individuals or between Mingzhou

and non-Mingzhou individuals could be found. A sobering result begging for explanation.

4) Snapshots

Extant records contain a wealth of information on postings in Mingzhou and the

collected writings of several Mingzhou men are filled with letters. Why the dearth of

information of this type in CBDB? Are the results described above indicative of larger

problems? In this section I evaluate the coverage of postings and association data in

CBDB.

a. posts

Figure 2 provides a graphic illustration of the lack of specificity for the

geographical location for the majority of post data. In 2270 records a broad temporal

reference (“Song Dynasty”) is inserted where an address code could be expected. Table 3

further shows that in an additional 6693 records out of total of 11374 in the post data

table the location for the post is “unknown.” Figure 3, corresponding to Table 3, shows

the total number of records for the 62 locations for which more than 1 post is included.19

Figure 3 and Table 3 show a marked unevenness in the number of records per location:

only 6 records are listed for Lin’an Prefecture; with 205 records, Guangnan East, on the

periphery, appears better covered than any other circuit. One could attribute the higher

number of incumbents in a peripheral circuit to the kinds of difficulties that typically

render posts there more difficult or less desirable. Clearly, more is at stake here. The

Song Empire consisted of anywhere between roughly 200 and 300 counties and 600 and

1500 prefectures (the lower figures apply to the Southern Song Empire); and posts were 19 There are an additional 90 places for which only 1 post exists in the post data table.

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typically held for no longer than three years. The numbers of posts for each jurisdiction in

the table are clearly deficient; this is not surprising given the high percentage of records

for which no location is entered. The table shows that circuits are used for the

geographical reference of post data. This makes queries at the more commonly used

administrative levels of the prefecture and county futile and best explains why we only

found two records for individuals stationed in Mingzhou.

Figure 2. CBDB post data by location. Address ID # of Records Address 0 6693 unknown 10989 2270 宋朝 10991 31 開封 11026 15 京畿路 11027 7 開封府 11140 92 京東路 11141 2 京東東路 11203 10 京東西路 11212 2 宋州 11287 98 京西路 11294 7 京西南路 11371 6 京西北路 11372 3 河南府 11538 83 河北道 11539 69 河北路 11546 12 河北東路 11703 12 河北西路 11898 148 陝西路 12214 73 河東路 12245 2 晉州

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12344 2 豐州 12432 105 淮南路 12433 45 淮南東路 12572 7 盱貽軍 12587 25 淮南西路 12588 2 廬州 12654 2 無為軍 12668 189 兩浙路 12669 18 浙西路 12671 6 臨安府 12753 17 浙東路 12792 2 台州 12823 21 江南路 12824 100 江南東路 12907 104 江南西路 13014 16 荊湖路 13015 88 荊湖南路 13098 90 荊湖北路 13284 13 益州路 13285 75 成都府路 13425 38 梓州路 13426 19 潼川府路 13576 43 利州路 13700 47 夔州路 13762 2 忠州 13866 5 兩浙西南路 13867 126 福建路 13951 31 廣南路 13952 205 廣南東路 13976 2 韶州 14091 81 廣南西路 18925 4 陝西河北 18927 6 熙河路 18928 2 鄜延路 18929 2 環慶路 18930 2 涇原路 18931 14 秦風路 18933 7 峽路 18934 12 陝西永興 18935 32 四川 18936 10 湖廣

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18937 6 兩浙東北路 Table 3. CBDB post data by location for locations with multiple postings.

Figure 3. CBDB post data by location for locations with multiple postings. The biases in the geographical data for administrative posts derives in part from

the types of offices that are best covered in the database. Figures 4 and 5 suggest that

circuit level positions are recorded in higher numbers than those at the prefectural and

county level. Contrast, for example, the high numbers of circuit intendants (753 fiscal

intendants (zhuanyun shi) and 541 fiscal supervisors (zhuanyun sipanguan)) to the lower

number (868) of prefectural magistrates (zhi mouzhou shi and zhi moufu shi) and county

magistrates (268).

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Figure 4. CBDB post data by type of post.

