Views of New Testament Textual Space

Timothy J. Finney

Research Fellow, Vose Seminary

Table of Contents

1. Introduction

2. Sources

3. Analysis Results

4. Discussion

4.1. Gospels
4.2. Acts and General Letters
4.3. Paul's Letters and Hebrews
4.4. Revelation

5. What Difference Does It Make?

6. Acknowledgments

Bibliography

1. Introduction

Various views of the New Testament textual tradition can be produced by multivariate analysis of data which describes variation among surviving New Testament witnesses.^[1]

There are many witnesses to the text of the New Testament. Originally written in Greek, the New Testament was copied by hand for almost fifteen centuries until the advent of mechanized printing provided an alternative means of propagation. As with any hand-copied tradition, variations have crept into the text. One task of students of the New Testament is to establish the initial text which stands behind the range of texts found among surviving witnesses.^[2] A place where the texts of extant witnesses differ is called a variation unit, each alternative text at a variation unit is called a reading, and a list of witnesses that supports a reading is called its attestation.

The most important witnesses for establishing the initial text fall into these categories:

Greek manuscripts
ancient versions
patristic citations.

Ancient versions are early translations of the Greek text into languages such as Latin, Syriac, and Coptic. Patristic citations are most commonly Greek or Latin but can be in other languages such as Syriac. In cases where a witness is written in a language besides Greek, it is often possible to establish which Greek reading is supported through back-translation.

Given such a great cloud of witnesses it can be difficult to see where they stand in relation to one another. This study uses multivariate analysis to explore the textual landscape. As a preliminary step, a distance matrix is constructed which tabulates the simple matching distance between every possible pair for the set of witnesses under examination. The simple matching distance between two witnesses is the proportion of disagreements between them in those variation units where the readings of both are defined. Being a ratio of two pure numbers, this quantity is dimensionless (i.e. has no unit). It varies from a value of zero for complete agreement to a value of one for no agreement between the two witnesses.^[3] The reading of a witness is not defined when it cannot be discerned, perhaps because a manuscript is physically damaged, its ink faded, or its writing obscured in some other way. In the case of a versions, a reading is not defined unless a back-translation concurs with only one of the Greek alternatives. A pair of witnesses only qualifies for inclusion in a distance matrix if both members of the pair share a minimum number of variation units at which the readings of both are defined. This minimum requirement is intended to reduce sampling errors to a tolerable level. In the analysis performed here, the minimum required number is usually set at fifteen.^[4]

A wide variety of multivariate analysis techniques are available to explore relationships between the objects whose distances from each other are tabulated in a distance matrix. The results of only three techniques are presented here, namely classical multidimensional scaling (CMDS), divisive clustering (DC), and partitioning around medoids (PAM).^[5] While every technique has its own merits and potential weaknesses, these serve to introduce results obtained when exploratory multivariate analysis is applied to distance information derived from New Testament witnesses. All of the statistical analysis in this study is performed using the R Language and Environment for Statistical Computing. The relevant programs are available here.

Classical multidimensional scaling finds the set of object coordinates which best reproduces the actual distances between objects in the distance matrix. A plot of these coordinates shows how the objects are disposed with respect to one another when all distances are considered. This study refers to such a plot as a map and uses the term textual space for the space obtained when the objects are textual witnesses. Achieving a perfect spatial representation of a distance matrix may require any number of dimensions up to one less than the number of objects. This presents a problem when a large number of objects is being examined because our spatial perception is three-dimensional. Fortunately, three dimensions is often sufficient to achieve a reasonable approximation to the actual situation. The CMDS analysis produces a coefficient called the proportion of variance which is the proportion of distance matrix information explained (i.e. accounted for) by a map. This coefficient ranges from a value of zero to one, with a value of one indicating that the map is a perfect representation of the actual distances.

Divisive clustering begins with a single cluster and ends with individual objects. The program documentation describes the clustering algorithm as follows:^[6]

At each stage, the cluster with the largest diameter is selected. (The diameter of a cluster is the largest dissimilarity between any two of its observations.) To divide the selected cluster, the algorithm first looks for its most disparate observation (i.e., which has the largest average dissimilarity to the other observations of the selected cluster). This observation initiates the "splinter group". In subsequent steps, the algorithm reassigns observations that are closer to the "splinter group" than to the "old party". The result is a division of the selected cluster into two new clusters.

DC analysis produces a dendrogram which shows the “heights” at which clusters divide into sub-clusters. A divisive coefficient which measures the amount of clustering structure is presented as well. This coefficient ranges from a value of zero to one; the larger the value, the greater the degree of clustering. It should be emphasized that a DC dendrogram is not a genealogical tree of the type produced by phylogenetic analysis. Instead, it merely shows a reasonable way to progressively subdivide an all-encompassing cluster until every sub-cluster is comprised of a single object.^[7]

Partitioning around medoids builds clusters around representative objects called medoids. The program documentation provides this description:^[8]

The ‘pam’-algorithm is based on the search for ‘k’ representative objects or medoids among the observations of the dataset. These observations should represent the structure of the data. After finding a set of ‘k’ medoids, ‘k’ clusters are constructed by assigning each observation to the nearest medoid. The goal is to find ‘k’ representative objects which minimize the sum of the dissimilarities of the observations to their closest representative object.

PAM analysis produces a statistic called the mean silhouette width (MSW) which indicates how many clusters a data set contains.

2. Sources

Data which has been extracted from the following sources forms the basis of the analysis results presented in this study:

CB: Tables compiled by Richard Mallett using two volumes: (1) Comfort's New Testament Text and Translation Commentary; (2) Comfort and Barrett's Text of the Earliest New Testament Greek Manuscripts.
Cunningham: Tables extracted from Arthur Cunningham's PhD dissertation, “The New Testament Text of St. Cyril of Alexandria.”
EFH: A table compiled from data originally collected by Bart D. Ehrman, Gordon D. Fee, and Michael W. Holmes for their Text of the Fourth Gospel in the Writings of Origen. Bruce Morrill did the statistical analysis presented in that volume. Jared W. Anderson made the data available in his ThM thesis, “Analysis of the Fourth Gospel in the Writings of Origen.”^[9]
INTF-General: A database constructed by the Institute for New Testament Textual Research (INTF) to record textual information relating to their Editio Critica Maior (ECM) and Coherence-Based Genealogical Method (CBGM). The database covers the General Letters (James, 1-2 Peter, 1-3 John, and Jude), recording pair-wise numbers of agreements and variation units for a broad selection of Greek New Testament manuscripts.
INTF-Parallel: Tables derived from the apparatus of Strutwolf and Wachtel (eds.), Novum Testamentum Graecum: Editio Critica Maior: Parallel Pericopes. An R script was used to construct the tables from an electronic version of the apparatus generously made available by the INTF at this address: http://intf.uni-muenster.de/PPApparatus/.
UBS2: Tables compiled by Maurice A. Robinson using the apparatus of the second edition of the United Bible Societies' Greek New Testament. (See his “Determination of Textual Relationships” and “Textual Interrelationships.”) Maurice Robinson kindly arranged for his assistants Claire Hilliard and Kay Smith to prepare electronic versions of his tables of percentage agreement.
UBS4: Tables compiled from the apparatus of the fourth edition of the United Bible Societies' Greek New Testament. Richard Mallett constructed the tables for Mark, 2 Corinthians, and Revelation. A substantial part of the table for Matthew was encoded by Mark Spitsbergen. (Only the first fourteen chapters of Matthew are presently covered.)^[10]

If possible, the source has been used to construct a data matrix which encodes the readings of those witnesses included in an apparatus for the variation units which are covered. Where defined, the reading of a witness at a variation unit is encoded either as a numeral or letter. The numeral or letter is determined by the position of the reading in the relevant variation unit; for example, the first reading may be encoded as 1 or a. The code NA (for not available) is used at variation units where the reading of a witness is not well defined.

