If you think that one language for science improves efficiency and understanding, the rejection of Latin appears as a monument to human folly.

Gordin (2015b: 24)

§1 This concluding chapter of part 2 of this book considers how Latin's rôle as the leading language of science and learning came to an end. Above (chap. 14), we have seen that the eighteenth century was crucial to ending Latin's hegemony in science. First, the more general question is taken up of whether Latin is now finally dead (§1); Latin's main advantage, its stability in time, is considered (§2); then the question of how the vernaculars had to adapt to become vehicles of science is briefly tackled (§§3–5); and finally, the general situation is evaluated (§6). The further development of vernacular science is outside the scope of this book; the linguistic changes to Latin will be the topic of part 3.

Now, if even in scientific communication and in the Catholic Church, which may have been the two last bastions of Latin, Latin is practically no longer used today, we may wonder: is Latin now a truly dead language? It is definitely extinct as a language with native speakers who learn it from their parents. That ceased to be the case a long time ago. But does this mean that it is dead? Those native speakers developed their way of speaking, which produced the Romance languages. But rhetorical Classical Latin was not the language of everyday life, as even a cursory comparison between Cicero's orations and his familiar letters shows.1 Thus, from very early on, literary Latin began to be disconnected from the spoken language. This situation can be seen as continuing until the nineteenth century, when Latin lost the most important position among school subjects.

Among humanists from Lorenzo Valla2 to our own days, who only consider literature written by native speakers as of intrinsic value, this situation is completely misjudged. An entire genre of 'antibarbarus' literature meaning to purge Latin grew up over the centuries, culminating in Krebs's Antibarbarus, which was last reworked by Joseph Hermann Schmalz and printed in Basle in 1905. For Krebs, Latin from Late Antiquity is already of questionable value because the spoken language had drifted away from the written one. The simple amount of scientific, philosophical, and other relevant Latin texts, which is much greater and was

1 See chap. 8 §7 above. Leonhardt (2013: 78) points out that '[a]fter Cicero, however, the vernacular disappeared from literature'.

2 In his Elegantiae linguae latinae of 1471. In contrast to later authors, Valla saw himself as a native speaker of Latin, albeit in a colloquial form ('Italian'), in a way similar to modern Arabs, as is pointed out below.

much more influential than in the case of purist Latin, provides a first hint that the Ciceronians' argument misses the point.

'The Latin language, which had never completely ceased to live in the Middle Ages and had therefore been subject to changes of all kinds, was dealt its death blow by the same men who imagined that they could awaken it to new permanent life, make it an international cultural language.'

Taking into account the argument in this book, it is clear that this is at least exaggerated: in fact, 'normal', non-humanist Latin continued to flourish in early modern times,3 but the humanist criticism and its later consequence of disregarding 'non-native' Latin literature is nevertheless clearly obsolete today, as we understand much more about written and oral forms of languages. In fact, there are many similar cases of diverging written and spoken language: Swiss Germans write Standard German but speak dialects that can be as far from it as Italian is from Latin. The school language is different from one's mother tongue, and people learn to express complicated (e.g. scientific) thought only in the former. The parallelism goes even further: depending on the amount of nationalism, people will still try to formulate 'higher' things in their dialect (as the Swiss Germans do),4 or they switch to the standard language when speaking about such matters (as Italians or Bavarians would). For the less cultivated, it feels awkward to speak the written language and they may commit errors induced by their spoken variety, both in spoken and in written Standard German. And yet, who would claim that Swiss authors such as Gottfried Keller or Friedrich Dürrenmatt wrote a language that was dead for them, were not native speakers of German, and that their works are therefore of no value? This phenomenon was first studied in depth by Charles A. Ferguson (1959), who spoke of 'diglossia'. The difference is, of course, that there is Germany, where the 'dead' language can be experienced in action for the Swiss. For Arabs, not even this is the case: dialects are spoken in all Arabic-speaking countries today, but Classical Arabic is still written, even in newspapers,

3 As already Olschki knew (1919–1927: 2:68).

4 They just apply sound laws to words that only exist in standard German: Quantenmechanik turns into /'kxvantəmε''xa:nikx/.

although nobody speaks it as a mother tongue. So is all contemporary Arabic literature a dead literature?

Instead of using the unclear and pejorative term 'dead', Leonhardt (2013: 19) rightly proposes calling Post-Classical Latin a fi xed l an gu age instead. It certainly makes sense to distinguish 'dead' languages, knowledge of which was lost at some point and whose partial knowledge had to be recovered by scholars later on,5 from fixed languages, which are no longer learned from one's parents and family but knowledge of which and their literature has never been lost and which continue to play important rôles in society. Among the latter, we can distinguish subforms such as liturgical languages (such as Coptic, Hebrew, Koine Greek, Latin) and fixed international languages (such as Koine Greek until the fifteenth century, Latin until the nineteenth century, or Standard Arabic until today). Leonhardt (2013: 7) points out that the trend in modern linguistics to restrict the study of language to its 'natural' form, that is, one that is oral, spontaneous, and 'untainted' by schoolmasters, is an inheritance from nineteenth-century Romanticism and is completely unscientific. The approach in the present book (as in Leonhardt's) of not distinguishing between 'dead' and 'alive' phases of Latin is an attempt to remedy this manqué 'humanist' approach. Despite being fixed, we will see below in part 3 that scientific Latin did change over time. Following Christine Mohrmann, who spoke of a 'normativisme évolutif', 6 Stotz called the linguistic development of Mediaeval Latin in general a 'fortwährende Normenentfaltung' (1996–2004: I, §9.8 =vol. 1, p. 33). In this progressive unfolding of norms, older norms remain valid (in contrast to living languages, where they are forgotten and become obsolete), but new norms may nonetheless be added. Some syntactic change happened in the Middle Ages (e.g. concerning subordinate clauses), but most importantly much new vocabulary was added to Latin's stock. Academic Latin also changed through time, but differently than a living language: there

5 For instance, quite well for Sumerian, only piecemeal for Etruscan.

6 'Le latin a donc été une langue stylisée, une Kunstsprache vivante sans être la langue d'une communauté ethnique. Cette langue est vivante et variable, par suite de cette norme appliquée par les générations successives, qui n'était ni absolue ni fixe, mais qui marchait de pair avec l'évolution culturelle. Grâce à ce normativisme évolutif, le latin est devenu un instrument adéquat de la civilisation médiévale. Celui-ci, émanant de la Ideengemeinschaft des lettrés qui remplace la communauté ethnique, assure comme élément régulateur la vie du langage' ('Latin was therefore a stylised language, a living Kunstsprache without being the language of an ethnic community. This language was alive and changing, as a result of this norm applied by successive generations, which was neither absolute nor fixed, but kept pace with cultural evolution. Thanks to this evolutionary normativism, Latin became a suitable instrument for mediaeval civilisation. Emanating from the Ideengemeinschaft of the educated, which had replaced ethnic communities, it ensured the vitality of the language as a regulating element'; Mohrmann 1958: 273).

were no sound shifts reflected in the orthography, and hardly any change in the grammatical structure, but new constructions from within and sometimes from Greek were adopted besides, again, a lot of new vocabulary. We can thus say that Latin in the past one and a half millennia was not a dead language but (among other things) a living, although fixed, language of erudition. The linguistics of fixed languages is a field that has hardly been trodden as yet.

Fixed languages are also not'dead' in the sense that they can, all of sudden, become fully 'alive' again, as happened with the fixed liturgical language Hebrew in the form of Ivrit in the twentieth century. Although this is not very likely to happen any time soon for Latin, Latin does not seem to be as 'dead' as one might think, even today. A quick glance at the Latin Vicip aedi a shows that on 3 November 2018 it had 129,438 entries (54th among all languages in Wikipedia) with 112,290 users, although only 161 of them had made edits within the past month.7 In early 2021, it contained nearly 4 million words, only slight less than the Perseus Classical Latin text collection.8 The numbers for Modern Greek are only slightly higher. No other dead or fixed language comes close;9 Sanskrit (also a fixed language of liturgy, culture, and erudition) follows with only 11,351 entries. Vicipaedia's main page has the traditional Latin artes & litterae opposed to scientiae (see chap. 1 §6 above), besides societas, technologia, and lingua latina as main categories. It would thus seem that the field in which Latin is still most used is that of Latin literature, science, and technology. Of course, the Latin diction used has also taken up much from the modern European languages such as English and German, the continuation of a process observed above for Jesuit Latin. Some examples of words from Vicipaedia entries: disciplina scientifica, ethnocentrismus, societas conlaborativa, psychologia gestaltica, moratismus (i.e. behaviourism), miliardum, usor (all these terms yielded 0 hits in Corpus Corporum as of 2021). The administratores of Vicipaedia have to take care that the usores do not use 'Vulgar' Latin; indeed, the Latinity of their pages differs significantly, but they are mostly perfectly understandable.

'If you write a page in another language than Latin, or one distinguished by horrible Latinity, or you employ Latin made by machine translation, you must not be surprised or complain when your page is deleted.'

7 See https://meta.wikimedia.org/wiki/List\_of\_Wikipedias (3 November 2018).

8 Estimated from the downloadable dump https://dumps.wikimedia.org/lawiki, counting only article text, without discussion and editing history.

9 The artificial language Esperanto has more entries, but it is spoken as a mother tongue by several thousand people by now.

10 https://la.wikipedia.org/wiki/Vicipaedia:De\_Latinitate (21 June 2018).

§2 The truly great advantage Latin had to offer for science was its s tabili t y over time and its long memory11 – advantages that Greek shared only up to the fall of Constantinople (1453). The use of the classical form of Greek diminished rapidly and for good after this traumatic event. The linguistic studies (chaps 18–20) will show that the Latin language changed very little over two millennia, that the variation is more of a stylistic nature than of a unidirectional change over time. One could say that the positive side of a language being 'fixed' is its stability. Someone able to read Varro can also read Newton's Latin (although he may not understand the maths) nearly two thousand years later. In contrast, even Newton's English is already a significantly different kind of English than ours today. If Old English or Old High German scientific texts existed, they would be very hard for us to read now. A somewhat later example may illustrate this, the German translation of the De sphaera of John of Sacrobosco by Konrad of Megenberg (1309–1374):

Euclydes der maister beschreibt uns waz spera sei, und spricht: 'Spera ist ain gank ainer ůmbverte ains halben kraizzes, deu veste und eben stet an irr mittelmezzigen lengen und di man also lang umbfůrt piz sie wider kůmpt an die stat irs anvanges.' 12

Spera igitur ab Euclide sic describitur: spera est transitus circumferentie dimidii circuli quotiens fixa diametro quousque ad locum suum redeat circumducitur.13

'A sphere is thus described by Euclid: a sphere is the orbit of the circumference of a half circle having a fixed diameter when it is led around until it returns to its initial position.'

In the mere half-millennium between Konrad's times and ours, his German has become very hard to read for German-speakers. Some of the problems that arise are orthographic, but the more serious ones concern vocabulary: 'mittelmezzige lenge' is now called Durchmesser; 'die stat', Ort. By contrast, Sacrobosco's Latin is still close enough to Cicero's that the latter would have understood it easily (although probably disdaining its style). Thus, Antoine Meillet was spot-on when he pointed out (1928: 1):

Langue d'un grand empire […] le latin à gardé durant quelques huit cents ans une stabilité. Quand l'unité de la langue parlée a commencé à se rompre, du IIIe au Xe siècle ap. J.-C., l'unité de la langue écrite à persisté. Le latin classique est demeuré jusqu'à une période

11 This advantage was obvious to many writers before the nineteenth century. Samuel Gott addresses the three old holy languages (Hebrew, Greek, Latin) in book III of his novel Nova Solyma: In his, tanquam tot preciosis arculis omnes artium et scientiarum gemmae conduntur ('In these languages, as if in as many precious caskets, all jewels of art and science are stored'; 1648 edition, p. 132).

12 Deutsche Sphaera, ed. Matthaei, p. 4.

13 Edited in Thorndike (1949: 76).

avancée de l'époque moderne l'organe de la science et de la philosophie dans l'Europe occidental.

'As the language of a great empire […] Latin kept its stability during some eight hundred years. When the unity of the spoken language began to break down, from the third to the tenth century AD, the unity of the written language persisted. Until late modern times Classical Latin remained the organ of science and philosophy in Western Europe.'