Figure 5. CBDB post data by type of post, excluding types with fewer than 50 records. The lack of data on those holding positions in Mingzhou and its subordinate

counties is thus part of a more general problem with the nature of the data on

administrative offices and posts included in the current version of CBDB. The relative

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wealth of data on people from Mingzhou results from a comparable unevenness in the

biographical data. In this case we are more fortunate because the Mingzhou counties, Yin

in particular, happen to be among the best covered counties. Figure 6 shows that Yin

ranks third among the jurisdictions with the highest number of individuals included in the

database after Putian (Xinghua, Fujian) and Wu County (Suzhou, Zhe West). For

Fenghua and Cixi as well a relatively high number of individuals is included; the lower

numbers of records for the other counties (Changguo, Dinghai, and Xiangshan) are not

shown on the chart as it excludes those jurisdictions for which fewer than 50 individuals

are registered in the biographical data table.

Figure 6. CBDB biographical address data by location excluding locations with fewer than 50 records.

b. associations

The absence of association by correspondence data for Mingzhou individuals is

not an anomaly in CBDB. Figure 7 shows the total number of records documenting

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association by letter writing by year. If one were to judge by the current data in CBDB,

one would have to conclude that a maximum of 8 letters were sent or received during the

Song Dynasty!

Figure 7. CBDB correspondence association data by year. We can ask further how the paucity of data on the abundant correspondence of

Song literate elites compares to data on other types of association. Figure 8 tabulates the

number of records for different types of association. This shows the most frequently

occurring types of association, as those types for which less than fifty records exist are

excluded.

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Figure 8. CBDB association data by type, excluding types with fewer than 50 records. The table suggests that associations documenting the exchange of biographical writing

(tomb inscriptions (muzhiming) and ritual texts (jiwen)) are recorded in relatively large

numbers; those tracing qualitative human relationships (those not centering on the

exchange of written texts such as friendship, discipleship or recommendation) are also

given extensive coverage. Those like myself interested in associations by prose letter

writing are thus currently at a disadvantage compared to users interested in other types of

association.

Since one of the objectives of the larger project on correspondence networks is to

compare them to networks formed by other types of association, I took the experiment

further and reviewed all association type data for Mingzhou. In this experiment I looked

not only at relationships of the first order (those linking Mingzhou individuals to others

directly) but also at second-order relationships (those removed at a distance of two edges

from Mingzhou individuals). This is intended as a first step towards mapping networks

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that show the extent of the direct as well as indirect connections of Mingzhou individuals.

This experiment was made possible thanks to the nifty Lookatnetworks form designed by

Michael Fuller.

The distribution of the types of Mingzhou associations of the first and second

order is conform to the overall distribution in Figure 8. The exchange of biographical

genres of writing is by far the most frequently documented type of association; friendship

and discipleship also figure prominently (Figure 9). Similarly, preface writing and

personnel administration rank second only to the exchange of biographical texts in

Mingzhou and rank among the top three and top eight overall respectively (Figure 8). The

latter category is somewhat confusing; the Chinese note on personnel administration

indicates that this (ill-defined) type is slated for removal in the future (暫時保留，待刪

除).

Figure 9. CBDB association network data to the second degree, by type, for Mingzhou individuals.

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Given the uncertainty about the extent of coverage for each of these types, it is

difficult to draw any firm conclusions. However, further analysis of the current status of

the data produces some findings that may stimulate and direct further research.

Comparisons of the distribution of association types by degree of separation, by place and

by time result in striking contrasts.

Figures 10A and B contrast the distribution by type for first- and second-order

connections:

Figure 10A. CBDB association network data to the first degree, by type, for Mingzhou individuals.

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Figure 10B. CBDB second-order association network data, by type, for Mingzhou individuals. These figures show that the first-order connections more or less mirror the overall

distribution by type. Second-order connections, those extending from the individuals

separated one degree from Mingzhou individuals, show a rather different distribution.

The messy category of personnel administration becomes the main type of association,

and other political affiliations (such as member of the Yuanyou or Qingyuan coalitions)

emerge from the background. This does not necessarily tell us much about the overall

distribution of the kinds of associations that are maintained in the places inhabited by the

individuals at a second degree of separation from Mingzhou individuals. It does, however,

suggest that already at the second degree court political ties become more significant.