The analysis techniques employed in this study operate on a distance matrix, not a data matrix. In cases where it is possible to construct a data matrix from the source data (e.g. UBS4), the corresponding distance matrix is constructed by calculating the simple matching distance between every possible pair of witnesses. In other cases, the distance matrix is constructed from a table of percentage agreements (e.g. Maurice Robinson's tables) or from a table which records the number of agreements and number of variation units where both witnesses of a pair are defined (e.g. INTF General Letters data).

Some sources represent manuscripts by Gregory-Aland numbers (e.g. 01, 02, 03, 044) while others use letters or latinized forms (e.g. Aleph, A, B, Psi). These symbols carry through to the analysis results. Abbreviations UBS, WH, and TR stand for the texts of the United Bible Societies' Greek New Testament (4th ed.), Westcott and Hort's New Testament in the Original Greek, and the Textus Receptus, respectively. In INTF data, ECM or A (for Ausgangstext or initial text) represents the text of the Editio Critica Maior. The A for Ausgangstext in INTF data sets should not be confused with the A used to represent Codex Alexandrinus in other data sets. Maj, Byz, and Lect stand for majority, Byzantine, and lectionary group texts, respectively. The relevant printed editions should be consulted for explanations of what these group symbols represent.

3. Analysis Results

The following table presents data matrices, distance matrices, classical multidimensional scaling results, and divisive clustering results for every data source mentioned above. A data matrix is only provided if it is possible to construct one from the source. A Greek MSS data matrix covers Greek manuscripts alone while an aggregate one includes versional and patristic citations as well. Lack of a data matrix is indicated by NA for not available. Three decimal places are used for distances regardless of whether this level of precision is warranted. Data and distance matrices are formatted as comma-separated vector (CSV) files. They can be downloaded and imported into a spreadsheet program for inspection.

Table 1. Data matrices, distance matrices, CMDS maps, and DC dendrograms
Book or Division	Source	Coverage	Matrices		CMDS		DC
Book or Division	Source	Coverage	Data	Distance	Map	Coeff.	Tree	Coeff.
Matthew	CB	Aggregate	→	→	→	0.73	→	0.69
	CB	Greek MSS	→	→	→	0.75	→	0.54
	INTF-Parallel	Greek MSS	→	→	→	0.28	→	0.80
	UBS2	Aggregate	NA	→	→	0.35	→	0.70
	UBS2	Greek MSS	NA	→	→	0.52	→	0.77
	UBS4	Aggregate	→	→	→	0.53	→	0.73
	UBS4	Greek MSS	→	→	→	0.61	→	0.72
Mark	CB	Aggregate	→	→	→	0.76	→	0.74
	CB	Greek MSS	→	→	→	0.74	→	0.59
	INTF-Parallel	Greek MSS	→	→	→	0.33	→	0.80
	UBS2	Aggregate	NA	→	→	0.42	→	0.69
	UBS2	Greek MSS	NA	→	→	0.59	→	0.74
	UBS4	Aggregate	→	→	→	0.52	→	0.74
	UBS4	Greek MSS	→	→	→	0.59	→	0.74
Luke	CB	Aggregate	→	→	→	0.75	→	0.77
	CB	Greek MSS	→	→	→	0.81	→	0.68
	INTF-Parallel	Greek MSS	→	→	→	0.27	→	0.81
	UBS2	Aggregate	NA	→	→	0.38	→	0.71
	UBS2	Greek MSS	NA	→	→	0.55	→	0.73
John	CB	Aggregate	→	→	→	0.72	→	0.67
	CB	Greek MSS	→	→	→	0.72	→	0.62
	Cunningham	Aggregate	NA	→	→	0.54	→	0.67
	EFH	Aggregate	→	→	→	0.61	→	0.64
	INTF-Parallel	Greek MSS	→	→	→	0.34	→	0.84
	UBS2	Aggregate	NA	→	→	0.36	→	0.68
	UBS2	Greek MSS	NA	→	→	0.49	→	0.75
Acts	UBS2	Aggregate	NA	→	→	0.41	→	0.71
Acts	UBS2	Greek MSS	NA	→	→	0.58	→	0.74
James	INTF-General	Greek MSS	NA	→	→	0.35	→	0.83
1 Peter	INTF-General	Greek MSS	NA	→	→	0.35	→	0.78
	UBS4	Aggregate	→	→	→	0.45	→	0.72
	UBS4	Greek MSS	→	→	→	0.54	→	0.72
2 Peter	INTF-General	Greek MSS	NA	→	→	0.36	→	0.79
1 John	INTF-General	Greek MSS	NA	→	→	0.33	→	0.74
	UBS4	Aggregate	→	→	→	0.42	→	0.72
	UBS4	Greek MSS	→	→	→	0.53	→	0.76
2 John	INTF-General	Greek MSS	NA	→	→	0.32	→	0.80
3 John	INTF-General	Greek MSS	NA	→	→	0.35	→	0.84
Jude	INTF-General	Greek MSS	NA	→	→	0.32	→	0.81
Paul's Letters	Cunningham	Aggregate	NA	→	→	0.70	→	0.71
2 Corinthians	UBS4	Aggregate	→	→	→	0.44	→	0.75
2 Corinthians	UBS4	Greek MSS	→	→	→	0.55	→	0.74
Hebrews	UBS4	Aggregate	→	→	→	0.39	→	0.76
Hebrews	UBS4	Greek MSS	→	→	→	0.53	→	0.76
Revelation	UBS4	Aggregate	→	→	→	0.41	→	0.61
Revelation	UBS4	Greek MSS	→	→	→	0.60	→	0.62

As mentioned before, PAM analysis produces a statistic called the mean silhouette width (MSW) which indicates how many clusters are contained in a data set. The following table gives profiles of the MSW versus the number of clusters for some of the distance matrices found above. In general, PAM analysis has only been applied to the most comprehensive data sets for each book. However, more than one MSW profile may be given per book or division, especially if the most comprehensive data set does not include patristic and versional citations. Local maxima in a profile indicate preferred numbers of clusters for partitioning the corresponding data set. The table includes the numbers of clusters corresponding to the first two local maxima of a profile.

Table 2. MSW versus number of clusters
Book or Division	Source	Coverage	Profile	Preferred numbers
Matthew	INTF-Parallel	Greek MSS	→	2, 11
Matthew	UBS2	Aggregate	→	2, 6
More to follow...

Partitions corresponding to preferred numbers will go here.

4. Discussion

	Note
	This section is just me thinking aloud. Hopefully it will not be too long before I can do it properly.

Applying multivariate analysis to New Testament textual data reveals apparent structure in relationships among witnesses. The modes of analysis are new to the field of biblical textual research and a new vocabulary is required to describe the results produced.

Eldon J. Epp uses the analogy of a galaxy to describe text-types:

A text-type is not a closely concentrated entity with rigid boundaries, but is more like a galaxy — with a compact nucleus and additional but less closely related members which range out from the nucleus toward the perimeter. An obvious problem is how to determine when the outer limits of those more remote, accompanying members have been reached for one text-type and where the next begins.^[11]

This image seems especially apt for describing the textual space revealed by CMDS maps derived from New Testament textual data. Taking Epp's lead, a local maximum in the density of objects within a CMDS map might be called a nucleus, although cluster, pole, or focus might also be used for the same thing. (The term text-type will not be used.) Regions between poles where there is a higher than usual concentration of witnesses might be called a stream or corridor. A line pointing in a particular direction can be called a trajectory. Thus, a witness located between two others might be described as lying on a trajectory between them.