The argument that Latin's status as a 'dead' language actually benefited it in its rôle as language of science because the language was no longer suffering erosion by linguistic change and remained intelligible and usable as a kind of metalanguage,14 was already used in the time when Latin was fighting to retain but finally lost this rôle. Of course, this was already clear to the more thoughtful early modern authors. For instance, Baltasar Gracián, SJ, addressed Latin in 1651 as eterna tesorera de la sabiduría ('the eternal treasurer of wisdom'; El criticón I.4, ed. Romera-Navarro, vol. 1, p. 164). When this state of affairs is no longer taken for granted and the discussion of the continued use or abolition of Latin in the sciences is taken up, this point is also often stressed; for instance, Renatus Carolus de Senkenberg (Meditationes maximam in partem juridicae quinque, p. 139) pointed out in 1789:

Mortua quum sit [lingua latina], id est nulli amplius populi propria, sed communi tantum eruditorum consensu talis, qualem Romani scriptores nobis reliquere, pro lingua scientiarum adoptata, nullis haec mutationibus obnoxia est. Ergo omnia substantiva, omnia verba, omnia vel minima vocabula, eandem post mille annos, modo non plane exulare tunc jussa sit, apud ejus peritos habebunt, quam nunc et quam ante bina jam millia annorum habuere, significationem.

'The Latin language being dead, that is, no longer the property of any nation but only through mutual consent of scholars adopted – as the Roman writers left it to us – as the language of the sciences, it is not subject to any changes. Thus, all nouns, all verbs, all words, even the slightest – provided that Latin will not be abolished altogether – will have for those versed in it the same meaning in a thousand years as today, and as they already had two thousand years ago.'

§3 Latin had taken over the function of being Europe's language of science and learning from Greek and was succeeded by several European vernaculars; we might speak of a translatio linguae, comparing it thus to the mediaeval concept of translatio imperii (Pörksen 1999: 649). Some of Latin's heirs – and, one is tempted to say: murderers – were already encountered above (chap. 14 §§3, 6), especially French. After the initial success of French as the sole international language in the eighteenth century, three languages soon ended up replacing Latin as the

14 See Glei (2014).

languages of science throughout the nineteenth century: French, German, and English (Gordin's 'triumvirate'). Somewhat earlier, Italian15 started to be used for scientific publications, but this was not to last long, as a look at the languages in the list above (chap. 14 §3) shows. In the early twentieth century (after World War I and the exclusion of German scientists from international scientific conferences for eight years), English started to ascend to world hegemony, which (at least in the natural sciences) is today all but complete, as can be seen in Ammon's graphic (fig. 29). The curves show how only German between the Wars and then Soviet Russian were able to briefly challenge English after the break-up of the 'triumvirate'. Latin is not even depicted any more.

Fig. 29: Source: Ammon (2012: 338). The values are given as percentages and are based on the natural sciences worldwide, from Biological Abstracts, Chemical Abstracts, Mathematical Reviews, Index Medicus and Medline, and Physics Abstracts.

Latin as the language of the sciences had some clear advantages, especially its ready-made vocabulary and syntax for scientific use, but most of all its international comprehensibility.16 Leibniz called it the lingua europaea universalis et durabilis ad posterioritatem ('the European language that is universal and durable for posterity'; 1872a: 441),17 and would have liked to see it preserved at universi-

15 For which see Olschki (1919–1927).

16 For a list of advantages and disadvantages, see Pörksen (1986: 69–71), besides Roelli (2018).

17 He points out in parentheses: 'zumahl da die lebenden sprachen veränderlich seyn' ('especially as the living languages suffer change').

ties. The three new languages of science (German, French, English) are all Indo-European languages with a similar structure and heavily indebted to Latin (and more indirectly to Greek). This made it relatively easy for them to adopt and to share the position of language of science, as any scientist with a decent education could be expected to read all three languages. A brief look at how these three vernacular languages acquired the necessary vocabulary and syntax concludes this part of the book. How their vocabulary had to adapt is discussed in more detail in chapter 21.

#### Scientific vocabulary

§4 As soon as the vernacular languages start to be used for scientific matters, technical terminology from Greek and Latin is quite naturally taken over. Chaucer's (ca. 1343–1400) Treatise on the Astrolabe, which he proudly wrote in his mother tongue, not in Latin, can still not avoid the use of Latin and Arabic terms (underlined), as this example shows (part II, §6, ed. Skeat, p. 20):

To knowe the spring of the dawyng & the ende of the euenyng, the which ben called the two crepusculus: Set the nadir of thy sonne vp-on 18 degrees of heyhte Among thyn Almykanteras on the west side; & ley thy label on þe degre of thy sonne, & thanne shal the poynt of thi label schewe the spryng of day.

But the extent of this can be much greater still, and may include phrases and syntax. Pörksen (1994b) speaks of Fachwerkstil ('timber-frame style') for what often ensued, that is, texts that although written in a vernacular language are interspersed with Latin, not only Latin words (which is to some extent still true today of much scientific English prose) but also phrases and entire sentences. An example from Leibniz (1872a: 439):

Ein Studiosus Medicinae, ob er schohn bloß ad praxin gehen will, soll neben denen communibus omni studioso dignis guthe kundschaft haben in mathesi practica et physica generali, auch deneben herbas medicinales vel officinales umd andere materialien kennen lernen, die bey den Apothekern und materialisten gebräuchlich.

'A studiosus medicinae, even if he only wants to go ad praxin, should, in addition to the communibus omni studioso dignis, have good knowledge in mathesi practica et physica generali, as well as getting to know herbas medicinales vel officinales and other materials used by pharmacists and purveyors of remedies.'

One of the main reasons for Latin's long persistence in a time of vernacular tongues vying for European hegemony was clearly its terminology. In many sciences, it already had a vast stock of Greek and Latin terms inherited from Antiquity, which was often considerably enlarged in scholasticism and during the heyday of the Scientific Revolution. Besides this advantage, among the new contestants for becoming scientific languages, only German had the ability to effortlessly form new words by compounding. This flexibility, on the other hand, had the disadvantage that often several different attempts to render one Latin term coexisted. For instance, German writers from Notker Teutonicus (ca. 950–1022) to Wolfgang Bütner (ca. 1530–ca. 1596) translate subiectum variously as underin, Vordertail des Fürschlags, Subjectum, Grundwort. 18 Thus, Germans had no problem forming new words, especially compounds, to render Latin concepts; the problem was only one of standardisation. Even in the seventeenth century, it will have been much easier even for educated Germans to understand standardised Latin than scholarly German authors in many fields. So, for sciences with a need for a vast and growing vocabulary, it was still Latin that offered the best solution as late as the eighteenth or even the nineteenth century. Good examples of this are botany (chap. 15 §4) and chemistry, which still uses abbreviations of the Latin names of chemical elements (chap. 21 §7 below). Medicine could also be mentioned in this respect.19 In order to gain the necessary vocabulary, the Romance languages and English naturalised Latin and, to a lesser degree, Greek terms from the Latin scientific literature by submitting them to some simple sound-change laws and adapting their pronunciation. German did/does this partly as well, but often translates the Greek or Latin terms into German compounds.20 Indeed (Pörksen 1999: 645):

Die deutsche wissenschaftliche Prosa hat sich nicht auf der Grundlage einer eigenen untergründigen mündlichen Kultur herausgebildet, sondern als Lehnprägung der lateinischen Schriftkultur.

'German scholarly prose did not develop on the basis of its own underlying oral culture, but rather as a borrowed formation from Latin written culture.'

The entomologist Theodore H. Savory observed that contemporary scientific language can be very easily translated, as illustrated by an example of a short entomological text he translates very closely from French to English, shown in figure 30. This observation is interesting, although it will become clear (chap. 22) that this can only work if scientists in both languages share the science in question and have established a one-to-one correspondence between terms – today, espe-

18 See the table in Schmid (2015: 45) with a dozen or so similar examples.

19 See also Dirckx (1983).

20 Many German non-scientific terms are also clearly calqued from Latin, but this is no longer recognised by speakers, e.g. Barmherzigkeit = misericordia, Einfluss = influentia, Eindruck = impressio, Zufall = accidens, Allmacht = omnipotentia, unbegreiflich = incomprehensibilis, ausdenken = excogito (see Wiegand 1999: 642).

cially when they share the general Begriffsgemeinschaft. All of this is the case here, as most terms are of Greek or Latin origin ('arthropod', 'chitinous', 21 'ecdysis', and so on). Moreover, both French and English developed their scientific language out of Latin. But the situation is very different for languages that do not take over concepts easily (see chap. 23), or that do not (yet) share the Begriffsgemeinschaft – for instance, for Arabic translators from Greek in the Middle Ages. Thus, this easy translatability of scientific language is largely illusory. Besides vocabulary, one-to-one syntactic correspondences are also crucial to transplant a science from one language to another.

Fig. 30: Perfect translation of scientific language? From Savory (1953: 116–117). Line 8 in the French text has a typographical error: poinds should read poids.

#### Syntax

§5 Syntactic borrowing in the Western European vernaculars from Latin was probably considerable, but the field is understudied.22 Blatt (1957: 69) concluded about syntactic borrowing:

These two features taken together, viz. the architecture of the sentences or phrases and the rationalisation of the language, suffice to prove that Modern European syntax bears the stamp of the Latin genius. European standard languages of to-day may be considered useful instruments for modern thought, because tuned from Classical syntax.

21 This substance's name is ultimately derived from χιτών ('garment').

22 Beckman (1934) made a start but remained on the quite general level of matters like the emergence of words for 'yes' (14) or 'one'/man/on (15). Pörksen rightly wonders: 'Warum gibt es keine Geschichte vom Übergang vom Lateinischen zum Deutschen?' ('Why is there no history of the transition from Latin to German?'; 1999: 644).

In the case of German, more infinitive and participle constructions, hypotaxis, and more complex sentences have been named as emerging under the influence of Latin.23 It also seems that the modern Western European languages took over some absolute constructions from Latin. We shall confine the discussion to one example of a potential borrowing that works in English but not in German.24 English can form ‑ing-form or passive participle clauses that resemble the Latin participium coniunctum and the ablativus absolutus. Thus, one can say:

This substance, discovered almost by accident, revolutionized medicine.25

This corresponds exactly to Latin (translating verbatim):

Haec substantia, inventa quasi fortuite, medicinam novavit.

The English substitute for the ablativus absolutus is sometimes called a 'nominative absolute'. It can be traced back to a 'dative absolute in disguise', which was common, for instance, in Wycliffe (ca. 1325–1384).26 A modern example:27

No further discussion arising, the meeting was brought to a close.

This corresponds to Latin:

Disputatione absente, conventus terminatus est.

It seems that this construction becomes fully naturalised in English only after 1660, at first in authors with classical influence.28 This cannot be done in German or in French; both languages require a construction with a finite verb form. But Old High German had a similar construction (also with the dative) which was sub-

23 Habermann (2001: 33–57). Von Polenz (2000: 219), surprisingly, estimates the Latin syntactic influence on German as minor.

24 The Romance languages have similar constructions: Questa sostanza, scoperta quasi per caso, rivoluzionò la medicina, or cela étant dit, although this would not be used to translate the 'No further discussion arising …' example below.

25 From Quirk et al. (1985: §15.61, pp. 1124–1125), who speak of 'subjectless supplementive clauses' and note that this also works without a participle: 'I found George, unconscious, a few hours later.'

26 See Ross (1893: 302).

27 Also from Quirk et al. (1985: §15.58, pp. 1120–1121), who speak of 'absolute clauses'.

28 Thus Ross (1893: 302).

sequently lost: bî fatere lebendemu = patre vivente. Modern German tends to use nominal construction for similar cases: zu Lebzeiten des Vaters.

