6.0124 Report on Textual Criticism Challenge 1991 (1/433)
Elaine Brennan & Allen Renear (EDITORS@BROWNVM.BITNET)
Fri, 10 Jul 1992 09:31:16 EDT
Humanist Discussion Group, Vol. 6, No. 0124. Friday, 10 Jul 1992.
Date: Tue, 7 Jul 92 8:35 BST
Subject: Textual Criticism Challenge 1991: Report
REPORT ON THE TEXTUAL CRITICISM CHALLENGE 1991
Dr Peter Robinson
Research Officer, Computers and Manuscripts Project
Oxford University Computing Services, Oxford UK.
This posting reports the results of attempts at the "Textual
Criticism Challenge 1991", posted by me to various email
boards in July 1991. The challenge, reproduced below, was to
re-create by statistical or numerical means alone the table of
relationships for some 44 manuscripts of the Old Norse
narrative "Svipdagsmal" established by me on the basis of
external evidence and traditional stemmatic methods.
Especially, I report the remarkable results achieved by Dr.
Robert J. O'Hara, an evolutionary biologist at the University of
Wisconsin -- Madison. Dr O'Hara used a technique known as
"cladistic analysis", developed over the last thirty years by
evolutionary biologists for the reconstruction of the
evolutionary history of species from study of their shared
characteristics. Using cladistic analysis, specifically the
computer program PAUP (Phylogenetic Analysis Using
Parsimony) Dr O'Hara was able to reproduce all the major
manuscript groups hypothesized by me. In all cases, the
relationships between individual manuscripts suggested by
PAUP agreed with those known from external evidence.
Most previous attempts at computer-assisted analysis of
manuscript relations have used statistical clustering
techniques. These methods have not been outstandingly
effective. The success of cladistic analysis, based on a quite
different intellectual model, may have considerable
implications for scholars concerned with the exploration of
large manuscript traditions.
The Textual Criticism Challenge 1991: extracts from the
"A textual critic engaged upon his business is not at all like
Newton investigating the motion of the planets; he is much
more like a dog hunting for fleas. If a dog hunted for fleas on
mathematical principles, basing his researches on statistics of
area and population, he would never catch a flea except by
accident." -- A.E. Housman
Housman (and others) believed that statistics and
mathematics have no place in the study of textual traditions,
such as those of Biblical, Classical or Medieval texts. A
scholar's only weapons when trying to determine how an
author's single long-lost original descended into hundreds (
even thousands) of surviving copies are a trained mind and
The Challenge: Prove Housman Wrong
The Old Norse narrative sequence "Svipdagsmal", comprising
two poems "Grougaldr" and "Fjolsvinnsmal" together about
1500 words long, survives in 47 manuscripts known to me.
These manuscripts were written in Iceland, Denmark and
Sweden between 1650 and 1830. Because of this late date
much is known about how these manuscripts are related.
>From this evidence and from database analysis of a complete
computer collation I have made a table of relationships of the
manuscripts, showing how they are divided into groups and
how these groups and the individual manuscripts within
them are descended one from another.
The challenge is this: to construct by Housman's
"mathematical principles" alone, and not using any external
evidence, a table of relationships of the manuscripts (a
"stemma") like that I have already made. Only the raw data
of manuscript agreements and disagreements in individual
readings generated direct from the computer collation may be
used. As far as I know, while attempts at exploring
manuscript traditions have been made using statistical
analysis of small samples of data this will be the first time all
the data for a complete manuscript tradition has been so
analysed. It will also be the first time results of such analysis
can be so thoroughly checked against external evidence.
How Success might Appear
In approximately ascending order of difficulty, a successful
1. Divide the manuscripts into groups reflecting the most
consistent patterns of agreements and disagreements within
the manuscripts. These groups might constitute "genetic
groups": that is, manuscripts presumably related by direct
copying one from another or from a common parent
2. Identify just what readings in what manuscripts are
characteristic of the groups identified in (1) above.
3. Show the groups identified in (1) which are themselves
descended from other groups and identify the groups they
descend from; show the individual manuscripts within the
groups descended from other manuscripts and identify the
manuscripts they descend from.4. Identify particular groups
and manuscripts which contain readings which have not
descended to them by direct copying from their parent
manuscript but by deliberate importation from an alien group
("contamination"). Identify just what readings in what
manuscripts seem to have spread by contamination as well as
by direct copying: compare 2
5. Identify just what readings in what manuscripts appear
distributed at random: that is, readings which have spread by
virtue of the common descent of all these manuscripts from a
single parent manuscript, or readings independently
conceived by different scribes.