The vocabulary of tree structures will be employed to discuss DC dendrograms: a branching point is called a node, each structure which descends from a node is called a branch, and terminals are called leaves. The dendrograms produced by analysing New Testament data have a self-similar character where any part of a tree bears a resemblance to the entire tree, and vice versa. (Self-similarity is evident in the CMDS maps too.) Each branch contains its own sub-branches or sub-clusters, unless terminated by leaves (i.e. individual witnesses). A partition based on a DC dendrogram is obtained by means of a horizontal line which cuts across the dendrogram at some height.

Classical multidimensional scaling (CMDS), divisive clustering (DC), and partitioning around medoids (PAM) are distinct modes of analysis and they produce differing views of the data. The respective views are often consistent but this is not always the case. If results obtained by all modes point to the same conclusion then that can be taken as a reasonably sure result. When the respective results for a data set differ significantly with respect to implied clustering then each result needs to be treated with due caution. If the analysis methods do not produce consistent results with respect to a witness then final judgment on its affiliation must be reserved. This kind of ambiguity is common when a witness stands between one nucleus and another. In DC and PAM analysis, a slight change in the data set can cause a witness which lies near the border of two clusters to jump from one to the other.

Clustering may be identified by inspecting a CMDS map, cutting a DC dendrogram, or choosing a local maximum in the mean silhouette width and producing a corresponding partition with PAM. Humans are good at recognising clustering in a point cloud of the kind represented by a CMDS map, although they sometimes see clustering when none actually exists. (See the discussion of example C, above.) In what follows, the PAM-based method will be employed as a first resort.

Once a cluster is identified, one is immediately confronted with the problem of what to name it. Various approaches might be employed, including enumeration of members or writing down the first and last members according to some order, separating them by an ellipsis (e.g. "K ... 1241"). Epp's method of labelling with neutral symbols (i.e. A, B, C, and D) can be used for clusters which correspond to the traditional text-types.^[12] The preferred method of naming clusters in this study is to label each one with the corresponding medoid identified by PAM analysis.

As mentioned before, the analysis techniques used in this study are not genetic. They do not provide direct guidance concerning the relative priority of texts or the clusters they comprise. Another technique such as the Coherence-based Genealogical Method developed by the INTF can be used to investigate whether one cluster is closer to the initial text than another.

Even though the analysis results presented here give no genealogical insights, they do reveal the overall relationships of the texts and the main streams of textual development. To use another analogy, the map results are like time-exposures where texts of differing date occupy the same frame. Even though the maps and dendrograms do little to establish temporal order among the texts, they are valuable instruments for exploring the relative dispositions of the texts, with similar texts occurring close to each other in CMDS maps, in the same branches of DC dendrograms, and the same clusters of a PAM result. That is, similar texts tend to collocate in results produced by all three analysis modes.

The textual space occupied by witnesses of the New Testament includes a number of concentrations of texts. This study calls such a concentration a pole or nucleus. Given two textual poles, witnesses that lie directly between them represent mixtures in various proportions of the polar texts. A number of approaches can be taken to classifying these mixed texts. One approach is to assign a text according to its location with respect to the midpoint between the notional centres of the respective poles.

The large number of Byzantine witnesses tends to make the first axis of a CMDS map point in a direction perpendicular to the plane occupied by the non-Byzantine poles. Consequently, plotting only the second and third dimensions tends to maximize the separation of the non-Byzantine streams, making them stand out more clearly.

Eccentricity increases the distance of a text from all others, isolating it. The more eccentric a text, the more remote its location in a CMDS map. If a text is a mixture of two polar texts but also includes another component then it will be displaced from the trajectory between the poles.

4.1. Gospels

4.1.1. Matthew

Figure 1. Mean silhouette widths (Matthew, INTF-Parallel)

First two maxima: two and eleven clusters.

Table 3. PAM result (Matthew, INTF-Parallel, 11 clusters)
Medoid	Members
A	01 03 038 33 892 A
033	011 013 019 021 0233 031 032 033 034 036 037 04 042 043 07 09 1009 1071 1093 1253 1273 131 1328 1329 1330 1331 1333 1334 1338 1339 1340 1342 1344 1345 1346 1446 1457 150 1502 1555 1593 1602 1661 1692 174 176 1780 18 1823 191 22 222 2372 2766 2786 35 4 700 732 735 740 752 79 791 792 807 827
045	017 0211 022 028 030 041 045 047 1110 1230 1241 1296 130 1326 1335 1336 1341 1343 1347 1348 1500 1506 157 1574 2193 233 2411 2542 2546 2680 273 28 3 31 565 579 713 851 863 979
05	05
1582	1 1582
968	1012 1451 968
209	118 205 209
826	124 13 346 543 69 788 826 828 983
184	1279 1421 1528 1579 16 184 2726 348 555 61 829
517	1424 1604 1675 517 954
372	2737 372

Poorly classified (worst last): 579 1348 863 1328 732 1009 827 1334 740 18 1342 043 1330 1339 019 33 1457 792 011 79 1661 35 022 174 037 1780 1344 2372 1071 04 1506 131 042 791 2786 1340 807 1692 1093 013 752 1823 2411 1555 4 150 031 1273 735 22 892 191 1253 222 032 176 2546 851 2766 07 1333 2680 1329 1446 1345 1338 1574 034 021 1602 1346 036 09 700 038 1331 0233 1502

4.1.2. Mark

The Gospel of Mark is not well represented among the New Testament papyri, indicating that it was the least copied of the Four Gospels in Egypt during the first few centuries of the Christian era. According to Streeter, “Mark provided very few lessons for the selection read in the public services of the Church. It was much less used and much less commented upon than the other Gospels.”^[13] Noting the tendency of certain manuscripts to have fewer Byzantine readings in Mark than in the other Gospels, Streeter proposed that “Research into the pedigree of a MS. should begin with a study of its text of Mark.”^[14] If Mark was less often copied and less likely to draw the attention of correctors then it may have had a less convoluted transmission history than the other Gospels. It does seem a good place to begin an investigation of clustering among Gospel witnesses using the techniques introduced above.

Figure 2. Mean silhouette widths (Mark, UBS4)

The first two maxima indicate optimal partitions of three and eleven clusters, respectively.

Table 4. PAM result (Mark, UBS4, 3 clusters)
Medoid	Members
Psi	UBS Aleph B C L W Delta Psi 892 2427 it-k syr-s cop-sa cop-bo
Byz	A f-1 f-13 28 33 157 180 205 579 597 700 1006 1010 1071 1241 1243 1292 1342 1424 1505 Byz E F G H N Sigma Lect it-aur it-f it-l syr-p syr-h syr-pal eth geo slav Augustine
it-i	D Theta 565 it-a it-b it-c it-d it-ff-2 it-i it-q it-r-1 vg arm

In what follows, clusters will be labelled by the corresponding medoids (e.g. "it-i"). The three-way partition is reminiscent of the traditional Alexandrian (Psi), Byzantine (Byz), and Western (it-i) divisions. Other clusters emerge from the eleven-way partition:

Table 5. PAM result (Mark, UBS4, 11 clusters)
Medoid	Members
B	UBS Aleph B Psi 2427
Byz	A f-13 33 157 180 579 597 700 1006 1010 1071 1241 1243 1292 1342 1424 1505 Byz E F G H N Sigma Lect syr-p syr-h slav
Delta	C L Delta
it-ff-2	D it-a it-b it-c it-d it-ff-2 it-i it-r-1
W	W
Theta	Theta 565 syr-pal
205	f-1 28 205
cop-bo	892 cop-sa cop-bo
vg	it-aur it-f it-l it-q vg eth Augustine
it-k	it-k
arm	syr-s arm geo

Some correspond to familiar text-types such as the primary Alexandrian (B), Byzantine (Byz), secondary Alexandrian (Delta), Old Latin (it-ff-2), and Vulgate (vg). Comparing with the corresponding CMDS map shows that the "Theta," "205," and "arm" clusters are located in the same region of textual space. Members of the "205" and "arm" clusters also occupy the same branch of the corresponding DC dendrogram, along with W and f-13. It so happens that a five-way partition, while not optimal according to the mean silhouette width criterion, places W, f-1, 28, 205, 565, syr-s, arm, and geo in the same cluster.