§6 Science in the vernacular, of course, brings with it both ad v an ta ges and dis ad v an ta ge s. With vernacular science, influence on popular culture is augmented dramatically (for good and for ill); it can be abused in nationalism; the texts may become unintelligible beyond national borders, which again favours a nationalist group identity and the formation of national schools; and its terminology may waiver between technical meanings and everyday ones. On the other hand, more people gain access to erudition, and new ways of practising science may become easier outside the old Latin framework. Vernacular prose certainly also profited from this influx from the sciences. As mentioned above, the inherent stability of a fixed language that had long ceased to be spoken by a people and had thus become common property is the most important point in favour of the continued use of Latin. Latin was still the only medium when the important changes of the Scientific Revolution happened; this revolution might not have happened at all in a linguistically fragmented Europe that became the norm in the nineteenth century. However, as far as the kind of science is concerned, I cannot discern a significant change in methodological Denkstil in the eighteenth and nineteenth centuries:29 the vernaculars carry on the Latin kind of science developed in the Scientific Revolution, even copying its language, especially the terminology, considerably. The revolutionary science we still practise today seems to have remained faithful to its Latin foundations in the Scientific Revolution.

29 In contrast to Pörksen (1999: 657).

### Part 3 Changes in the language of science

This third part of the book undertakes several linguistic forays into largely uncharted territory about the Latin of science and learning. Various methods will be used, but especially corpus linguistic ones. In particular, this is the first attempt to linguistically study scientific Latin from its beginnings to the present; texts from the authors introduced in part 2 will be used to this end.1 Data for scientific Latin will be mined from Corpus Corporum, first by studying one large general scientific corpus (chaps 18–19), then several smaller specific ones (chap. 20) diachronically and comparing the results to several corpora of other Latin prose. With the help of these corpora, the goal is to find out (i) to what extent scientific Latin differs from other Latin, (ii) to determine whether there are trends of change through time, and (iii) to identify different types of Latin scientific writing. Then, progressively more general topics are addressed: differences in naming novelty in science between Antiquity, scholasticism, and modernity in Latin (chap. 21), a comparison of Latin with some other traditional languages of science and their translatability (chap. 22), and the reuse of Greek and Latin in the modern languages of science (chap. 23). The last chapter (chap. 24), finally, attempts a synthesis of how science, culture, and language interact and of how far the Greek scientific Denkstil

1 Banks (2008) did something similar for scientific English: from Chaucer to present-day usage.

depends on the Greek language and how it could be transplanted into Latin, whence it led to modern science. It is hoped that these approaches will produce an initial overview upon which further research can build.

### 17 Introduction to the linguistics of scientific language

§1 Above (chap. 4), linguistic prerequisites for a language of science were postulated. Its vocabulary should, it was suggested, (i) have a well-defined terminology, (ii) be unambiguous for specialists, and (iii) display extendability/flexibility, and its syntax should demonstrate (iv) perspicuity and (v) evidentiality, such as nuances of certainty. In general, the syntactic structures available in a language of science should represent the topic under consideration adequately, for instance by representing clearly the kinds of relations between the objects studied by the science in question. Structure words (conjunctions, prepositions, particles, the article) are especially important for achieving this. In general, we might ask whether the parts of speech follow different distributions in technical scientific Latin than in other registers. How did their use change diachronically in Latin? How do they compare to other languages of science?

This introductory chapter will review some findings from the study of modern scientific language; especially for English and German, quite a lot of work has been done in the preceding decades. These insights will then serve as a point of departure for studying scientific Latin. We would expect to find some similarities, or at least a general trend converging toward contemporary practices, between these Latin results and those for modern scientific English and German. Differences in vocabulary and syntax, especially parts of speech, in scientific German and English are reviewed first.

#### Vocabulary

§2 According to Gerr (1942), the evolution of a language of science consists of three elements: (i) increasing size and complexity of vocabulary, (ii) rationalisation of the vocabulary through multiplication of functional and operational terms, and (iii) general rationalisation, that is, the progressive reduction of syntactic complexity to the absolute minimum. Point (iii), however, may only apply to the contemporary English of the natural sciences and may not be typical at all. Special vocabulary, point (i), is certainly the most conspicuous characteristic of scientific language in general. Indeed, technical languages or languages for special purposes (Fachsprachen) have hitherto mainly been studied in terms of specialised vocabulary, which, in turn, is often claimed to consist especially of nouns.1 'Langues techniques' were described by Vendryes (1921: 294–295) as:

Les langues techniques sont dues à la nécessité de désigner des objets ou des notions qui n'ont pas de nom dans l'usage courant; mais elles répondent aussi au besoin de désigner 'scientifiquement', c'est à dire par un terme plus précis, excluant toute équivoque, des objets que désigne fort bien la langue ordinaire.

'Technical languages arise due to the need to designate objects or notions which do not have a name in everyday use; but they also respond to the need to designate "scientifically", i.e. by a more precise term, excluding any ambiguity, objects which are already designated in ordinary language.'

He then compares technical languages to argot, jargon, and cant. These varieties of language have in common the fact that they are most distinctive in their technical vocabulary. Langslow defines technical terminology thus (2000a: 25):

A referring expression which is recognized and used in a standard conventional way by the relevant community of specialists and which unambiguously (and often uniquely) names an object or a concept of the discipline, and therefore, because of this attachment, tends itself to absolute synonymy and total translation.

We have already pointed out (chap. 16 §4) that such total translation is in general illusionary: it works only if the two languages in question share a scientific approach and a Begriffsgemeinschaft. If one is dealing with less 'abstract' topics, as Langslow does in medicine, it may be enough to merely label a sensibly perceptible 'object' shown by ostension and apply a name (a bone, medicinal plant, disease, etc.), or to define a translation for such a label from another technical language (in the case of Antiquity, Greek). This makes the use of technical vocabulary in medicine, for instance, much more straightforward than in more abstract sciences such as physics or even more 'philosophical' fields such as logic or linguistics. Here, complex thoughts and often new not sensibly perceptible items are met and stand in need of words that make sense only within the system of thinking (Fleck's Denkstil). Some examples: 'work', 'force-field', 'significant error', 'metabolism', and so on. If a science is strongly formalised, especially mathematically, which becomes common for some sciences only after the Scientific Revolution, this becomes much easier (e.g. work: W = ∫ F ds). This explains why 'total translation', as demanded by Langslow, was, in fact, not at all trivial. For instance, the first mediaeval translators of Aristotle's Physica and Metaphysica had to deal with a very difficult task.

1 e.g. Langslow (2000a: 6–7).

In general, there seem to be two phases in the development of the terminology of a scientific branch: a groping in a new field, accumulating facts, then a cleaning-up of terminology once a certain standard approach and understanding have been gained. Sager, Dungworth & McDonald put it thus: 'only when a sufficiently large body of knowledge has been accumulated, can an attempt be made to order it systematically and to reflect this ordering in regular patterns of designation' (1980: 239). In medicine and biology, this led to the contemporary quasiartificial language based on Greek and Latin; in chemistry, a special body (IUPAC) defines rules for naming chemical compounds. But completely new substances, such as toluene, are still named arbitrarily.2 Further examples are mentioned below (chap. 21 §5).

Sager, Dungworth & McDonald (1980: 242) found that scientific vocabulary consists of (i) general language words ('note, observe, prove'), (ii) general language words used specifically with some restriction or modification of meaning ('segregate, precipitate, current'), and (iii) specialist terms usually only used by specialists ('to age a dye, conversational device'). Such specialised terms can generally be formed by three methods (245): (i) creation within the language (suffixes, compounds, …), (ii) extension of meaning, and (iii) borrowing from outside. In comparison to other Indo-European languages such as Sanskrit, Greek, or German, compounding is less common in Classical Latin – it is even quite consciously avoided – but suffixation does play an important rôle both in scholastic Latin and in English, in fact with many suffixes from the former in the latter ('‑ise', '‑ous', '‑ent', '‑al', '‑ic', '‑ation', …).3 English does use the equivalents of compounds quite freely, but they tend to be considered noun phrases as they are rarely written as a single word. They can get nearly as long as in German in scientific English, for instance 'fluid power transmission system' (273).4

Some examples of scientific neologisms illustrate several ways in which they can be formed in English (281): by combinations of Greek or Latin word elements (such as 'dictaphone'), Latin or Greek stems (such as 'cusp', 'apex'), blending, compression of existing terms (such as 'transceiver' < 'transmitter' + 'receiver'), eponyms (such as 'Mach number'), and use of letters (often Greek, such as 'gamma ray'); absolute invention, however, is rare (such as 'byte', 'paraffin'). Below (chap. 21), we will study examples from medicine of the formation of Latin scientific vocabulary. Sager, Dungworth & McDonald (chap. 9)5 also provide numbers

2 Although toluene could be called methyl benzene, and benzene itself [6]annulene, but terminology becomes too long like this and is avoided.

3 Sager, Dungworth & McDonald (1980: 298–300) offer a list of English scientific suffixes.

4 On English compounds, see Marchand (1969).

5 This standard work will provide us with figures for many parameters below.

showing how far technical terminology can be developed. For instance, in 1980 there were more than 4 million names in organic chemistry. Although many constituents of them stem from Latin- and Greek-based words or parts of words, this special vocabulary has its own complex rules of derivation, enabling chemists to understand most of these artificial words without having heard them before. For instance, someone who knows 'toluene' will also understand 'trinitrotoluene'. 6

#### Syntax and parts of speech

§3 The distribution of parts of speech (PoS) in technical languages can differ significantly from ordinary language.7 Below, it will be seen that this is also true for scientific Latin. For English, Sager, Dungworth & McDonald (1980) provide some numbers: nouns account for 28 % of words in general English, but 44 % in scientific English; on the other hand, adverbs seem to be less frequent (4 % vs 8 %; 234). Conversely, a study by Alekssev (cited ibid.) also found verbs to be rarer (full verbs 9.6 % vs 15.8 %, auxiliaries 6.9 % vs 11.9 %) when he compared the language of electronics to ordinary telephone conversations. Articles were more common in scientific language (12.8 % vs 7 %). In contrast to Latin and Greek, English (like Chinese) can very easily convert PoS (244), that is, use one word category for another. But unlike Chinese, English also borrows very easily. All of this together makes English quite unique among the major languages, and scientific English, a mixture of constituents from many sources, even more so.

PoS distributions can also be telling regarding syntactic differences, especially the percentages of structure words, which will be studied for Latin below. There is less literature about syntactic differences between ordinary and scientific language than about vocabulary. Quite in general, specialised languages tend to make use of already existing syntactic devices, although possibly fine-tuning them and using them in different frequencies. Gross, Harmon & Reidy (2002: 230) summarise their study and describe scientific syntax as follows:

In the 20th century, we find the scientific article growing considerably more uniform across national boundaries and scientific disciplines. Most striking of all, 'scientific English' has become the international discourse of science, which involves not only a specific language but also a suite of stylistic features: relatively short, syntactically simple sentences containing complex noun phrases with multiple modification, verbs in the passive voice, noun strings, technical abbreviations, quantitative expressions and equations, and citational

6 Chinese characters are somewhat similar in this respect: sometimes it suffices to understand their constituent parts to guess a character never seen before. Of course, in chemistry the system is much more logically stringent.

7 For this section, see Sager, Dungworth & McDonald (1980: chap. 8).

traces. French and German scientific articles also conform to this basic style, with some variations. For example, French and German scientific prose has resisted the noun string; each of these languages employs several grammatical structures that avoid the passive voice yet maintain an objective tone. Whatever the language or discipline, the style is streamlined to focus the reader's attention on the things of the laboratory and the natural world beyond the printed page, rather than to draw attention to the text itself or its author.

Similarly, Gerbert (1970)8 already found that typical features of scientific English syntax are 'high density of nominal groups, usually heavily modified, a large number of non-finite verb forms and extensive use of the passive'. On the other hand, one is unlikely to encounter idioms (but not jargon), colloquialisms (such as 'isn't', 'gonna'), or the personal pronoun 'I' (although 'we' is frequent; it may be used for a group, a member of a society, anyone, the reader – 'as we shall see later' – or the reader and the author; Sager, Dungworth & McDonald 1980: 226– 227). So the fi rs t pe rson sin gul a r is rarer than in most other types of writing. Indeed, the third person is by far the most common one. Banks (2008: 197) finds low numbers for the first person singular through the entire timespan of his study (eighteenth to twentieth century) in English.