This finding raises such questions as whether similar differences at different degrees of

separation (up to 5) can be found for other jurisdictions, whether differences in

distribution at longer distances correspond to different levels of connectedness among

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local places or at least the elites of these places, and whether such differences are

indicative of the political significance (centrality) of particular places.

Sharp differences in the distribution of ties among localities are evident from the

data on Mingzhou. Figures 11A and B show the overall distribution of first- and second-

order Mingzhou associations by common types and by locality. Figure 11A underscores

the predominance of inhabitants of Yin in Mingzhou associations. The close-up of the

other localities in Figure 11B suggests that Mingzhou inhabitants (mostly from the

counties of Yin, Cixi and Fenghua) maintained first- and second-order ties of various

kinds with only a small number of other jurisdictions, which are all jurisdictions that

attained economic, cultural and/or political prominence during Song times (Luling,

Yongjia, Jinhua, Luoyang).

Figure 11A. CBDB common-type association network data to the second degree, by location, for Mingzhou individuals.

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Figure 11B. Close-up of Figure 11A, excluding Yin County. The further analysis by degree of separation of the Mingzhou connections tabulated

above shows marked differences in the types of direct and indirect ties maintained in

different counties. Figure 12A compares the most common types of first-order ties for

different counties in Mingzhou. It suggests that the literate elite of Cixi and Yin produced

some very prolific writers of biographical texts, whereas Fenghua produced individuals

who were more frequently on the receiving end of textual exchanges. While such

differences within one prefecture may result from the differential survival rates of

collected writings and other texts, they may also relate to socio-economic and cultural

differences among counties and may have direct bearing on the types of higher-order ties

they maintained. Such a conclusion could be tested against findings for different

prefectures.

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Figure 12A. CBDB common-type association network data to the first degree, by Mingzhou counties. Mingzhou individuals maintained first-order connections almost exclusively with other

Mingzhou individuals. Figure 12A suggests that such is the case for the most common

association types; when all other types are added in, this picture does not change. Only

one association (a postface exchange) of the first order involves someone whose primary

affiliation is not with Mingzhou.20 Figure 12B shows that second-order ties connected

Mingzhou individuals to individuals from a wider variety of places. Indeed, second-order

ties almost never involved other Mingzhou individuals—which would reflect an

unusually fragmented (and open) local community, but further data will most likely

modify such a finding. As suggested above, political ties predominated in the majority of

the second-order ties, and a wider variety of ties were only maintained with a small

number of prominent places.

20 Lu You, from Shanyin (Yuezhou, East Zhe), wrote a preface for Wang Cong’s writings. Wang hailed from Yin.

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Figure 12B. CBDB common-type second-order association network data, for Mingzhou individuals. Examining, in addition to degree of separation and place, the timing of particular

types of associations raises further questions about both the CBDB data and Song

Dynasty social networks. Figures 13A-D trace the frequency of the most common types

of association for Mingzhou individuals by ten-year intervals.21 The first two charts in

the series show the frequency of both first- and second-order connections. Both charts

show marked increases in all types of associations in the late twelfth century, especially

those concerning the exchange of written texts. They also show, however, marked

decreases in frequency in the early decades of the thirteenth century. Even though the

exchange of biographical texts appear to fluctuate in sync, Figure 13A shows a mark

contrast between the production of epitaphs and other such exchanges around 1210.

Explanations for or rectifications of these and other patterns in the data await

ed

future work.

21 The vast majority of the association data for Mingzhou individuals include temporal references; a good number (around 1/8) does not include a reliable time reference for the association.

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Figure 13A. CBDB common-type association network data to the second degree, by ten-year interval, for Mingzhou individuals.

Figure 13B. CBDB common-type association network data to the second degree, by ten-year interval, for Mingzhou individuals. Figures 13C-D demonstrate the similarities and differences in the historical trends of

first- and second-order ties in Mingzhou. Figure 13C shows the impact of the first-order

data on the overall trends traced in 13A; Figure 13D, on the other hand, illustrates the

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continued significance of preface writing in the production of ties that bind individuals

across a greater distance.