Many of these are members of the Caesarean local text postulated by Streeter. He lists Theta and 565 as primary authorities for this text; f-1, f-13, 28, 700, W (in Mark), and the Old Georgian are listed as secondary authorities.^[15] Streeter did not include the Sinaitic Syriac (syr-s), regarding it as an authority for another one of his postulated local texts, that of Antioch.

The multivariate analysis results support the existence of a textual variety which has many of the same members as the one Streeter labelled as "Caesarean." There are differences, however. The medoid of the relevant cluster in the five-way partition is f-1, implying that the constituents of family 1 are more representative of the cluster than, say, Theta. The CMDS map shows that Theta and 565 are peripheral members, lying on a trajectory between the Armenian and Georgian versions on one side and the Old Latin cluster on the other.^[16]

Figure 3. Mean silhouette widths (Mark, INTF-Parallel)

First two maxima: two and four clusters.

Table 6. PAM result (Mark, INTF-Parallel, 4 clusters)
Medoid	Members
A	01 019 03 037 04 044 05 1342 33 579 892 A
1339	011 013 017 02 021 0211 022 028 030 031 033 034 036 041 042 043 045 047 07 09 1009 1012 1071 1093 1110 1230 1241 1253 1273 1279 1296 130 131 1326 1328 1329 1330 1331 1333 1334 1335 1336 1337 1338 1339 1340 1341 1343 1344 1345 1346 1347 1348 1421 1424 1446 1451 1457 150 1500 1502 1506 1528 1555 157 1574 1579 1593 16 1602 1604 1661 1675 1692 174 176 1780 18 1823 184 191 22 222 233 2372 2411 2546 2680 2726 273 2737 2766 2786 3 31 348 35 372 4 427 517 555 61 700 713 732 740 752 79 791 792 807 827 829 851 863 954 968 979
209	032 1 118 1582 205 209 2193 2542 28
826	038 124 13 346 543 565 69 788 826 828 983

Poorly classified: 05.

4.1.3. Luke

Figure 4. Mean silhouette widths (Luke, INTF-Parallel)

First three maxima: three, seven, and eleven clusters. (Local maxima at seven and eleven clusters are weak.)

Table 7. PAM result (Luke, INTF-Parallel, 11 clusters)
Medoid	Members
A	01 019 03 1241 579 A P75
3	011 013 0211 022 028 030 031 034 036 037 039 045 047 07 09 1110 1273 1296 130 1326 1331 1335 1340 1341 1343 1344 1347 1348 1424 1555 1604 1675 176 1780 22 2372 2546 273 3 4 732 740 791
041	017 02 041 1346 1421 2411
35	021 044 1009 1093 1230 1253 1328 1329 1330 1333 1334 1336 1337 1338 1339 1342 1345 150 1502 1506 1574 1602 1661 1692 174 18 1823 191 222 233 2680 2737 2766 2786 28 31 35 372 427 565 61 713 735 807 851 863 954 979
024	024 032 033 038 04 040 1071 157 33 700 79 792 892
05	05
1582	1 118 131 1582 205 209 2193 2542
1012	1012 1451 968
826	124 13 346 543 69 788 826 828 983
184	1279 1528 1579 16 184 2726 348 555 752 829
1446	1446 1457 1593 827

Poorly classified (worst last): 044 1337 1241 1692 807 1342 1253 233 2680 954 892 851 61 979 713 1336 1093 1661 191 1329 1009 1339 1338 28 18 1334 1328 35 372 2737 31 157 1502 427 565 1333 33 1330 1602 1823 2766 150 174 021 792 1071 222 79 033 700 1345 04 032 040 038

4.1.4. John

Figure 5. Mean silhouette widths (John, UBS2, aggregate)

Table 8. PAM result (John, UBS2, 3 clusters)
Medoid	Members
33	P66 P75 B C L X 33 syr-c cop arm geo Nonnus Cyprian Tertullian Cyril Origen Aleph-c W-supp
Byz	A K Delta Theta Pi Psi 063 Byz Lect f-1 f-13 28 565 700 892 1009 1010 1071 1079 1195 1216 1230 1241 1242 1253 1344 1365 1546 1646 2148 2174 it-f it-q syr-p syr-pal syr-h goth eth Chrysostom Theodoret
it-c	D it-a it-aur it-b it-c it-d it-e it-ff-2 it-l it-r-1 vg syr-s Diatessaron Hilary Eusebius

Figure 6. Mean silhouette widths (John, INTF-Parallel)

First two maxima: two and six clusters

Table 9. PAM result (John, INTF-Parallel, 6 clusters)
Medoid	Members
A	01 019 022 03 032 05 2786 579 892 A P66 P75
150	011 013 021 028 030 031 034 036 037 045 047 07 09 1110 1296 130 131 1326 1328 1329 1331 1333 1334 1335 1336 1338 1339 1340 1341 1342 1343 1345 1347 1348 1421 1424 1457 150 1502 1555 1574 1593 1602 1604 1675 1692 174 1780 18 1823 191 22 222 233 2372 2546 2726 273 2737 2766 28 3 31 35 4 61 700 713 732 740 752 79 791 863 954 979
1346	017 02 0211 038 041 044 1009 1012 1071 1230 1253 1273 1346 1446 1451 157 2411 2680 33 807 851 968
184	039 1093 1279 1344 1528 1579 16 184 348 555 792 827 829
1582	1 118 1241 1582 205 209 2193 565
826	124 13 543 69 788 826 828 983

Poorly classified (worst last): 032 01 1071 827 713 1457 P66 1273 579 022 017 019 33 2786 892

4.1.5. Summary

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4.2. Acts and General Letters

...

4.2.1. Acts

...

4.2.2. James

The maps and dendrograms of the General Letters are derived from data compiled by the Institut für neutestamentliche Textforschung (INTF). The INTF has been collecting information on witnesses to the New Testament text for many years and has been using computer technology to support its work for much of that time. The Institute has now developed the Coherence-Based Genealogical Method to help establish the initial text which is presented in their Editio Critica Maior.^[17] One product of this research is a database which records numbers of agreements between pairs of manuscripts for a large number of manuscripts which cover the General Letters. Standing behind the database is a complete collation of these witnesses to identify every variation unit among them. The INTF data gives a comprehensive account of the extant Greek textual tradition for the General Letters.

Results based on analysis of this data are final in the sense that analysis of any similarly comprehensive data set will produce substantially the same results. Being based on comprehensive data, maps and dendrograms derived from the INTF data provide the best available views of the Greek textual tradition.

Tetrahedral structure; two streams close to each other.

4.2.3. 1 Peter

Tetrahedral structure again.