It would seem that the use of prepositions and conjunctions, which determine the relationship between words and clauses and which may be used to model those between processes and entities, is especially important in scientific writing.9 Declarative sentences are indeed frequent; logical connections between thoughts are often expressed by conjunctions such as 'consequently, hence, so, therefore, thus', 'as a result of, because of, in view of, owing to', and so on (Sager, Dungworth & McDonald 1980: 186–202, here 190, 191). Sentences are often explicitly linked together by particles such as 'such, this, these; consequently etc.; additionally, in addition, besides, for example, for instance, furthermore, likewise, moreover, similarly, then; conversely, however, nevertheless, otherwise; as follows, following, below, later' (198–200). As science often deals with the relation between things, p repo si ti ons are clearly also important. For prepositions, Poncelet (1957) tried to show that Greek's richness was hard to reproduce in Latin, especially in Classical Latin that of κατά ('according to') to express conformity (in scholasticism, secundum was to take its function).10 Complex prepositions – those consisting of several words, such as 'in respect of' – can usually be added to a language's repertoire easily. Gowers, Barrow-Green & Leader (2008a: 10–13) point

8 Quoted in Sager, Dungworth & McDonald (1980: 184–185).

9 In strongly inflecting languages, cases can take on such rôles as well; see, for Sanskrit, Jacobi (1970).

10 Quoad can take similar functions (Lewis & Short's last meaning: '[w]ith respect to, as to, = quod attinet ad'), but it too was rare in classical times.

out that mathematical functions can be seen as having the same rôle as prepositions in natural language. Thus, 'the cat is under the table' corresponds to 'five is the square root of twenty-five'; mathematical equivalence relations can similarly be compared to conjunctions. Or, put differently: modern mathematics in a sense generalises and formalises conjunctions and prepositions found in natural languages.

Among verb forms, imperatives are frequent in some technical writing (such as manuals), but not in strictly scientific texts. On the other hand, the verb 'to be' is in general particularly frequent. 89 % of all tenses are simple present (64 % active, 25 % passive), the remaining 11 % mostly present continuous active and passive and simple future. Earlier studies found percentages for the p a ssi ve voice in science to be 32.6 %, 28 %, 26 %, 26.3 % (Sager, Dungworth & McDonald 1980: 209), thus between a third and a quarter.11 In literary works, they are much lower: only 2.2 %, or in drama 3 % (206). The reason for this seems to be that the focus is on the result, not on the subject. The passive voice also allows the result to be placed more prominently before the verb and permits shorter formulations: 'density was measured' vs 'the experimenter (or: we) measured density'. Banks (n.d.: 13–14) confirms these numbers (30.6 %) and shows that this predilection for the passive voice is noticeable from the early nineteenth century onward. It has often been claimed that this is due to a wish to have the texts look impersonal and 'objective', 12 but the above explanation to put the object of study rather than the scientist himself into thematic and emphasised position seems more plausible.13 French, German, and Russian can also use reflexive verbs and impersonal active clauses (German es) similarly; English only has the impersonal 'one', which easily sounds awkward. Turner (1962: 181–197) claimed that the high incidence of the passive voice goes back to Mediaeval Latin, providing examples from Frederick II's book on falconry (182). He concludes: 'The scientific paper […] inherited the passive from general English and from science Latin, but had to develop characteristic uses of it' (183). On the other hand, Banks (2008: 100) shows that between the eighteenth and twentieth centuries in English scientific papers (both in physics and in biology) numbers for the passive voice rise from roughly one-fifth to more than one-third of all finite verbs. Thus, it is not so clear whether this feature

11 Banks (2008: 99–111) similarly finds between 7 % and 50 % of all finite verbs in the passive mood. The averages are around 30 %, with some differences between texts on physics and biology. Similar numbers in Banks (1990: 14–15), for a corpus of eleven oceanographic English papers; I calculate from his table 32.16 % ±6.27 %, although in the sections describing the experiments the numbers were even higher: 52.5 %.

12 e.g. by Quirk et al. (1985: §3.73, p. 166).

13 So also Banks (2008: 140).

stems from Latin or developed only recently within English. Numbers for Latin scientific texts will be evaluated below and show that there is, indeed, a higher incidence (chap. 18 §4), although less strongly: 12.8 % of all verb forms are third person passive, in contrast to 9.1 % in non-scientific texts; in poetry, by contrast, the numbers are much lower (4.6 %).

Among modal auxiliaries, those indicating possibility are especially common (Sager, Dungworth & McDonald 1980: 210): 'can' and 'may' usually for possibility, 'will' for future and prediction. Non - fini te ve rb fo rms are more common in science (212–215): 35 %–39 % of verbs were found to be non-finite, compared to only 17 % in drama. One study found 19 % infinitives, 34 % past participles, and 47 % ‑ing-forms among non-finite verb forms; another 37.7 %, 26.9 %, and 35.4 % respectively. 'The chief characteristic of the ‑ing form is its grammatical flexibility. […] [which] makes it extremely popular with specialist writers' (215). It can be nominal ('rust proofing'), stand after prepositions ('by considering'),14 be used as an adjective ('operating cycle'), appear in clause reduction ('The E and B fields satisfying the Maxwell equation in free space'), express result (often after 'thus', 'thereby'), or form detached non-finite clauses ('Radioactive decay is a true first order process, the rate of decay depending only upon […]'; often introduced by 'with' or 'thus'). This last-mentioned usage combines clarity and conciseness, which are important for economy of expression. Clause reduction and detached non-finite clauses can be achieved in Latin using the ablativus absolutus, but these English clauses can be used more generally. Below, it will become apparent that non-finite verb forms are not more common in scientific Latin.

An important feature of modern English scientific language is what Banks (n. d.) calls 'hedging', that is, 'reducing the strength of what' someone 'is writing' (104), especially by means of adverbs (110) such as 'probably, generally, possibly, perhaps, apparently, conceivably, presumably, significantly, reasonably, usually'. This is comparable to our criterion (v), evidentiality or modalities, for scientific language. For English, the numbe r o f wo rd s pe r sen tence has sometimes been used as a measure of syntactic complexity.15 Unfortunately, this is a quantity that is not well defined for pre-print Latin, and cannot be used.16 But indicative vs subjunctive can be measured, as a broad indicator of main and subordinate clauses. Numbers are presented below: they differ significantly from other Latin prose only for some scientific texts, especially scholastic ones.

14 After, in descending frequency, 'by', 'of', 'in', 'for', 'on', 'after', 'before'.

15 e.g. by Banks (2008: 68).

16 Antiquity used no or very different punctuation, and mediaeval manuscripts used their own systems of punctuation. Punctuation in editions is largely the editor's and depends strongly on his nationality and taste.

Noun ph ra ses and compounds are also often mentioned as typical for scientific English. Quirk et al. show the high frequencies of noun phrases in scientific writing, especially of non-subject, complex ones.17 Sager, Dungworth & McDonald (1980: 219) point out that

nominal groups are the most appropriate vehicles of condensed linguistic expression for scientists and technologists who are trained to perceive and consequently to speak about the physical world in terms of concepts, processes and quantifiable units.

In scientific English, there are many possibilities for modifying noun phrases: (before the clause) verbless or ‑ing clauses, predeterminers (such as 'all'), determiners (articles, demonstratives); (after the clause) adjectives, prepositional phrases, non-finite clauses, relative clauses, nominal apposition, adjectival phrases ('equal to').18 Banks (2008: 63) found that nominalised processes in the English translations of Newton's works are directly derived from Latin. The method by which an action is carried out can be described using ‑ing-forms or rel a ti ve cl ause s. Result or purpose clauses introduced by 'in order that, so that, such that', adverbial clauses introduced by 'as, because, when, since', and conditional clauses ('if, then') also abound. Sager, Dungworth & McDonald (1980: 222–224) speak of 'oneway communication', i.e. no dialogues, no questions other than rhetorical ones, and so on. Relative clauses with a relative pronoun at their head also seem to be more common in science than in ordinary speech. In English, active relative clauses can be reduced to an ‑ing-form (without relative pronoun), unlike in German, French, Russian, Latin, or Greek.19

English is not very helpful for studying the use of cases (excepting the geni ti ve, which alone has kept its own form). For German there seem to be no available data on the percentages of genitives or nominatives, which would a priori seem to be the two cases most likely to be more frequent in scientific writing. Nominal phrases with the genitive are a prominent feature in the German scientific texts studied by Brommer (2018: esp. <IP_ADDRESS>).

17 Quirk et al. (1985: §17.123, p. 1350); their example is: 'At the mouth of the respiratory tube is a series of velar tentacles, corresponding exactly in position to those of amphioxus, and serving to separate the mouth and oesophagus from the respiratory tube while the lampre is feeding' (italics in original).

18 More on such impersonal constructions in chap. 22 §7 below.

19 But a similar construction exists in Arabic: it is possible to form indefinite relative clauses without the relative pronoun, e.g. 'he is a man who works in a factory' = 'he is a man working in a factory', in Arabic huwa raǧul allaḏi yaʿmal fi masnaʿ = huwa raǧul yaʿmal fi masnaʿ. For this construction, see Badawi, Carter & Gully (2004: 489).

In summary, we can conclude that the following features are especially conspicuous in scientific English today: the use of ‑ing-forms, prepositions and conjunctions, the passive voice, a lack of the first person singular, and the nominalisation of processes. We can concur with Sager, Dungworth & McDonald (1980: 277): 'Special languages are able to compress information both syntactically and lexically.' The next two chapters will test how much of this is also true for Latin.

### 18 Linguistic development studied in a general scientific corpus

§1 Using the Corpus Corporum Latin language full-text collection, large amounts of data can now be processed automatically very quickly and reasonably correctly. Starting from what was described for scientific English in the previous chapter, this chapter tries to find similar characteristics of scientific Latin and to determine whether they have changed over time. At least to some extent, the development will also be considered from the other side: what features of scientific Greek were imported into Latin? As a a comparison set, some diachronic benchmark data for normal (non-scientific) Latin prose are produced first. For the scientific texts, forty of the Latin prose texts discussed in part 2 of this book from different fields and times were chosen. As a potentially interesting out-group, four translations from Greek are included, among them a non-scientific text, the Vulgate version of the New Testament. The idea is to first find characteristics that set all (or most) of the scientific texts apart from the benchmarks, and then to try to group them and to find different scientific Latin styles within them. For this, principal component analysis (PCA; see §6) will be used. This first relatively heterogeneous sample of forty texts was chosen in order to spot general trends; it will be compared to more homogeneous samples in chapter 20, which studies scientific Latin texts from some well-defined fields. Anyone familiar with such texts will know that different scientific styles or registers do exist in Latin, so one would expect them to be detectable quantitatively.

One might doubt whether much diachronic change will be detectable, given that the Latin language became fixed in the time of Cicero to such an extent that its written form stopped developing further according to normal language development and was petrified as a Hochsprache for the two thousand years to come (chap. 16 §1). Indeed, we can hardly expect scientific Latin to change in a clear manner through time. But as Latin did take up new words and constructions through these two millennia while retaining the older patterns, it is likely that new styles of writing emerged over time; these will be discussed in the next chapter (chap. 19). Besides, as Latin has a deep memory, it may be expected that old registers of scientific writing will be found to reappear again over time in some authors.

#### Parts of speech

The concept of PoS has, of course, its own long history (see chap. 9 §4 above on Donatus, and in general Splett 2002) and is to a certain degree imposed on a language from outside. In any PoS system, there will always be cases that are hard to assign. The traditional system, which has been in use for Greek, Latin, and their descendent languages for more than two millennia, uses eight or nine parts of speech: noun (N), pronoun (PRON), adjective (ADJ), verb (V), adverb (ADV), conjunction (CONJ), preposition (PREP), interjection (INTER), and article (ART), the last of which is lacking in Latin. The Corpus Corporum Latin PoS tagger (TreeTagger, with language-specific data compiled by Gabriele Brandolini; http://www. cis.uni-muenchen.de/~schmid/tools/TreeTagger) uses this system and further distinguishes between some subtypes, e.g. among CONJ and PRON, verbal moods and the verb ESSE among V, and nominal cases among N. There are new approaches to defining PoS these days, designed to be applicable to all human languages. Universal PoS tags (UPOSTAG; http://universaldependencies.org/u/pos) is certainly the most successful such attempt. Table 3 compares the traditional system to UPOSTAG.

Table 3: Comparison between classical PoS and UPOSTAG.