I have computer files of every agreement and disagreement
on every reading of 44 of the 47 manuscripts (the other three
are not important), generated direct from my computer
collation of these manuscripts in my doctoral work (see my
articles in *Literary and Linguistic Computing* 4 (1989) 99-
105, 174-81). This data is available in two ASCII files, one
containing all the data for "Grougaldr", the other for
These files are available in two formats. In format A, each
line begins with the variant number, followed by numbers
identifying which mss have this variant and with the
numbers separated by a single space. Thus the line "6 1 2 7"
indicates that variant no 6 occurs only in manuscript
numbers 1 2 and 7. In format B, each line again begins with
the variant number, followed by a space and then a sequence
of 0s and 1s for each of the 44 manuscripts. A "1" indicates the
reading is in the manuscript corresponding to that column of
the table, a "0" indicates it is not. Thus the line
that variant no 6 occurs only in manuscript numbers 1 2 and
7. The two files have about 3500 lines between them. I alone
have the key to the variant and manuscript numbers.
A closing date of 1 December 1991 was set .
Attempts at the challenge
Nine scholars requested the challenge data outlined above.
Three submitted entries. Two of these attempts used varieties
of statistical clustering techniques. One of these, performed
by Dr Daniel Apollon of the University of Bergin using his
own multivariate analysis program Analytica, achieved a
partial separation of the manuscripts into groups
corresponding with those constructed by me. However, while
Dr Apollon's results were impressive in their consistency
with the table of manuscript relations established by me, they
did not define precisely which manuscript, or group of
manuscripts, might be descended from which. Thus,
although Analytica managed to cluster manuscripts known to
be directly related close to one another, in most cases such
manuscripts were clustered within larger groups. One could
not, from the output of Analytica alone, have distinguished
the manuscripts of a clustered group which were actually
closely related from those which merely contained many
similar readings but were not in fact closely related.
The third attempt was that of Dr O'Hara, using the cladistics
program PAUP. In five minutes, using a Macintosh II
computer, PAUP achieved the following:
1. It placed directly adjacent to one another (usually as
descendants from the same node) sixteen manuscripts known
from external evidence to be directly related to one another.
2. It successfully defined the seven manuscript groups
deduced by me within the tradition.
3. It successfully defined two of these groups as
subgroups of another, larger group.
4. It suggested, accurately, that the two largest groups
were each descendants of single manuscripts, and that a third
group also descended from one of these two manuscripts.
5. It provided lists of just what variants were introduced
at what point of the tradition. These agreed reasonably
closely with my own lists of the variants, derived by database
analysis of the collation output, characteristic of particular
groups of manuscripts.
Some of the results achieved by PAUP showed relationships it
had taken me weeks, or months, to discover using other
means. Had I had this analysis at the beginning of my work
with these manuscripts I could have devoted more time to
exploring fine detail of relationships within the established
Fuller discussion of these results, with figures, is available
from me or from Dr O'Hara at the addresses at the bottom of
this document. I have since tested PAUP on the collation
output of some one hundred and seventy manuscripts across
eight different traditions. In each case, PAUP has produced
results consistent with known relations among the
manuscripts (largely reproducing, for example, Manly and
Rickert's analysis of the manuscripts of Chaucer's "Wife of
Bath's Prologue"). It has also, most interestingly, in several
cases pointed to manuscript relations otherwise unsuspected
but which further, traditional, analysis suggested might be
Why Cladistics succeeded
Why did PAUP perform so much better than the better-
known (to manuscript scholars, at least: see the articles of
Griffiths and Holton Pierce; cf Lee 1989) methods of statistical
Cladistic (or phylogenetic) techniques are fundamentally
different, in concept and practice, from statistical clustering
techniques such as those employed by Analytica. Statistical
clustering uses various mathematical means to derive
"measures of distance" from all the data concerning
agreements between manuscripts. It pays no attention to the
type of agreement: especially, it does not attempt to
discriminate agreement in "inherited" or "ancestral"
readings from agreement in "introduced readings", typically
errors. This appears to be the source of the relative failure of
Analytica, referred to above: manuscripts actually genetically
distinct looked similar to it because they happened to share a
large number of ancestral readings. In contrast, fundamental
to cladistic analysis is the identification of ancestral readings
and their elimination from analysis at every point. Thus:
cladistic analysis hypothesizes a tree of descent for the
manuscripts. It then "measures" the tree by spreading all the
data about manuscript agreements across the tree: the shortest
possible tree will be the one involving the fewest variant
changes. When thus measuring each hypothetical tree,
cladistics identifies just what variants are "inherited" at each
node and then rules those out of consideration as it evaluates