4.2.4. 2 Peter

Not in the Syriac Peshitta. Same old tetrahedral structure.

4.2.5. 1 John

Same old tetrahedral structure.

4.2.6. 2 John

Not in the Syriac Pehitta. Not the usual picture. Not as much standardization? This may reveal copying centres.

4.2.7. 3 John

Not in the Syriac Pehitta. Not the usual picture. Not as much standardization? This may reveal copying centres.

4.2.8. Jude

Not in the Syriac Pehitta. Tetrahedral structure is there but not well defined.

4.2.9. Summary

It is hard to say how many nuclei there are, and the question remains of what to call them. Corridors between the nuclei are in some cases populated and in other cases not. This phenomenon provides an important clue concerning the later development of the New Testament textual tradition. Each corridor between a minor nucleus and the major nucleus is populated with mixed witnesses while corridors between the minor nuclei are sparsely populated. In other words, there was not much cross-talk among the texts represented by the minor nuclei but there was interaction between each minor text and the one that eventually dominated.

At first sight, these multivariate analysis results do not appear to conform to the conventional divisions of “Alexandrian,” “Byzantine,” “Western,” and, perhaps, “Caesarean” text-types sometimes used to describe the New Testament textual tradition. Certain features of the map can be reconciled with the traditional categories: the Byzantine text-type is there, and members of what are sometimes called “primary” and “secondary” Alexandrian text-types can be seen in two of the other nuclei. However, the third major non-Byzantine nucleus (the one associated with 1611) does not have a place among the traditional text-types. Nevertheless, it is not a new discovery, having been identified by Barbara Aland and Andreas Juckel.^[18]

A number of the maps indicate that there are four major varieties of text which occupy the edges of a tetrahedral structure in the textual space comprised of witnesses of the New Testament. Not all witnesses fit this structure, with a few standing apart. The apexes of the structure are composed of more or less diffuse nuclei, and distances between them vary from one General Letter to the next. If indeed four major varieties existed, what might these four have been? One possibility is that each corresponds to a central authority among whose responsibilities was the promulgation of a sanctioned text. The following is a tentative association between regions and textual varieties. As it happens, each region has a patriarchate, shown here in parentheses:

Byzantine Empire (Constantinople): The mass of witnesses to the Byzantine standard text.
Syria (Antioch): Barbara Aland and Andreas Juckel noticed that witnesses such as 206, 614, 1505, and 2147 preserve the same kind of text as consulted by Thomas of Harkel when producing his Syriac revision at Enaton near Alexandria in 616 CE. This cluster may be associated with a later text of the Syrian Church. Its earlier forms may be what stands behind the Armenian version and the Byzantine standard text.
Palestine (Jerusalem): Witnesses which may be associated with this variety of text include 04, 1175, 1739, and 1881. Although Jerusalem was early abandoned by Christians, a patriarchate was eventually established there.
Egypt (Alexandria): In 1 Peter this variety includes witnesses such as P81, 02, 03, 81, and 1735. Results derived from the UBS4 apparatus place the Coptic versions in this cluster.

	Note
	This is just a first take. I have yet to take a close look at the dendrograms, which tell their own stories.

4.3. Paul's Letters and Hebrews

...

4.4. Revelation

...

5. What Difference Does It Make?

The analysis results presented here show the variation among witnesses of the New Testament in graphic form. This naturally raises the question of what difference the variations make to the meaning of the text. Many variations are of little consequence — whether an added or dropped article, a change of word order, or substitution of a synonymous phrase. Some variations have a larger effect, the two most extreme examples being Mark 16.9-20 and John 7.53-8.11 which are absent from a number of witnesses.

One way to convey how much difference the variations make is to provide translations of a number of textual varieties for the same section of text. The following table gives a parallel translation of four varieties of the first chapter of Mark, highlighting the variation sites identified in the fourth edition of the United Bible Societies Greek New Testament. This edition only presents a selection of textual variations:

The intention was to provide an apparatus where the most important international translations of the New Testament show notes referring to textual variants or even have differences in their translations or interpretations. Other groups of variants have also been included when for various reasons they are significant and worthy of consideration.^[19]

The variation units presented in the UBS apparatus constitute a small proportion of the total number of variation units that exist. However, the ones given below should provide a reasonably good impression of how much the respective varieties of text differ in meaning. This is because the great majority of variations which are not presented in the UBS apparatus have only a slight semantic effect.

The textual varieties shown in the table consist of four clusters identified by reference to the DC dendrogram of UBS4 aggregate data for Mark:^[20]

A: The mainly Byzantine cluster comprised of A ... syr-pal
B: Aleph B C L Delta Psi 892 1342 cop-bo cop-sa it-k
C: W Theta f-1 28 205 565 arm geo syr-s
D: D it-a it-b it-c it-d it-ff-2 it-i it-q it-r-1

For each variation unit, the reading of a textual variety is taken to be the one that occurs most frequently among its members. To illustrate, suppose that a variation unit has three readings and that two witnesses in cluster C have the first, three have the second, and four have the third. The reading of cluster C would then be taken to be the third. For the purpose of this exercise, if ties occur then readings which tend to emphasize the differences between varieties are given preference.

Notes

Sometimes the most frequent readings of the four varieties are all the same as in Mark 1.6 where two witnesses from cluster D have leather instead of hair.
A variation unit may affect more than one verse, as at Mark 1.7-8.
The translation attempts to produce contemporary English while retaining the atmosphere of the Greek. Consequently, "change your attitude" is preferred to the archaic "repent," and "campaign" is preferred to the rarely used "proclaim" or less vivid "preach." The simple present is used to translate Mark's "historic present." (E.g. "He says to them...")

6. Acknowledgments

Isaac Newton said, “If I have seen further it is only by standing on the shoulders of giants.” This sentiment truly applies to the results presented here. Our field owes a great debt to those who have compiled the information, both printed and electronic, upon which the data and distance matrices are based.

The task of constructing a data matrix from apparatus information is arduous and painstaking. Richard Mallett encoded data matrices for a number of the Gospels using the NTTTC, TENT, and UBS4 editions. Mark Spitsbergen helped to encode the UBS4 apparatus data for the first fourteen chapters of Matthew.

Maurice A. Robinson kindly provided tables of percentage agreement for the Gospels and Acts. These are derived from the apparatus of the second edition of the United Bible Societies' Greek New Testament. The exacting task of transforming the data into electronic format was performed by Claire Hilliard and Kay Smith.

A number of the results are produced from comprehensive data generously provided by the Institut für neutestamentliche Textforschung in Münster, Germany. Researchers at the INTF have spent many years on the gargantuan task of compiling this data. Holger Strutwolf, Klaus Wachtel, and Volker Krüger were instrumental in providing access to the data.

The analysis would scarcely have been possible without the marvellous R Language and Environment for Statistical Computing. Finally, special thanks go to Gerald Donker for suggesting that the RGL plotting library be used to produce three-dimensional CMDS maps.

Bibliography

Aland, Kurt, Matthew Black, Bruce Metzger, Allen Wikgren, and Carlo Martini, eds. The Greek New Testament. 2nd ed. Stuttgart: United Bible Societies, 1968.

Aland, Barbara, Kurt Aland, Johannes Karavidopoulos, Carlo M. Martini, and Bruce M. Metzger, eds. The Greek New Testament. 4th rev. ed. Stuttgart: United Bible Societies, 1983.

Aland, Barbara, Kurt Aland†, Gerd Mink, Holger Strutwolf, and Klaus Wachtel, eds. Novum Testamentum Graecum: Editio Critica Maior. Stuttgart: Deutsche Bibelgesellschaft, 1997-.