The rarer PoS italicised in table 3 (proper names, interjections, numerals) will not be used in our studies; among the rest, there is very little difference – basically only that UPOSTAG uses subordinating and coordinating CONJ as two different PoS and distinguishes particles from adverbs. Others have just received more general names (especially 'adpositions' instead of PREP). But, of course, the application of this general system to individual languages is still not always unambiguous. Thus, DET ('determiners') is wider than ART ('articles'), and it may be debated whether any words in Latin qualify as such (e.g. is, meus, omnis). Another major problem is that ADJ, PRON, N, and V sometimes overlap: for instance, omnis can behave as ADJ, PRON, DET, or even N. Another unclear case are participles (PTC): are they ADJ or V? The automated tagging is unable to differentiate between such difficult cases: it will, for instance, always assign PRON to omnis, 1 and will treat lexicalised PTC as ADJ, others as V.2

In order to obtain a better understanding of precision and usability, the automated results of TreeTagger were evaluated by comparing them with the manual

1 This is clearly wrong in many instances. But it was not feasible to program a solution able to distinguish between cases.

2 Depending, obviously, on the lexicon used. In reality, cases such as the following should be differentiated: docta puella (ADJ) vs discipulus doctus est (V). Again, this could not be automated.

PoS tagging done by the Laboratoire d'Analyse Statistique des Langues Anciennes (LASLA)3 for Cicero's De officiis. Corpus Corporum (CC) uses the Loeb edition digitised by Perseus as base text, LASLA the edition by Karl Atzert (Leipzig: Teubner, 1932). Slight differences are therefore to be expected simply because of the different base text: the Atzert edition has 386, or 1 %, more words than Loeb.4 Table 4 presents the numbers.

Table 4: Comparison between LASLA (manually determined) and CC (automated counting) for some features in Cicero's De officiis. The cases were counted among N only and are given as percentages of all N.

Among the cases, the rare vocative and locative were not considered, and the ablative and dative only in their combined sum (as CC distinguishes them very poorly). The figures for CC and LASLA correspond well for some of the values (N, V, IND), but some differ conspicuously due to differences and sometimes mistakes in counting (marked in red in the table).

3 The LASLA corpus data are freely available online (http://cipl93.philo.ulg.ac.be/OperaLatina/ users/MainInterface.aspx) after requesting log-in details. Their manual PoS tagging is based on the Forcellini lexicon. I thank LASLA, Université de Liège, for sharing their excellent data.

4 This is also partly to do with different definitions of words. For instance, filioque counts as two words for LASLA, as one for CC.

108, igitur 103, autem 266, vero 43, enim 269) renders the values at least closer (–7 %).

In conclusion, it seems that the results are reasonable for a fully automated counting and should be acceptable as a basis for the studies to come (although there is certainly room for improvement). As the same system was used for all texts, the results are at least consistent among themselves: the same errors will apply to all of them equally.

#### Corpus approach

§2 As the main basis of comparison, five large Latin ad hoc prose corpora were generated for five important time periods of Latin. The corresponding texts were loaded as TEI xml files into Corpus Corporum (CC), where automatic part of speech (PoS) tagging was performed using TreeTagger, and the resulting data downloaded again from the server as PoS-tagged TEI xml files which could be studied further with linguistic Unix tools (sed, grep, and the like). The tagging produces data of the form: <w type="PRON:DEM" lemma="hic">his</w> for each word in the text, thus assigning each word (here his) its lemma and a type including its PoS. If the lemma in question is not known to the database, the type will be unreliable, for instance <w type="ADJ" lemma="unknown">Chananaea</w> (type should be N:nom, not ADJ). 'Unknown' words are mostly proper names; they were removed from the samples for our studies. The entire process was based exclusively on open-source software.

Basic data about these ad hoc corpora is presented in table 5.5 Additionally, some specific, non-scientific corpora were compiled in order to permit compari-

5 All texts are in Corpus Corporum, where further information about them, including references, can be found. These ad hoc corpora contain all prose texts from the respective corpora and time ranges (in 2018); any lines of verse in corpora 1–5 were removed. Only texts of at least 1,000 words in length were included. The author's death date or floruit (as available in CC) was used as an ap-

son with potentially interesting other registers. A large corpus of metrical texts (mostly hexametric), and smaller ones of the Digesta (see chap. 8 §3), a small collection of charters from the High Middle Ages, and the New Testament Vulgate (as a non-scientific text that was translated from the Greek) were used. It became clear above how important jurisprudence was for the development of Latin as a language of science, so the Digesta may reveal interesting traits. The Vulgate is included for its great importance for Christian Latin in general (see chap. 9 §2). The language of scientific poetry will be compared below, as will that of historiography, whose language may exhibit similarities with charters (both in chap. 20). The language of these additional text collections differs greatly from that of the diachronic prose texts.

Table 5: Information on the five benchmark samples and out-groups to be used below.

9 The Digesta were collected by order of Justinian in 530–533. 9,139 is the number of excerpts, 38 is the number of authors cited in the Florentinus list. See chap. 8 §12 above.

proximation to date the texts. Obviously, undated texts were not used (CC currently has date tags for only some 85 % of its texts).

6 The average of the five prose samples is 5.95 ±0.32 letters. Mediaeval and poetic texts seem to have a shorter average word length than classical and early modern ones.

7 Comprising the texts in corpus 15 'Poetica' on CC, plus Vergil and Ovid. The longest texts are (in descending order): Michael Hospitalis, Carmina; Carmina Burana; Marcello Palingenio Stellato, Zodiacus vitae; Ugolino Verino, Carlias; Francesco Petrarca, Africa; Rafael Landívar, Rusticatio mexicana. Many of these texts were written by Italian humanists.

8 Metrical Latin poetry is very conservative, so it was decided to bring texts from different times together. We will compare the numbers to numbers obtained for Vergil and Ovid only. They are surprisingly similar.

Parameters that may be important for scientific language were determined for the five large benchmark samples: distribution of PoS, moods, cases, suffixes, and subordinate clauses. To begin, the PoS distribution was calculated for each text within the five large diachronic samples, then values were averaged per group. This made it possible to determine standard deviations within samples, which indicate how much variation there is. The PoS distribution has changed only little over time (table 6 and fig. 31) – mostly not beyond the standard deviation range for the classical sample. The amount of verbs employed diminished somewhat through this timespan, but the amount of nominal PoS (defined as N + ADJ + PRON) rises perceptibly only in the early modern period – thus, Mediaeval Latin can hardly be said to become more 'nominal', even though the numbers of N do rise somewhat. Only the numbers of PREP rise after the first sample to a value beyond 1 stdev of the deviation within that sample. This is the only PoS consistently outside the standard deviation ranges. ADJ become much more frequent in early modern times, N become slightly more common with time, while V and PRON become less so. Averaging the PoS values for the five samples shows that the classical sample differs most strongly from the average and thus from the (mostly Christian) rest.

Table 6: Average and standard deviation for PoS over all texts in the five ad hoc prose samples as percentages of the total.Values more than 1 stdev outside the antique value are highlighted in colour:12 red means less than the antique average minus 1 stdev, green more than the average plus 1 stdev

10 Digitised by the ALIM project, http://it.alim.unisi.it. The non-standardised spelling complicates the automatic tagging, and the quality of the results will be worse than usual.

11 Ed. Tweedale; see chap. 8 §2 above.

12 The values add up to only 98 %–99 % of all words because TreeTagger also tags the few abbreviations, interjections, and Roman numerals in the text.

Table 6: (continued)

Fig. 31: PoS distribution over time. The N + ADJ + PRON value was halved to fit the scale. Values on the y-axis in percent.

The PoS values provide a first impression of how much (or rather, how little) variability is to be expected in Latin over the centuries. A second table (table 8 below) will compare the cases, the most important moods of the verb, and some other specific features that may be revealing for scientific language. Above (chap. 17), it was observed that scientific English tends to favour passive constructions and noun phrases. The latter correspond mostly to compounds in Greek and German (see chap. 9 §5), but in Latin they are often expressed by relative clauses. Therefore, the relative pronoun qui (REL) and the verb esse, which is often involved in such constructions, were also counted. In the wake of Greek usage, sentence-modifying or discourse particles may be another feature typical of scientific Latin:13 at, autem, enim, ergo, igitur, nam, and vero were counted. Kroon, who studied these particles in great detail, categorises them in a table (see table 7).14

Table 7: Latin sentence-modifying particles, from Kroon (1995: 373).

Another feature of some kinds of Latin often criticised by humanists (chap. 12 §2) is the use of suffixation, which will be discussed below as a surrogate for compounding (chap. 24 §7). In order to obtain numbers, a sample of seven especially common nominal suffixes (‑tio/‑sio, ‑tas, ‑itia, ‑ntia, ‑mentum, ‑tor/‑sor, ‑tudo) and eight adjectival ones (‑alis/‑aris, ‑bilis, ‑eus, ‑icus, ‑inus, ‑ivus, ‑orius, ‑osus) was used. Promising suffixes for this purpose had already been selected in Roelli (2013: 334–335, based on Leumann 1944).15 The suffixes' rôles can be briefly described as follows. For the nominal suffixes:

13 Ramshorn (1842) presents larger groups of such modifiers. Adversative particles: sed, verum, vero, at, atqui, autem; explanatory ones: nam, namque, enim, etenim; concluding ones: itaque, igitur, ergo, eo, ideo, idcirco, propterea, (pro)inde, quare, quamobrem, quapropter. I used only the seven most important ones, those studied by Kroon (1995).

14 Some caveats in Langslow (2000b: 559), especially for medical Latin.

15 Helander (2014: 47) studies a similar list for the adjective suffixes.

• -icus, -alis/‑aris, -inus (added to nominal roots): express a relationship (e.g. pluvialis).16

The use of these suffixes has, on the whole, remained constant in Latin. Only very rarely did special, new constructions for some of them arise in Post-Classical Latin. For instance, the suffix ‑ivus plus objective genitive is often used in the High Middle Ages in a special syntagm (e.g. novum testamentum est veteris impletivum).17 There are also suffixes derived from roots, such as ‑ficus, ‑formis, ‑oides, that become frequent in early modern times. It is obvious that a set of such suffixes that can enhance language systematically is very useful for scientific expression. In fact, most of these suffixes are still very common in scientific English today.

Ablativi absoluti may be another useful feature for scientists, as they make it possible to state the circumstances of the main action in a condensed way. An attempt was made to estimate their numbers automatically. Of course, counting this special feature of the Latin language automatically is not a trivial matter; in some cases it even remains unclear to Latinists whether an ablative construction is to be read as an ablativus absolutus or as another kind of ablative (especially an instrumental one). My tentative approach was to count all occurrences of two ablative forms with a maximum of two other words in between and no strong punctuation, where one of the two was a participle. Checking a small sample shows that most ablativi absoluti were indeed found, but of course there were also some false positives. A comparison with manually determined values by LASLA shows that our amounts tend to represent between 80 % and 150 % of the true value. However, as the determined numbers can, for instance, differ by a factor of ten between Pliny and Anselm of Canterbury, the numbers may still be of some relative value. The numbers are included here in the knowledge that they are not very accurate.18 Late Antiquity has lower numbers than the rest, which have rather similar average numbers, although stdevs are large, indicating that authors differ considerably in their frequency of employing the ablativus absolutus.

The last feature in the table is textual entropy.19 As in entropy defined in physics, the degree of orderliness of a text string is measured. Whereas very orderly

16 Words with these suffixes were counted using the Linux grep tool; they were required to be the correct PoS and have at least two more letters (thus excluding words such as divus, vivus, binus, etc.). For ‑icus, words in ‑ficus (compounds with facere) were excluded. Some false positives, such as semivivus, had to remain in the count and will distort the result slightly.

17 As Stotz (1996–2004: VI, §86 = vol. 2, p. 356) points out.

18 I thank Alexandra Bünzli for writing the perl script I used.

19 Proposed by Shannon (1951), then used by Evrard (1967: 81–85), this number is calculated as the negative sum –Σ [fj × log2 (fj)] over all lemmata j, where fj is the relative frequency of lemma

sequences of strings are at best very uninteresting and predictable texts, say est est est est, real and interesting texts are less predictable and monotonous. The entropy value is a measure that indicates the unpredictability of words in a text, the 'news value' of the next word in the sequence; it is measured in bits of information per word. Values tend to range between 7 and 11 bits. The entropy value rises slightly with more tokens; for texts with too few tokens, the value depends significantly on the text's length and therefore makes little sense. Bentz et al. (2017: 14) feel that the problems are not present above 50,000 tokens. The values below were calculated only for texts longer than 10,000 words.20 The graphic in figure 32 makes this choice plausible.