This elimination of "ancestral variants" brings cladistics very
close to traditional stemmatic practice (e.g. West, Maas) of
insisting that only "errors", or readings introduced below the
archetype, may define sub-groups of manuscripts. In fact,
cladistics actually elaborates this eliminination of ancestral
readings further than does traditional stemmatics. Whereas
stemmatics only concerns itself with distinguishing readings
in the presumed single archetype from all other introduced
readings (usually defined as errors), cladistics seeks to
identify not just the readings ancestral at the "top" of the tree
but those ancestral at every node within the tree. This has a
remarkable and most powerful consequence. Because
inherited variants are eliminated at *every* node, wherever it
lies in the tree, one does not need to specify beforehand just
what variants are ancestral to the whole tree. The tree is
unrooted: whichever way it is oriented, the ancestral variants
are discounted. Therefore, cladistic analysis offers a way
around the paradox of recension identified by Talbot
Donaldson: that one cannot create a stemma until one knows
what readings are archetypal, but one cannot determine what
readings are archetypal until one has a stemma. One can use
cladistic analysis to create an unrooted tree, deferring
judgement on just what readings are ancestral to the whole
tree until one has this unrooted tree. Then, one can decide
which of the branches of the tree lies closest to the archetype
and root the whole tree at this branch. This was the technique
used by Dr O'Hara with the Svipdagsmal material.
A further reason for the success of cladistics is that it works
explicitly on the tree model. It assumes that a varied group of
objects (whether of manuscripts or of species) is the result of a
sequence of branching descents over time. Cladistics simply
finds the shortest (or most 'parsimonious') tree of descent
which explains the agreements and disagreements within
this group. The overall similarity or dissimilarity of the
objects under study, so important in statistical clustering, is
unimportant in cladistics. Like species, manuscripts may
appear alike but be genetically quite distinct because of their
disagreement on just a few key readings: cladistics
recognizes this explicitly. There are many types of
manuscript analysis (particularly, studies of dialectal,
palaeographic or other scribal phenomena) for which
measures of similarity are appropriate. It may also be
appropriate in those cases where contamination between
manuscripts has so obscured relationship by descent as to
make it impossible to determine genetic affiliation. But such
cases apart (and these may be rather rarer than are supposed
by some critics, e.g. Kane) we have every reason to think that
manuscripts descend from one another just as do species.
Therefore, a tool which seeks to reconstruct the stages of
descent is appropriate: cladistic analysis is such a tool.
The limits of PAUP's analysis; further directions
PAUP's analysis was not without fault. Its greatest difficulties
lie in the areas of contamination and coincident variation.
Cladistics programs effectively ignore this: they assume that
such instances of horizontal transmission will be
outnumbered by instances of vertical transmission. This is
broadly true of the mass of variants in manuscript traditions
too, hence PAUP's general success with the Sv material. But
there are subgroups of variants in subgroups of manuscripts
highly susceptible to horizontal transmission. Thus, there
are a large number of variants found as marginalia in several
groups of Sv manuscripts which appear to have been
borrowed from the text of distinct other groups. PAUP's
failure to recognize this led to some deformation of the
stemma. Thus, one group of manuscripts which had been
heavily contaminated by readings from another group was
incorrectly placed by PAUP too close to that group. There
were similar problems with coincident variation, involving a
series of readings found in four manuscripts: this coincident
variation led PAUP to place these four manuscripts closer to
one another than was warranted.
Evolutionary biologists have been developing cladistics
programs for some twenty years now, and have equipped
them with sophisticated procedures for refining their
analysis. Variants ("characters", in cladistic terminology)
may be weighted; they may be declared as irreversible, or as
necessarily occurring in set sequences. The analysis of the
Svipdagsmal material used none of these facilities, and it is
likely that its results could have been impoved yet further had
they been used.
There is much to be learnt about the use of cladistic
techniques with manuscript traditions. PAUP, the program I
and Dr O'Hara have been using, is a very powerful and
flexible instrument: considerable experiment is necessary to
determine appropriate ways of using it (or other cladistic
programs) in different circumstances. On 1st June Dr O'Hara
and I met in Chicago with David Swofford, PAUP's developer.
We discussed the special difficulties of analysis of manuscript
traditions, especially those arising from contamination. We
agreed to work together to optimize PAUP for use in
stemmatics. I have developed an interface between the
collation program Collate and PAUP: this reads apparatus
output by Collate and formatted in one of the styles to be
recommended in the next draft of the Text Encoding Initiative
and translates it into the standard NEXUS form recognised by
cladistic programmes. A user manual, introducing PAUP for
manuscript scholars, is a desideratum.