Aland, Barbara and Andreas Juckel. Das Neue Testament in syrischer Überlieferung, I, Die grossen katholischen Briefe. ANTF 7; Berlin: de Gruyter, 1986.

Anderson, Jared W. “An Analysis of the Fourth Gospel in the Writings of Origen.” ThM thesis, University of North Carolina at Chapel Hill, 2008.

Colwell, Ernest C. "Establishing Quantitative Relationships between Text-Types." In Studies in Methodology in Textual Criticism of the New Testament, New Testament Tools and Studies 9, 56-62. Leiden: Brill, 1969.

Comfort, Philip W. New Testament Text and Translation Commentary. Carol Stream: Tyndale House, 2008.

Comfort, Philip W. and David P. Barrett, eds. The Text of the Earliest New Testament Greek Manuscripts. Wheaton: Tyndale House, 2001.

Cunningham, Arthur. “The New Testament Text of St. Cyril of Alexandria.” PhD dissertation, University of Manchester, 1995.

Ehrman, Bart D., Gordon D. Fee, and Michael W. Holmes. The Text of the Fourth Gospel in the Writings of Origen. New Testament in the Greek Fathers 3. Atlanta: Society of Biblical Literature, 1992.

Epp, Eldon J. “The Significance of the Papyri for Determining the Nature of the New Testament Text in the Second Century: A Dynamic View of Textual Transmission.” In Gospel Traditions in the Second Century: Origins, Recensions, Text, and Transmission, Christianity and Judaism in Antiquity 3, 95. Notre Dame: University of Notre Dame Press, 1989.

———. “The Multivalence of the Term 'Original Text' in New Testament Textual Criticism.” Harvard Theological Review 92, no. 3 (1999): 245-81.

Finney, Timothy J. Analysis of Textual Variation. http://purl.org/tfinney/ATV/.

———. “Mapping Textual Space.” http://purl.org/tfinney/Mapping/.

Maechler, M., P. Rousseeuw, A. Struyf, and M. Hubert. "Cluster Analysis Basics and Extensions." Program documentation for the “cluster” package of R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing, 2005.

Mink, Gerd. “Problems of a Highly Contaminated Tradition: The New Testament.” In Studies in Stemmatology II, edited by P. van Reenen, A. den Hollander, and M. van Mulken, 13-85. Amsterdam: John Benjamins, 2004.

———. “The Coherence-Based Genealogical Method: Introductory Presentation.” Münster: Institut für neutestamentliche Textforschung, 2009. http://www.uni-muenster.de/NTTextforschung/cbgm_presentation/.

R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing, 2011. http://www.r-project.org/ .

Robinson, Maurice A. "The Determination of Textual Relationships among Selected Manuscripts of the New Testament through the use of Data-Processing Methods." Unpublished paper in three parts, Southeastern Baptist Theological Seminary, 1972-3.

———. "Textual Interrelationships among Selected Ancient Witnesses to the Book of Acts." ThM thesis, Southeastern Baptist Theological Seminary, 1975.

Spencer, Matthew, Klaus Wachtel, and Christopher J. Howe, “The Greek Vorlage of the Syra Harclensis: A Comparative Study on Method in Exploring Textual Genealogy.” TC: A Journal of Textual Criticism 7 (2002) http://purl.org/TC/v07/SWH2002/.

Streeter, Burnett Hillman. The Four Gospels: A Study of Origins Treating of the Manuscript Tradition, Sources, Authorship, & Dates. (Eighth impression, 1953.) London: Macmillan, 1924.

Strutwolf, Holger and Klaus Wachtel, eds. Novum Testamentum Graecum: Editio Critica Maior: Parallel Pericopes: Special Volume Regarding the Synoptic Gospels. Stuttgart: Deutsche Bibelgesellschaft, 2011.

Wachtel, Klaus. Der Byzantinische Text der Katholischen Briefe: Eine Untersuchung zur Entstehung der Koine des Neuen Testaments. Berlin: de Gruyter, 1995.

———. "Colwell Revisited: Grouping New Testament Manuscripts." In The New Testament Text in Early Christianity: Proceedings of the Lille Colloquium, July 2000, Histoire du texte biblique 6, 31-43. Lausanne: Editions du Zèbre, 2003.

———. "Conclusions." In The Textual History of the Greek New Testament: Changing Views in Contemporary Research, edited by Klaus Wachtel and Michael W. Holmes, 217-26. Text-Critical Studies 8. Atlanta: Society of Biblical Literature, 2011.

^[1]Analysis results based on practically complete data sets, such as the INTF data for the General Letters, are final in the sense that analysis of any similarly complete set of data will produce substantially the same results. Results obtained from mere samples, such as data sets derived from UBS apparatus data, are not final; analysis of more complete samples may produce different results. All conclusions based on samples should be treated as provisional.

^[2]Gerd Mink provides a definition of the term initial text in “Problems of a Highly Contaminated Tradition,” 25-26. Eldon J. Epp finds the term original text problematic, as discussed in his “Multivalence of the Term 'Original Text.'”

^[3]A distance matrix can be obtained from a table of percentage agreements by dividing each percentage by one hundred then subtracting the result from one. For example, a percentage agreement of 85% corresponds to a distance of 0.15.

^[4]A sample size of fifteen corresponds to a confidence interval with a relative width of about 50% of possible values, as shown in my “Mapping Textual Space.”

^[5]Other multivariate analysis techniques are applied to New Testament data in my “Analysis of Textual Variation.” CMDS and DC are also discussed in “Mapping Textual Space.”

^[6]Maechler et al., "Cluster Analysis Basics and Extensions" (2005); diana method of the cluster package.

^[7]Examples of phylogenetic analysis results are presented in Spencer, Wachtel, and Howe, “The Greek Vorlage of the Syra Harclensis.”

^[8]Maechler et al., "Cluster Analysis Basics and Extensions" (2005); pam method of the cluster package.

^[9]A revised version of Jared Anderson's thesis will be published in SBL's New Testament in the Greek Fathers series.

^[10]The UBS4 apparatus includes minuscule 2427 which is now regarded as a forgery. The data for this manuscript has been retained for the sake of interest; dropping it has little effect on analysis results.

^[11]Epp, “Significance of the Papyri,” 95.

^[12]Ibid. (Page reference to come.)

^[13]Streeter, The Four Gospels, 64. My copy is the eighth impression (1953). In the preface to the fourth impression (1930) Streeter writes, “Fresh discoveries, and the kindness of friends in pointing out errors, have necessitated numerous alterations — so numerous that, had not many of them been already made in the second and third impressions, this might not improperly have been styles a Revised Edition.”

^[14]Ibid.

^[15]Ibid., 108.

^[16]Both Theta and W are affected by block mixture in Mark. Plan: discuss block mixture. Chop Mark into three or four chunks. Show shifting witnesses such as W and Theta. (Need to keep an eye on sampling error. Chapter by chapter results in unacceptably small samples for this data set.) Phenomenon can be explained as flagging enthusiasm of scribes correcting ancestral texts. That's why the nature shifts after the beginning of the book. Streeter said as much.

^[17]See Gerd Mink's “Introductory Presentation” for a comprehensive introduction to the Coherence-Based Genealogical Method.

^[18]See Aland and Juckel, Das Neue Testament in syrischer Überlieferung, 41-90; Wachtel, Der Byzantinische Text, 190-98; and Spencer, Wachtel, and Howe, “The Greek Vorlage of the Syra Harclensis,” paras. 4-6.

^[19]Aland et al., Greek New Testament (4th ed.), 2*.