Fig. 32: Doubly logarithmic (log10) plot of entropy values for all texts in PL: the x-axis shows the entropy value, the y-axis the number of tokens (words). The red curve shows the maximum possible entropy value (log2 of the number of tokens), representing the case that each token is used exactly once. Above y-value 4 (10,000 tokens), the real values no longer seem to follow the maximum possible value closely.

The first thing that hits the eye in table 8 is that the standard deviations for all moods and cases are relatively high: different authors differ strongly, even within the same period. Nonetheless, there are some parameters that deviate on average more than 1 stdev from the classical value (again, highlighted in colour). The

j. The same formula is used to calculate entropy in information theory, hence the name. More precisely, this is uni-gram entropy, as defined in Bentz et al. (2017: 5, formula 3).

20 For the five corpora in ascending chronological order, this means 40, 242, 161, 375, and 18 texts respectively.

amounts of IND rise significantly in the Middle Ages and drop even more afterwards, when humanists overcompensate in employing this un-classical usage. SUB exhibit the inverse behaviour. INF drop in the Middle Ages while PTC rise. The former change is very conspicuous, such that lower numbers of infinitives might be a typical characteristic of Mediaeval Latin. As ACC numbers also drop somewhat, this may be connected with the rarer use of the accusativus cum infinitivo. Interestingly, the humanists have somewhat higher numbers of INF again, but use PTC even more than Antiquity. This may be an attempt to imitate Greek, a language very fond of participle constructions. In the Middle Ages, the high PTC numbers may point to influence from biblical Latin (although the value for our NT Vulgate sample is only slightly higher than the benchmarks).

Table 8: Some more specific, potential characteristics for scientific language. The verbal forms are given as percentages of all V, the nominal ones as percentages of all N. For details, see the main text.

The use of cases remains relatively stable for NOM and ACC, except that the sample from Late Antiquity exhibits a rather high percentage of NOM and a correspondingly low number of ABL/DAT, possibly because these cases were becoming rarer in the still-spoken language. The number rises again from Carolingian times onward (when grammar was learned in school). Most interesting for scientific language may be GEN, which is the only case that becomes more than 1 stdev more common as time passes, and even remains so in the humanist sample. This may be one of the reasons why Mediaeval Latin gives the impression of being more 'nominal', 21 as 'nominal' GEN constructions contrast with 'verbal' ACC constructions. Unexpectedly, both ESSE and the REL pronoun become rarer as time passes, although strongly so only in the humanist sample. Constructions with relative clauses and a high concentration of the copula will have been perceived as 'scholastic' and worth avoiding, although it can now be seen that they were even more common in classical times. The third person passive (singular and plural) is somewhat more common in the Middle Ages than before or after, but it is the first person singular that surprises by being a lot less common in the Middle Ages. Interestingly, the numbers of the third person passive are highest for the twelfthcentury sample, at the beginning of scholastic writing. Nominal suffixes are clearly another feature that was perceived as 'scholastic' and avoided in the humanist sample, though adjective suffixes apparently were not.

More detailed data about these suffixes are shown in table 9 and figure 33. Because their occurrences are usually low in number, and chance fluctuations are thus to be expected, averages across all texts were used (thus, no longer counting per text then averaging the numbers obtained for each text in one corpus), except for the first corpus (Antiquity) in order to still have a stdev value. The first and third rows in table 9 thus reflect the difference one will generally have to expect between these two ways of counting. It is mostly small (very small for the PoS in table 6 above, numbers not printed); only ‑bilis, ‑ivus, ‑osus; ‑itia, ‑ntia exhibit a difference of more than 10 %, indicating that their frequencies were especially variable among antique authors and texts. Standard deviations are in general high; only ‑alis and ‑tio consistently reach values more than 1 stdev higher than in the classical samples in the Middle Ages and early modern times. But, presumably due to criticism by humanists, some frequencies drop significantly in early modern times compared to the Middle Ages, especially for ‑tas, ‑ntia, ‑bilis – most abruptly for the first.22 Some others, which were apparently not consciously asso-

21 See chap. 11 §2 above: Stotz on scholasticism's 'ausgesprochenen Nominalstil' ('pronounced nominal style').

22 This suffix was especially targeted by the humanists, e.g. Lorenzo Valla, quoted in chap. 12 §2 above.

ciated with 'scholasticism', such as ‑tio, ‑alis, keep rising through the entire sample period; a few (‑eus, ‑ivus) rise decidedly in early modern times; and some remain quite constant (‑mentum, ‑osus, ‑tudo, ‑itia).23

Table 9: Occurrences of suffixes in ‰ of words. The first row was measured per text and then averaged; the second row contains the stdev over all texts in the same corpus. All further rows are simple averages over all texts in the respective corpus. Thus, the second 100 BC–AD 200 row is the one that should be compared to the numbers from the other corpora.

Finally, a closer look is taken at subordination, which seems to be of special importance for the well-structured, syntactic connection of scientific thoughts. Total numbers are counted in table 10 below.24 The general numbers above (table 6) have shown that numbers of subordinating CONJ remain quite constant, before dropping significantly in the early modern sample. A selection of eight CONJ:S

23 These results are comparable to those in Roelli (2013), which were acquired from a much smaller sample.

24 The common ones in the benchmark samples are antequam, cum/quum, donec, dum, dummodo, etiamsi, etsi, igitur, ne, neve, ni, nisi, nonnisi, posteaquam, postquam, priusquam, prout, quam, quamquam, quamvis, quando, quandoquidem, quanquam, quasi, quia, quo, quod, quominus, quoniam, si, sin, siquidem, tametsi, tamquam, tanquam, ut.

and two conspicuous PREP, sometimes in semantic groups, was counted to this end (qui was already included in table 8 above as REL).

Fig. 33: Suffixes in the five samples in ‰. The values of the two most common nominal suffixes, ‑tas and ‑tio, have been halved to fit the scale.

Table 10: Numbers for some subordinating CONJ in ‰. For the differences between the first and third rows, see the comments on table 9.

25 Corpus Corporum cannot distinguish between the two cums. Roelli (2013) determined that an average 74 % of occurrences are of the conjunction; the total number has been multiplied by this value. The accuracy of these numbers is, therefore, worse than that of the others, as the ratio is likely to change depending on the author.

26 Both quoad and quo ad were counted, the latter orthography being rather rarer in our texts.

Table 10: (continued)

As expected, many of these numbers are reasonably stable through time (e.g. for quasi, tamquam and cum; slightly falling for ut), but often the stdev is high. Some seem to be especially 'mediaeval': quia, quoniam, and secundum, although the values from the early modern corpus are still a lot higher than the classical ones (except quoniam); quoad behaves in exactly the opposite manner, although it is much rarer. Indeed, quia and quoniam are used much more profusely in the Middle Ages in situations where Antiquity would prefer other constructions, especially the AcI (it was found above that the Middle Ages have conspicuously lower numbers for INF).27 The Croatian early modern authors seem to avoid hypotaxis quite generally, possibly because it was felt to be a trait of mediaeval, 'barbarous' Latin. Thus, their numbers for relative sentences and si and nisi are much lower than the mediaeval and the antique values, which are similar to each other.

These numbers obtained from the five large corpora representing five important periods will now serve as benchmark values to compare against the scientific samples.

#### General scientific corpus

§3 The table below (§4) summarises important data about the forty texts chosen for this general, diachronic scientific corpus and provides some initial linguistic information about the texts.28 The texts cover rather different topics and may thus

27 See Stotz (1996–2004: IX, §106 = vol. 4, pp. 397–398 on quia; IX, §107 = vol. 4, pp. 398–399 on quoniam). His observation (p. 398) that quoniam remains significantly rarer than quod and quia is confirmed by our numbers.

28 Details about the editions used can be found in the bibliography. All texts are in Corpus Corporum.

serve to illustrate general trend developments. They were chosen as relatively original treatments of a scientific subject, excluding mere schoolbooks, technical manuals, translations, and texts written in verse. Some scientific texts translated from Greek are included in the study as out-groups: four texts translated under different circumstances and at different times (listed at the end of the table). After this table listing the texts used in the sample, a table with the PoS distribution and another one with the other parameters discussed above for the benchmark samples follow. Average figures of the more homogeneous samples studied in the next chapter are also displayed in the tables: text samples from arithmetic, historiography, and didactic/scientific poetry.

In order to gain an insight into the innovated technical vocabulary, words not occurring in Antiquity were counted in the last 5,000 words (thus avoiding the special language used in prefaces) of each work in this corpus.29 In order to find them, an 'Antiquity word-list' was first generated from texts by authors between 100 BC and AD 200 from corpora 4 and 5 in CC (171 texts, yielding some 257,333 words), which was subtracted from the word-lists of later texts in the sample.30 The resulting word-lists of post-antique lemmata for each author are printed in appendix 1 at the end of this book. The 31 scientific texts after AD 200 in total contain 917 [3,032] lemmata [occurrences] not extant in the sample for before AD 200. Among these were 294 [1145] ADJ, 20 [37] ADV, 465 [1,544] N, and 138 [306] V. Thus, at least these post-antique words do show a decidedly nominal character. The numbers vary strongly depending on the scientific field. Logical or philosophical texts (Boethius, Anselm, Spinoza) only rarely use new words, unless they belong to university scholasticism (Suárez). Indeed, the author who uses by far the most such words is the twentieth-century Jesuit Boyer. Among the humanist authors, some exhibit lower numbers (Cardano, Vesalius, Descartes, Newton, Kretschmann), but even avowed classicists such as Vesalius cannot help using some late words in a field like medicine. The comparison with the out-groups shows that, interestingly, the Vulgate uses quite precisely the same number of new words as the average of the scientific texts.31 Since the numbers depend

29 A similar experiment with only classical authors (Cicero, Caesar, Cornelius Nepos, Pliny the Younger, Quintilian, Ad Herennium, Ps-Caesar, Livy, and Sallust, in total some 54 texts – compare Krebs, who recommends the 'pure' style of the later authors Pliny the Younger and Quintilian) produced too many words, many of which are seemingly completely normal Latin that just happened not to be present in the relatively small sample of 'authoritative' texts. They are not included.

30 Some manual clean-up and lemmatising of words unknown to Corpus Corporum's lemmatiser had to be done.

31 This procedure was also applied to the Vulgate text: 41 lemmata [101 instances] were found, also listed in appendix 1.

strongly on the scientific field and possibly also on the part of the work from which the 5,000 words were taken, they are not used as a parameter for the plots below.32

The list in the appendix shows that Latin scientific language created nouns, adjectives, and verbs in large numbers, but there are very few new uninflected words (aptota).33 The only one discussed in this book is the scholastic pseudoarticle ly (see chap. 24 §6 below). It remained marginal and was no longer employed in early modern times. Nevertheless, it will become clear that some aptota are much more common in scientific writing, especially PREP and in some authors ADV. Some cases are conspicuous, for instance secundum. A look at the entries in Schütz yields, besides ly, only aptota that are adverbs derived from adjectives, in -e, -ter, and some less regular ones in -im (capitulatim, coniunctim, copulatim, disiunctim, divisim, subalternatim, summatim). It may be a generalisable finding that technical languages create new vocabulary nearly exclusively among the open (inflectable) word classes, hardly ever among the structure words of a language. The latter would constitute a much deeper intervention in language, on the way toward language engineering.

§4 There follow the tables with information about the texts used and the figures obtained for them (tables 8–10). The texts of translations from Greek in the second part of the table are included for comparison. The first column indicates the text and edition used for the calculations. Often these are not the latest or best critical editions but those that were available in digital form.34 It is not to be expected that the differences would result in greatly differing numerical values. The scientific field with which the text is concerned and the text's style are also briefly described in the table. For deeper information, the reader is referred back to part 2, where the works were discussed. The brief assessment of the type of language used is, of course, rather subjective. It is meant merely as an indication what the Latin these texts use 'feels' like to the reader.