Figure 13C. CBDB common-type association network data to the first degree, by ten-year interval, for Mingzhou individuals.

Figure 13D. CBDB common-type second-order association network data, by ten-year interval, for Mingzhou individuals.

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5) Extensions

In any project of historical research the initial stages involve locating and

evaluating data. This report extended the evaluation process in part because the results

obtained from the database proved inadequate to answer my initial research question on

correspondence networks from Mingzhou. It also investigated some of the reasons behind

the unevenness of the database search results in the belief that CBDB provides the basic

infrastructure for future network research on imperial Chinese social life. By way of

conclusion, let me offer some suggestions for solutions to some of the issues raised in this

report as well as some desiderata.

First, what data should be acquired through what means? For some variables

sources exist that could dramatically improve current results. As shown above, the

postings table is at this point of very limited use. Entering the data contained in the work

of Li Zhiliang 李之亮which includes postings data at the court, circuit and prefectural

levels for the duration of the Song Dynasty,22 would update and correct the current data

in a comprehensive fashion. It might be useful to compile a list of reference works

covering the Tang through Ming periods which could similarly contribute to the

continued improvement of the data, or introduce new categories of information. Data that

are at this time not registered in the database and that would make a major contribution to

current historical and literary research include individuals’ writings and publications

(both extant and non-extant, tracing time, form and place of publication, and variant

titles). For this type of information both contemporary and modern catalogs can be used

22 Songdai jingchao guan tong kao 宋代京朝官通考 (Chengdu : Ba Shu shu she, 2003), 5 vols.; Songdai lu fen zhangguan tong kao 宋代路分长官通考 (Chengdu : Ba Shu shu she, 2003), 3 vols.; Songdai junshou tong kao 宋代郡守通考(Chengdu : Ba Shu shu she, 2001), 10 vols.

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to perform large-scale uploads, but given the lack of bibliographies that include the vast

amount of title data in the prefaces, postfaces and other prose genres hidden in collected

writings, other models of data acquisition should be considered as well. Expansion in this

area would also open up the database to uses inspired not only by SNA but also by the

cultural sociology and anthropology of networks.

Collaborative structures should be developed that allow for both large-scale

uploads and the integration of smaller datasets. For particular types of data such as

association data which are plentiful and not easily extractable from sources in electronic

or print format, data acquired through case-studies could make a significant contribution

to the gradual reconstruction of networks focused on specific places or individuals.

Someone writing a dissertation on the local history of Mingzhou, for example, might be

amenable, particularly in the early stages of their research, to systematically track

associations relevant to their project and add content-related association fields (e.g.

content of correspondence). The data generated through such projects could be added to a

public master database after review by a panel of area or period specialists.

This leads us into the area of the alteration of data. Users of the current version of

CBDB will all come across erroneous data. While large-scale uploads and reviews may

drastically reduce the amount of erroneous material, broader participation from users will

ensure the continued revision of old and new mistakes or remedy omissions. I propose

that if and when CBDB goes online, its publication will be accompanied by a set of

communication tools allowing for, among other things, the submission of corrections to

area and period editors. Forms can be designed that allow for automated uploading. In

order to avoid automated spam submissions, specialist users can be recruited and given

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passwords to be able to submit corrections. In order to encourage and facilitate use and

participation, the site should feature working papers (with sample projects), a description

of data content, instruction guides, a forum to discuss technical questions, and a

directory of users and data reviewers.

Apart from data acquisition and modification, access is a third consideration

crucial to the future of CBDB. Flexibility is my main concern here. I benefited from

having access to the raw data (even though they came in an Access database) and hope

that if and when the database goes online, the data will remain available for download.

This allows users to experiment with the data, alter and import them in other applications.

Flexibility should equally apply to the design of a Web interface. Users should be able to

search for and filter results according to the variety of criteria that were used in the

experimental projects presented at the workshop. In the case of my experiment that

includes time (years and spans), place (at all levels of the administrative hierarchy), and

type of association. Users should also be able to export results in formats that allow for

their use in GIS and network visualization software. Brief instructions on how to merge

Chinese GIS and CBDB data are in order given their common ancestry.