^[20]Minuscule 2427, which is now considered to be spurious, has been dropped from the B cluster so that it does not affect decisions on cluster membership.

Reference	A	B	C	D
1.1	The beginning of the good news about Jesus Christ, Son of God.	The beginning of the good news about Jesus Christ, Son of God.	The beginning of the good news about Jesus Christ.	The beginning of the good news about Jesus Christ, Son of God.
1.2	As written in the prophets, "Look, I send my messenger before you, who will prepare your way;"	As written in the prophet Isaiah, "Look, I send my messenger before you, who will prepare your way;"	As written by Isaiah the prophet, "Look, I send my messenger before you, who will prepare your way;"	As written in the prophet Isaiah, "Look, I send my messenger before you, who will prepare your way;"
1.3	"A voice shouting in the wilderness, 'Prepare the way of the Lord! Make his paths straight!'"	"A voice shouting in the wilderness, 'Prepare the way of the Lord! Make his paths straight!'"	"A voice shouting in the wilderness, 'Prepare the way of the Lord! Make his paths straight!'"	"A voice shouting in the wilderness, 'Prepare the way of the Lord! Make his paths straight!'"
1.4	John appeared, baptizing in the wilderness and announcing a baptism of a changed attitude for forgiveness of wrong deeds.	John the Baptist appeared in the wilderness, and [was] announcing a baptism of a changed attitude for forgiveness of wrong deeds.	John the Baptist appeared in the wilderness, and [was] announcing a baptism of a changed attitude for forgiveness of wrong deeds.	John appeared in the wilderness, baptizing and announcing a baptism of a changed attitude for forgiveness of wrong deeds.
1.5	They went out to him, all of the land of Judea and those of Jerusalem, and were baptized by him, confessing their wrong deeds.	They went out to him, all of the land of Judea and those of Jerusalem, and were baptized by him, confessing their wrong deeds.	They went out to him, all of the land of Judea and those of Jerusalem, and were baptized by him, confessing their wrong deeds.	They went out to him, all of the land of Judea and those of Jerusalem, and were baptized by him, confessing their wrong deeds.
1.6	John was clothed [with] camel hair and a leather covering around his waist; he ate locusts and wild honey.	John was clothed [with] camel hair and a leather covering around his waist; he ate locusts and wild honey.	John was clothed [with] camel hair and a leather covering around his waist; he ate locusts and wild honey.	John was clothed [with] camel hair and a leather covering around his waist; he ate locusts and wild honey.
1.7	He gave notice saying, "One more powerful than me comes after me, whose sandal straps I am not worthy to bend down and untie."	He gave notice saying, "One more powerful than me comes after me, whose sandal straps I am not worthy to bend down and untie."	He gave notice saying, "One more powerful than me comes after me, whose sandal straps I am not worthy to bend down and untie."	He gave notice saying, "I baptize you in water. One more powerful than me comes after me, whose sandal straps I am not worthy to bend down and untie."
1.8	"I baptize you in water; he will baptize you in the Holy Spirit."	"I baptize you [in] water; he will baptize you in the Holy Spirit."	"I baptize you in water; he will baptize you in the Holy Spirit."	"He will baptize you in the Holy Spirit."
1.9	In those days Jesus came from Nazareth, Galilee, and was baptized in the Jordan by John.	In those days Jesus came from Nazareth, Galilee, and was baptized in the Jordan by John.	In those days Jesus came from Nazareth, Galilee, and was baptized in the Jordan by John.	In those days Jesus came from Nazareth, Galilee, and was baptized in the Jordan by John.
1.10	Then coming up from the water he saw the heavens being torn open and the Spirit coming down to him like a dove.	Then coming up from the water he saw the heavens being torn open and the Spirit coming down to him like a dove.	Then coming up from the water he saw the heavens being torn open and the Spirit coming down to him like a dove;	Then coming up from the water he saw the heavens being torn open and the Spirit coming down to him like a dove;
1.11	There came from the heavens a voice: "You are my beloved Son; I am delighted with you."	There came from the heavens a voice: "You are my beloved Son; I am delighted with you."	from the heavens he heard a voice: "You are my beloved Son; I am delighted with you."	from the heavens a voice: "You are my beloved Son; I am delighted with you."
1.12	Then the Spirit drives him into the wilderness.	Then the Spirit drives him into the wilderness.	Then the Spirit drives him into the wilderness.	Then the Spirit drives him into the wilderness.
1.13	He was in the desert forty days being tested by Satan; he was with the wild animals and the angels waited on him.	He was in the desert forty days being tested by Satan; he was with the wild animals and the angels waited on him.	He was in the desert forty days being tested by Satan; he was with the wild animals and the angels waited on him.	He was in the desert forty days being tested by Satan; he was with the wild animals and the angels waited on him.
1.14	After John had been arrested, Jesus went into Galilee announcing the good news of the kingdom of God	After John had been arrested, Jesus went into Galilee announcing the good news of God	After John had been arrested, Jesus went into Galilee announcing the good news of God	After John had been arrested, Jesus went into Galilee announcing the good news of the kingdom of God
1.15	saying, "The time has come and God's kingdom is near. Change your attitude and believe the good news."	saying, "The time has come and God's kingdom is near. Change your attitude and believe the good news."	saying, "The time has come and God's kingdom is near. Change your attitude and believe the good news."	saying, "The time has come and God's kingdom is near. Change your attitude and believe the good news."
1.16	Passing by the Sea of Galilee he saw Simon and Andrew, Simon's brother, throwing a net into the sea. (They were fishermen.)	Passing by the Sea of Galilee he saw Simon and Andrew, Simon's brother, throwing a net into the sea. (They were fishermen.)	Passing by the Sea of Galilee he saw Simon and Andrew, Simon's brother, throwing a net into the sea. (They were fishermen.)	Passing by the Sea of Galilee he saw Simon and Andrew, Simon's brother, throwing nets into the sea. (They were fishermen.)
1.17	Jesus said to them, "Come with me and I will make you into fishers of men."	Jesus said to them, "Come with me and I will make you into fishers of men."	Jesus said to them, "Come with me and I will make you into fishers of men."	Jesus said to them, "Come with me and I will make you into fishers of men."
1.18	Then they left the nets and followed him.	Then they left the nets and followed him.	Then they left the nets and followed him.	Then they left the nets and followed him.
1.19	Going a bit further he saw Jacob Zebedee and his brother John who were in the boat fixing the nets.	Going a bit further he saw Jacob Zebedee and his brother John who were in the boat fixing the nets.	Going a bit further he saw Jacob Zebedee and his brother John who were in the boat fixing the nets.	Going a bit further he saw Jacob Zebedee and his brother John who were in the boat fixing the nets.
1.20	Then he called them. Leaving their father Zebedee in the boat with the hired hands, they went after him.	Then he called them. Leaving their father Zebedee in the boat with the hired hands, they went after him.	Then he called them. Leaving their father Zebedee in the boat with the hired hands, they went after him.	Then he called them. Leaving their father Zebedee in the boat with the hired hands, they went after him.
1.21	They go into Capernaum. Then, on the Sabbath, having gone into the synagogue, he taught.	They go into Capernaum. Then, on the Sabbath, having gone into the synagogue, he taught.	They go into Capernaum. Then, on the Sabbath, having gone into the synagogue, he taught.	They go into Capernaum. Then, on the Sabbath, having gone into the synagogue, he taught.
1.22	They were shocked by his teaching because he taught them like someone with authority, not like the scholars.	They were shocked by his teaching because he taught them like someone with authority, not like the scholars.	They were shocked by his teaching because he taught them like someone with authority, not like the scholars.	They were shocked by his teaching because he taught them like someone with authority, not like the scholars.