32 If the entire process of finding post-antique lemmata could be automated, average numbers for any sample of 5,000 words could be calculated. But at present, listing these words is still partly manual work.

33 On aptota in Indo-European, see Dunkel (2014).

34 Restrictive copyright laws and editorial policies make it impossible to work with the latest editions in many cases. Of course, the best editions available were used in part 2 above.

35Red indicates less than the average minus 1 stdev, green more than the average plus 1 stdev.

36The number of words was counted in thousands. The shortest texts are around 8,000 words; most are much longer.

Table 11: (continued)

Table 11: (continued)

37 Average word length of these texts: 5.84 ±0.29, somewhat shorter than the benchmark: 5.95 ±0.32.

38 Averages: 39.4 ±24.5, 95.3 ±50.3.

Table 12: PoS values for the scientific texts in comparison to the benchmark general texts, as percentages. The colours green and red are used to show differences from the average of the five prose benchmark texts that exceed 1 stdev.39 Values more than 3 times the stdev from the average are underlined. The average and stdev values from the arithmetic corpus (studied in the next chapter) are included for comparison.

39 The samples are treated as a single text. This explains the (small) differences from the numbers in table 6 above.

#### Table 12: (continued)

#### Table 12: (continued)

Table 13: The first four values, the 1st person singular, and the 3rd person passive are measured as percentages of all V per text, the cases as percentages of N (the rare cases VOC and LOC are not included). All other values are in simple percentages, except ABL ABS (which is given in occurrences per 1,000 words) and entropy (in bits per word). Colours are used as in table 12.

Table 13:

(continued)

Table 13: (continued)

#### Characterising scientific Latin texts in contrast to other texts

§5 Tables 12 and 13 have presented numerical data about PoS and features that could be relevant for scientific Latin in light of what was reviewed (chap. 17) for scientific English. They show some traits rather clearly. In general, the composition of PoS differs very strongly between prose and poetry samples. All values for the poetry samples are outside 1 stdev of the benchmark prose samples: poetry has more ADJ, N, and V, but fewer CONJ, PREP, and PRON. Non-scientific poetry additionally has fewer ADV; scientific poetry is inconclusive in this respect. The charters show some traits typical for substandard Latin: high numbers of CONJ, PREP, but also a very nominal language (low V, high N, high ADJ). The Vulgate shows some similar traits (high CONJ and PRON), as do the Digesta (high CONJ, though not subordinating ones; high V; low ADJ, ADV, PRON), although these two samples clearly represent very different types of Latin. Within scientific prose, the translations from Greek exhibit some common features (although they are translations of very different texts), in particular more CONJ and PRON, fewer N. This may represent general differences between Greek and Latin. The scientific sample has fewer V, N, and PRON, but more ADJ, ADV, and PREP. CONJ are more common than in the benchmark in many texts, but less so in others, producing an average value close to that of the benchmarks.

The more specific parameters in table 13 also show significant differences between the average of the five benchmark corpora on the one hand and poetry or translations from Greek on the other, and, less clearly, also differences between the scientific texts and the benchmark. Verbal and nominal subcategories (the first eight columns) produce less clear differences than the other parameters. Poetry has fewer SUB but more PTC (and to a lesser extent INF), fewer GEN but more NOM and ACC; the translations more NOM, fewer GEN, more IND, and surprisingly fewer PTC (although this depends strongly on the author). The scientific texts show less clear trends for these eight parameters on average: more NOM, fewer ACC and ABL/DAT. Only the amount of NOM differs strongly; this case is much more common. The verbal parameters are on average within 1 stdev of the five benchmark samples. But many of the individual texts are outside the normal range, some above, some below. The next chapter will try to find groups of scientific writing styles to match such cases.

The twelve more specifically chosen parameters differ more clearly. They were selected from a greater number of similar parameters, many of which did not differ markedly from the benchmark (somewhat surprising in the case of subordinating CONJ and word length, which are the only ones printed). Poetry tends to have lower numbers for all of the values shown, except ABL ABS and entropy, for which it has much higher values (ADJ-SUF, PRON:POSS, 1st SG are within normal range); the translations show quite the inverse behaviour (except REL). The scientific texts behave more or less like the translations from Greek, except that REL and 3rd PAS are also higher but subordinating CONJ are within range and N-SUF are lower. Parameters that differ strongly in both this scientific corpus and the arithmetic one (described in the next chapter, but average numbers are already included in the tables above) are ESSE, 3rd PAS, ADJ-SUF, and REL (all higher) and 1st SG, PRON:POSS, ABL ABS, and entropy (lower). As a first result, we may consider these values as significantly different in scientific Latin.

Among the three out-group corpora, not very surprisingly the charters often use the first person singular and the indicative as well as the ablative and especially the ablative absolute. If the many 'unknown' place and person names were included, the numbers of ABL might rise even further. They also use PTC more often than usual. The Digesta use SUB and INF conspicuously often; quite the opposite is true for the Vulgate, which on the other hand betrays its Greek origin by the high numbers of modifiers. Interestingly, suffixes are rare.

Among these data, a progression can often be observed: poetry – scientific poetry – general prose (five benchmark corpora) – the scientific texts – the five translations from Greek. Sometimes the arithmetic sample from chapter 20 below follows at the end, as can be seen in table 14.

Table 14: Progressions for some values. Green marks the maximum value, red the minimum value (not including the arithmetic sample).

Table 14: (continued)

For some parameters the scientific texts show extreme values (which would seem to be especially typical for scientific texts): PREP, PRON:POSS, 3rd PAS, N-SUF; often the arithmetic sample shows even more extreme values in these cases. The scientific poetry text sample tends to behave like other poetry. Only rarely does it behave more like other scientific texts; this is especially the case for PRON:POSS and 1st SG. The next chapter (chap. 19) will try to name subgroups in the general scientific corpus according to characteristic parameters and thus come back to types of Latin encountered in part 2 above.

§6 Principal component analysis (PCA)40 is now applied to these data in order to plot them and to render these (or other) groups more clearly visible. The closer points are situated on the plot, the more similar these texts are in the parameters considered. The idea of PCA is to project multidimensional data onto two dimensions in the 'best' way, that is, preserving as much of the variation as possible. In order to achieve this, the n-dimensional data – for instance consisting of n of the above parameters for each sample – is transformed orthogonally in the direction of the maximal variation within the data, producing the first dimension, the second dimension is the dimension with the highest variation under the constraint of being orthogonal to the first one (and so on, but usually only two dimensions are plotted). 'PC1' in the plots thus shows this first and most significant component; the accompanying value in the graphics the percentage of the entire variation; 'PC2' the second component. In our samples, these two 'best' dimensions together tend to represent between 60 % and 70 % of the entire variation, in other words only about two-thirds of the entire variation. The components themselves are made up of linear combinations of all n parameters and, therefore, do not represent an intuitively meaningful quantity.

40 Clustvis (https://biit.cs.ut.ee/clustvis), a handy free online tool based on R, was used. The tool automatically turns values into standard scores (average 0, stdev 1), so no prior calculation of these is required.

The following plots depict the forty scientific texts (numbered chronologically) and those translated from Greek (blue) together with the five benchmark samples (green, boxed); the out-groups poetry (red), Digesta, charters, Vulgate (italics); and the corpora that will be studied in chapter 20 (arithmetic, historiography, scientific poetry, medicine, all in pink). Additionally, there are three groups of texts from within the forty texts named 'classical', 'scholastic', and 'new' science (also pink).41 They may represent especially typical subgroups. Despite the fact that Latin is (rightly) seen as a very homogeneous and stable 'fixed' language, clustering separates some major groups fairly well. The PoS work quite well for grouping, the values that were found to be specific for scientific texts even better. What we would expect from a 'good' clustering separating scientific texts from others is that

Of course, we also have some preconceptions from the scientific approaches and periods described in part 2 above: for instance, scholastic texts are expected to be grouped together.

First, a simple two-dimensional plot N against V is presented (fig. 34, without PCA). Such a simple plot can already separate the metrical texts quite well (top right), and puts the benchmark corpora approximately in the middle, the Greek translations in the bottom left, and the scholastic and arithmetic texts centre-left. The average value for all forty scientific textsin the sample ('avg 1–38') 42 lies slightly to the left of the benchmark (indicating fewer nouns), close to the medical sample and to the Vulgate. The historiographical sample lies on the other side, toward the poetic texts. Some technical artes authors also group to the right (more N): especially Pliny, Rabanus, Vitruvius, Bede, Isidore. In general, it would seem that 'new' science texts use fewer V, scholastic ones (unexpectedly) fewer N, juridical texts (Digesta, Gaius, Pauli sententiae) more V, and at least Pauli sententiae more N.

A more sophisticated plot (fig. 35) for the same texts uses all seven PoS (ADJ, ADV, CONJ, N, PREP, PRON, V); the seven-dimensional data is optimally fitted to

41 They comprise respectively Varro, Cicero, Seneca; Albertus, Aquinas, Ockham, Suárez; Copernicus, Vesalius, Galileo, Newton.

42 A single number is used for the two Boethius texts and for the two juridical primary texts, so the numbering reaches only 38, even though there are 40 texts.

Fig. 34: Simple N vs V plot. Details in the main text.

two dimensions using PCA. Interestingly, the plot is quite similar to the simple N vs V plot. Again, it sets the poetical texts quite clearly apart from the rest. The translations from Greek, too, are on the other side of the plot. The scientific texts tend to be below43 the benchmark samples, though the juridical and the 'classical' ones do not. The scholastic ones are again more to the left, the technical ones and those of the Scientific Revolution to the right. All in all, these PoS results seems interesting, though not very distinctive for scientific Latin in general.

In a further plot (fig. 36), all eleven parameters introduced above as potentially typical for scientific Latin are used: ESSE, REL, CONJ:S, PRON:POSS, 1st SG, 3rd PAS, ADJ-SUF, N-SUF, modifiers, ABL ABS, entropy. The non-scientific texts are now much more clearly separated from most texts of the scientific sample; indeed, none of them are plotted within the greyed-out area enclosing the five non-

43 The coordinates in these plots are relative values without an intuitive meaning, so 'up', 'down', and similar terms are merely relative terms. The plots' orientation was chosen to be such that the translations from Greek were always at the bottom left in order to facilitate comparison.

Fig. 35: PCA plot using the amounts of the seven PoS.

scientific benchmark samples. To the far left, the scholastic texts (including their 'father' Boethius) group quite neatly. Neo-scholastic ones (Suárez and Boyer) are between them and the centre of the plot. Many texts from Antiquity have a tendency to remain close to the five benchmark samples; in other words, their language is less distinctive than that of later scientific texts, for instance Varro, Cicero, Augustine, Seneca, Donatus. The two Neo-Latin human science texts (Kircher and Kretschmann), the charters, and historiography are located at the other side of the plot, close to the poetic texts. The translations from Greek are scattered all over the left-hand side of the plot, though the humanist translator Ficino ends up away from the others. Technical/encyclopaedic texts end up at the top centre (Vitruvius, Pliny, Bede, Isidore, Cardano, Vesalius, Galileo, Newton), the Vulgate at the bottom, far apart from the rest. The scientific corpus as a whole and the arithmetic corpus studied in the next chapter are situated in the centre together with some apparently 'inconspicuous' scientific texts: Gaius, Eriugena (surprisingly), Guilelmus de Conchis, Hugh of St Victor, and Roger Bacon, among others. Marius Victorinus, Anselm, and Lullus lean toward the translations from Greek.

Fig. 36: PCA plot of all eleven parameters from the right half of table 13.

In the hope of getting an even neater result, now (fig. 37) only those parameters are used that differ at least 3 stdevs for the average of the forty scientific texts from the benchmark average. These are NOM, ESSE, PRON:POSS, 1st SG,44 3rd PAS, ADJ-SUF. The five benchmark samples remain together (Varro, Cicero, Seneca, Augustine close to them); the poetry, Vulgate, and charter out-groups are far to the right. Technical texts together with texts from the Scientific Revolution are quite neatly apart from one another and from the benchmark, but it is the scholastic ones that are most clearly separated from the rest. Medicine and arithmetic are in between, medicine closer to the texts of the Scientific Revolution, arithmetic to the technical ones. Thus, the more practical or experimental sciences stay together, in contrast to the more theoretical ones. Again, early modern human

44 Obviously, 1st SG cannot be lower than 3 stdevs of 4.44 ±1.93, which is due to the high stdev in the benchmark samples, which is again due to much higher amounts of 1st SG forms in the classical benchmark sample than the others. The scientific texts are in many cases very much lower (below 1), so including this value seemed warranted.

scientists and historiographers are close to one another and the benchmark samples; the charters are now somewhat further off.