The implications of the success of cladistic analysis
PAUP's achievement with the Svipdagsmal material offers
hope that it may now be possible to reconstruct the history of
large and complex manuscript which have hitherto defied
explanation. This has consequences for textual scholars, for
students of language and for historians of culture. For textual
scholars, knowledge of the evolution of a text through its
tradition will change how that text is edited. For students of
language, knowledge of just what manuscripts are related to
one another will facilitate the study of changing linguistic
forms across the tradition. For historians of culture, the
reception of the text may be read in what is written into it as it
Publication of these results
The above is (in part) a summary of a paper written by Dr
O'Hara and myself discussing cladistic techniques and their
application to the Svipdagsmal material. This paper was
presented to the ALLC/ACH conference in Oxford in April
and will be published in "Research in Humanities
Computing '92", edited by Nancy Ide and Susan Hockey
(OUP, Oxford) under the title "Cladistic Analysis of an Old
Norse Manuscript Tradition". Copies of this paper are
available from either myself or Dr O'Hara. A version of this
paper was also presented at the Medieval Academy of
America conference in Kalamazoo in May. I will be giving
an outline of the results of cladistic analysis of the collation of
44 manuscripts of Chaucer's "Wife of Bath's Prologue" at the
New Chaucer Society conference in Seattle in August.
Donaldson, E. Talbot. (1970), "The Psychology of Editors", in
Speaking of Chaucer (London) 102-18.
Griffith, J.G. (1968), "A Taxonomic Study of the Manuscript
Tradition of Juvenal". Museum Helveticum 25:101-38.
Lee, A. (1989), "Numerical Taxonomy Revisited: John
Griffith, Cladistic Analysis and St. Augustine's Quaestiones in
Heptateuchum", Studia Patristica XX.
Kane, G. (1960), Piers Plowman: The A Version (London).
Maas, P. (1958), Textual Criticism (B. Flower, trans.) (Oxford).
O'Hara, R.J. (1988), "Homage to Clio, or, Toward an Historical
Philosophy for Evolutionary Biology", Systematic Zoology 37:
Manly, J.M. and Rickert, E. (1940), The Text of the Canterbury
Pierce, R.H. (1988), "Multivariate Numerical Techniques
Applied to the Study of Manuscript Traditions", in B. Fidjestol
et al (eds.) Tekst Kritisk Teori og Praksis (Oslo) 24-45.
Robinson, P.M.W. (1989), "The Collation and Textual
Criticism of Icelandic Manuscripts", Literary and Linguistic
Computing 4: 99-105, 174-81.
Robinson, P. M. W. (1992). Collate: A Program for Interactive
Collation of Large Textual Traditions, Version 1.1, Computer
Program distributed by the Computers and Manuscripts
Project, Oxford University Computing Services, Oxford.
Sober, E. (1988). Reconstructing the Past: Parsimony,
Evolution, and Inference (Cambridge, Mass.)
Swofford, D. L. (1991) PAUP: Phylogenetic Analysis Using
Parsimony, Macintosh Version 3.0r, Computer program
distributed by the Illinois Natural History Survey,
West, M.L. (1973), Textual Criticism and Editorial Technique
Applicable to Greek and Latin Texts (Stuttgart).
Dr Peter Robinson, Computers and Manuscripts Project,
Oxford University Computing Services, 13 Banbury Road,
Oxford, OX2 6NN, UK.
ph: Oxford (0865) 273200 -- fax: 0865 273275 -- EMAIL:
PETERR@UK.AC.OX.VAX. (@VAX.OX.AC.UK from outside
Dr Robert J. O'Hara, Department of Philosophy, 5185 Helen
C.White Hall, University of Wisconsin -- Madison, Madison,
Wisconsin 53706, USA.
ph: 608 263 3700 -- fax: 608 262 2150 -- EMAIL:
For assistance and discussion we are grateful to A. R. Ives, G.
C. Mayer, K. de Queiroz, E. Sober, D. L. Swofford, J. E. Wills, C.
M. Sperberg-McQueen, P. James, Malcolm Godden and the
HUMANIST electronic discussion group.
The Computers and Manuscripts Project is funded by the
Leverhulme Trust with aid from Apple Computer. Dr O'Hara's
work was supported in part by a Smithsonian Institution
Postdoctoral Fellowship and a U. S. National Science
Foundation Postdoctoral Fellowship (DIR-9103325).