1.23	Then there was a man with an unclean spirit in their synagogue. He screamed,	Then there was a man with an unclean spirit in their synagogue. He screamed,	Then there was a man with an unclean spirit in their synagogue. He screamed,	Then there was a man with an unclean spirit in their synagogue. He screamed,
1.24	"What's with us and you, Jesus Nazarene? Have you come to destroy us? I know who you are — God's holy one!"	"What's with us and you, Jesus Nazarene? Have you come to destroy us? I know who you are — God's holy one!"	"What's with us and you, Jesus Nazarene? Have you come to destroy us? I know who you are — God's holy one!"	"What's with us and you, Jesus Nazarene? Have you come to destroy us? I know who you are — God's holy one!"
1.25	Jesus told it off saying, "Be quiet! Get out of him!"	Jesus told it off saying, "Be quiet! Get out of him!"	Jesus told it off saying, "Be quiet! Get out of him!"	Jesus told it off saying, "Be quiet! Get out of him!"
1.26	Throwing a fit and shouting with a loud voice, the unclean spirit got out of him.	Throwing a fit and shouting with a loud voice, the unclean spirit got out of him.	Throwing a fit and shouting with a loud voice, the unclean spirit got out of him.	Throwing a fit and shouting with a loud voice, the unclean spirit got out of him.
1.27	All being shocked they asked each other, "What is this? What new teaching is this, that with authority he gives orders even to unclean spirits and they obey him?"	All being shocked they asked each other, "What is this new teaching with authority? He gives orders even to unclean spirits and they obey him."	All being shocked they asked each other, "What is this, this new teaching with authority? He gives orders even to unclean spirits and they obey him."	All being shocked they asked each other, "What is that teaching, this new one with authority, that he gives orders even to unclean spirits and they obey him?"
1.28	The news about him then got out everywhere in the whole region of Galilee.	The news about him then got out everywhere in the whole region of Galilee.	The news about him then got out everywhere in the whole region of Galilee.	The news about him then got out everywhere in the whole region of Galilee.
1.29	Then, leaving the synagogue, they went to Simon and Andrew's house with Jacob and John.	Then, leaving the synagogue, they went to Simon and Andrew's house with Jacob and John.	Then, leaving the synagogue, he went to Simon and Andrew's house with Jacob and John.	Leaving the synagogue, he went to Simon and Andrew's house with Jacob and John.
1.30	Simon's mother-in-law lay sick with fever. Then they tell him about her.	Simon's mother-in-law lay sick with fever. Then they tell him about her.	Simon's mother-in-law lay sick with fever. Then they tell him about her.	Simon's mother-in-law lay sick with fever. Then they tell him about her.
1.31	He went over, took hold of her hand, and helped her up. The fever left her and she began to wait on them.	He went over, took hold of her hand, and helped her up. The fever left her and she began to wait on them.	He went over, took hold of her hand, and helped her up. The fever left her and she began to wait on them.	He went over, took hold of her hand, and helped her up. The fever left her and she began to wait on them.
1.32	In the evening after sunset they began to bring everyone who was suffering from sickness and the demonized.	In the evening after sunset they began to bring everyone who was suffering from sickness and the demonized.	In the evening after sunset they began to bring everyone who was suffering from sickness and the demonized.	In the evening after sunset they began to bring everyone who was suffering from sickness and the demonized.
1.33	The whole town was gathered at the door.	The whole town was gathered at the door.	The whole town was gathered at the door.	The whole town was gathered at the door.
1.34	He cured a lot who suffered a variety of sicknesses and got out a lot of demons. He did not allow the demons to speak because they had recognized him.	He cured a lot who suffered a variety of sicknesses and got out a lot of demons. He did not allow the demons to speak because they had recognized him to be Christ.	He cured a lot who suffered a variety of sicknesses and got out a lot of demons. He did not allow the demons to speak because they had recognized him to be Christ.	He cured a lot who suffered a variety of sicknesses and got out a lot of demons. He did not allow the demons to speak because they had recognized him.
1.35	Getting up early while it was still dark, he left and went away to a deserted spot and prayed there.	Getting up early while it was still dark, he left and went away to a deserted spot and prayed there.	Getting up early while it was still dark, he left and went away to a deserted spot and prayed there.	Getting up early while it was still dark, he left and went away to a deserted spot and prayed there.
1.36	Simon and those with him hunted him down.	Simon and those with him hunted him down.	Simon and those with him hunted him down.	Simon and those with him hunted him down.
1.37	They find him and say to him, "Everyone is looking for you."	They find him and say to him, "Everyone is looking for you."	They find him and say to him, "Everyone is looking for you."	They find him and say to him, "Everyone is looking for you."
1.38	He says to them, "Let's go somewhere else -- into the next towns -- so that I can campaign there too, because I came out for this."	He says to them, "Let's go somewhere else -- into the next towns -- so that I can campaign there too, because I came out for this."	He says to them, "Let's go somewhere else -- into the next towns -- so that I can campaign there too, because I came out for this."	He says to them, "Let's go somewhere else -- into the next towns -- so that I can campaign there too, because I came out for this."
1.39	He was campaigning in their synagogues throughout Galilee, driving out demons too.	He went campaigning in their synagogues throughout Galilee, driving out demons too.	He was campaigning in their synagogues throughout Galilee, driving out demons too.	He was campaigning in their synagogues throughout Galilee, driving out demons too.
1.40	A leper came towards him begging and kneeling to him, saying "If you want to you can make me clean."	A leper came towards him begging and kneeling, saying "If you want to you can make me clean."	A leper came towards him begging and kneeling, saying "If you want to you can make me clean."	A leper came towards him begging, saying "If you want to you can make me clean."
1.41	Deeply moved, reaching out his hand he takes hold of him and says: "I want to. Be clean."	Deeply moved, reaching out his hand he takes hold of him and says: "I want to. Be clean."	Deeply moved, reaching out his hand he takes hold of him and says: "I want to. Be clean."	Getting annoyed, reaching out his hand he takes hold of him and says: "I want to. Be clean."
1.42	Then the leprosy left him and he was cleansed.	Then the leprosy left him and he was cleansed.	Then the leprosy left him and he was cleansed.	Then the leprosy left him and he was cleansed.
1.43	He told him off then sent him away.	He told him off then sent him away.	He told him off then sent him away.	He told him off then sent him away.
1.44	He says to him, "Look, don't say anything to anyone. Instead, go off, show yourself to the priest, and offer what Moses commanded for your cleansing as proof to them."	He says to him, "Look, don't say anything to anyone. Instead, go off, show yourself to the priest, and offer what Moses commanded for your cleansing as proof to them."	He says to him, "Look, don't say anything to anyone. Instead, go off, show yourself to the priest, and offer what Moses commanded for your cleansing as proof to them."	He says to him, "Look, don't say anything to anyone. Instead, go off, show yourself to the priest, and offer what Moses commanded for your cleansing as proof to them."
1.45	However, he went out and began much campaigning and spreading the word so that Jesus couldn't openly go into a city anymore but stayed outside in remote places. They came to him from everywhere.	However, he went out and began much campaigning and spreading the word so that Jesus couldn't openly go into a city anymore but stayed outside in remote places. They came to him from everywhere.	However, he went out and began much campaigning and spreading the word so that Jesus couldn't openly go into a city anymore but stayed outside in remote places. They came to him from everywhere.	However, he went out and began much campaigning and spreading the word so that Jesus couldn't openly go into a city anymore but stayed outside in remote places. They came to him from everywhere.