Fig. 37: PCA plot of the parameters for which the average of the scientific sample differs more than 3 stdevs from the benchmark: NOM, ESSE, PRON:POSS, 1st SG, 3rd PAS, ADJ-SUF.

For a final plot, the values whose averages in the forty scientific texts or in the arithmetic sample differ more than 3 stdevs from the benchmark were used (see fig. 38), a set of parameters that will be used again in chapter 20. These are ten parameters: ADJ, N, PREP, NOM, ESSE, PRON:POSS, 1st SG, 3rd PAS, ADJ-SUF, entropy. Many things remain the same as in the previous plot, but the groups of scholastic versus Scientific Revolution vs 'normal' texts become clearer (highlighted by green lines).45 The arithmetic sample is now clearly within the scholastic group.

45 Moving the near-vertical line somewhat further right would include Guilelmus de Conches, Suárez, and Spinoza in the scholastic group. These authors do indeed seem to lie somewhere between scholastic and more 'normal' Latin.

Scientific texts from Antiquity and human science texts tend to remain close to the benchmark samples. The Vulgate and the poetry samples separate clearly from the rest, but in another direction. In all plots, the juridical texts (Digesta, Gaius, Pauli sententiae) do not cluster close together. They belong to quite different genres, and it seems that jurisprudence – in Antiquity the most Roman of all sciences, as has been pointed out (chap. 8 §12) – used heterogeneous language in different genres, at least more so than other sciences. In this plot, by far the main part of the information (40.6 %) lies on the x-axis; the y-axis displays only 19.7 %, not much more than the third, not depicted, dimension would. The most robust result is, therefore, certainly found on the x-axis; the scholastic texts are therefore the most distinct ones in the sample.46

Fig. 38: PCA plot of the ten parameters for which the average of the scientific or the arithmetic sample (treated below, chap. 20) differs more than 3 stdevs from the benchmark: ADJ, N, PREP, NOM, ESSE, PRON:POSS, 1st SG, 3rd PAS, ADJ-SUF, entropy.

46 PC1's vector components: ADJ: 0.03, N: 0.39, PREP: –0.23, NOM: –0.42, ESSE: –0.44, PRON: POSS: 0.26, 1st SG: 0.28, 3rd PAS: –0.25, ADJ-SUF: –0.21, entropy: 0.43. Thus, ADJ is the piece of information that contributes least, ESSE, NOM, and entropy the most.

§7 Another approach that can be used to group the texts is stylometry. Although it was conceived to solve questions of authorship, this method may also produce meaningful results for distinguishing scientific types of language. The most common n tokens (words or lemmata) in each text are compared.47 Their frequencies are stored in a vector, and the distance between the vectors corresponding to the text samples is then calculated.48 The result is a clustered tree view based on a distance matrix calculated from the frequencies. This approach thus compares the core vocabulary of different texts. Figures 39 and 40 show a plot for the 100 most common words and lemmata respectively. In order to lessen the impact of specialised disciplines' specific vocabulary, a culling value of 80 % was used, which means that only tokens present at least once in at least 80 % of all samples (i.e. 46 of the 58 ones used) are taken into consideration. Tentative names for groups are superimposed on the plots.

The results are relatively similar to the previous PCA plots (bearing in mind that very different parameters are used). Some groups form more as would be expected in the word-based plot, some in the lemma-based one. The non-scientific metrical texts (red) cluster together in both plots, the benchmark samples only partly: the antique sample is found close to Cicero in both plots, not together with the other benchmark samples. The Vulgate and charters cluster together with the other benchmark samples as non-scientific texts. Scholastic texts tend to separate most neatly from the rest; they cluster together with the translations from Greek (except, again, Ficino). Strangely, Aquinas is found somewhere else in the lemma-based plot, the neo-scholastic author Boyer in both. The three juridical texts cluster together much better than in the PCA plots. In both plots, there are two groups comprising mostly natural-science authors and human-science authors respectively. In the word plot, Augustine and, surprisingly, Eriugena end up with the non-scientific texts. Changes in the sample size (i.e. adding or removing texts) can produce strange changes (not shown). Changing the number of tokens considered, on the other hand, leaves the result quite stable. In general, it would seem that the smaller units are usually relatively stable and tend to correspond well to expectations, but the uppermost bifurcations in the tree are not very

47 I used the stylo package for R (as described in Eder, Rybicki & Kestemont 2016). 'Unknown' lemmata were, again, removed from the samples.

48 The simple and intuitive 'Classic Delta' distance first proposed by Burrows (2002) was used. To calculate it, values are standardised to standard scores, then the distance between two vectors is defined as the length of the vector of the one minus the other in Euclidean space. Evert et al. (2017) study different distances and find that the cosine distance (defined as the cosine of the angle between the two vectors) tends to outperform the others. Applied to our sample, the differences were minor (results not depicted).

Fig. 39: Stylometric clustering of 100 most frequent words.

stable. In fact, with changing parameters, they tend to shift easily, as do some, apparently not clear, texts. On the whole, these results based on the core vocabulary seem less convincing and stable than those obtained above using grammatical categories and PCA.

A word of caution may be in order: the plots in this chapter are based on very basic values that were determined automatically. They are only as good as the input values. The approach is relatively primitive. If it were possible to automatically generate confident syntactic trees and compare them, the results would become more trustworthy and telling. That said, it is all the more remarkable to see that such basic values as the ones used yield results that are surprisingly close to what a literary critic would assess the Latin types of language of these authors to be. Of course, there are cases that do not square well; they may be interesting in making us think about why certain authors end up in different places than expected. Although this approach can quantify differences in scientific (or other) style,49 it certainly cannot supplant stylistic evaluation by critics, which is based on much more complex 'input' (the reading and understanding of the texts) – but it may enrich it and suggest new ways at looking at it. The next chapter compares the findings with non-computational impressions.

Fig. 40: Stylometric clustering of 100 most frequent lemmata.

49 We use the term 'style' in the following in its most comprehensive sense, as the entire linguistic form not directly related to the content.

### 19 Conclusions on the Latin used in scientific texts

§1 The computational results from the previous chapter can now be compared with the observations about the language used in scientific communication assembled in part 2 of this book. Through its long and varied history, Latin has known many different styles and registers. In Antiquity, for instance, we can speak of Ciceronian, 'bombastic' (see chap. 8 §11), or Christian Latin. Besides many individual registers and styles, the Latin Middle Ages developed its own kind of Latin koine,1 which, though different from classical standards to some extent, still had its own relatively fixed and stable standards, first described in detail by Stotz (1996–2004). Its syntax and vocabulary have more in common with Late Antiquity with a good dose of Christian Latin, than with Classical Latin. In the Middle Ages, some special types of Latin, such as Hiberno-Latin or scholastic Latin, are easy to discern too. In early modern times, humanist Latin contrasts with more pragmatic Latin. Those are but a few examples. Approaches to science have also changed significantly in the two thousand years reviewed in part 2. We found seven epochs. In some of them, language and approaches seem to have remained quite constant (the time of the artes liberales, university science, Scientific Revolution); those in between were rather more diverse (Roman Antiquity, twelfth century, Renaissance). Some attempts to group scientific Latin texts on the basis of all the data we have so far encountered are now presented: based on the last and apparently most convincing PCA plot (§2), on Latin style (§3), and on Greek scientific models (§4). Typical example texts are then presented and analysed (§§5–6). The discussion of differences that are due to scientific topics is postponed to chapter 20 §8.

§2 The numbers and plots in chapter 18 have shown that some of these rather crude grammatical parameters distinguish surprisingly well between scientific and non-scientific Latin prose. But, as expected, it has also become clear that there is no linear development of scientific prose through time, because Latin is a language with a very good memory. So, quite in general within Latin it has always been possible to imitate older authors, and traditionalists who are against all novelty were always on hand to rein in new developments. Nonetheless, there are also new norms being developed over time. The data above have produced the following candidates (from left to right in fig. 38).

• The 'scholastic type', including neo-scholastic authors such as Suárez and (less clearly) Boyer, forms a clearly defined group. High numbers: ADV, N,

1 As Chiesa (2017) puts it.

PREP, IND, ESSE, REL, modifiers; very low: V; low: 1st SG. Similar, often even more extreme, numbers were found for the next type.

The similarity between scholastic and Greek translation texts does not come as a surprise: after all, the scholastic type can be said to begin with Boethius' translations of Aristotelian Greek. Interestingly, the above groups fit in quite well with the following epochs treated in part 2: university science (chap. 11), twelfth-century translators (chap. 10), artes liberales (chap. 9), two types corresponding to the Scientific Revolution (chap. 13), and two to Roman science (chap. 7). Nontranslating authors from the twelfth century (Abelard, Anselm, Guilelmus de Conchis, Hugh of St Victor), as well as those of the Renaissance (Cardano, Copernicus, Vesalius, the translator Ficino) do not exhibit similar traits among one another (they were already found to be rather heterogeneous in part 2 above). Some authors seem to have quite their own type of Latin: Varro, Apuleius, Tertullian, and Lullus can be mentioned. Of course, some authors also fall rather in between such groups; for instance, Cardano sometimes goes with the tentative encyclopaedic-technical type, sometimes with the natural science type, or Vossius is often atypical for the modern human science group.

§3 Part 2 has shown some rather clearly disparate stylistic approaches among the authors treated, unrelated to their scientific approaches. The following ones seem to be deductible from our texts.2 The list is arranged chronologically by first exponents; examples below (§4) will provide more concrete data.

(i) 'Hexametric'. A 'scientific poetry' text sample that will be very different from the rest of the sampled texts will be studied further in the next chapter. Lucretius decisively shaped the form and style of didactic and scientific Latin poetry. The hexameter is mostly used, but this kind of didactic poetry clearly differs from other genres using it (such as the epic). The hexametric approach became mostly didactic after an initial phase in which leading scientific innovation was communicated in it in Greek by authors such as Parmenides and Empedocles (see chap. 7 §2).

(ii) 'Rhetorical'. A rhetorical approach to presenting scientific material can be said to have been the standard approach in Roman Antiquity. The Latin rôle model was certainly Cicero; authors such as Seneca, Quintilian, or Augustine followed, as well as some historiographers. These authors were especially intent on teaching the reader dialectically. Didactic dialogues are common, and new words are avoided. This way of writing tends to remain rather close to non-technical Latin, as an orator will not wish to put off his audience with, for instance, unusual terminology. The concern for the beauty of the text sometimes seems to outweigh that for scientific precision. Humanists strove to return to such a style, but it remained rather rare among scientific writers due to its obvious disadvantages in precision and flexibility; still, there are some writers using it in all epochs, for instance Vesalius in the sixteenth century, but after the twelfth century this style was mostly confined to popular science. In Greek a similar approach was used by Plato (chap. 7 §4).

2 Greek-translation Latin is not considered here as it is not genuinely Latin, although it influenced scholastic Latin decidedly.

(iii) 'Plain'. The first surviving, and most important, author for what might be called plain, unrhetorical, matter-of-fact scientific Latin is Pliny. Later technical and encyclopaedic writers sometimes use similar Latin (Vitruvius to some extent, Isidore, Bede, Rabanus). This plain approach toward language, concentrating fully on the scientific content, may be seen as especially fit for the task. However, later scientists will realise that clear and deliberately employed syntax and wellchosen vocabulary are important for conveying difficult content: the plain approach was, therefore, largely superseded by the more technical and Hellenised scholastic approach after the advent of the universities in the thirteenth century, although some later encyclopaedic authors such as Cardano use a similar approach again. A Greek model can be seen in Alexandrian technical tracts, for instance grammatical ones. Below (chap. 21 and table 22), it will be seen that 'medical Latin' is a special subgroup of this approach. Quite similar to that of Pliny, it represents the language of a more practical science. Among medical writers, Celsus may be rather atypical, as he hardly used Greek terms and did not coin Latin ones frequently; later authors are quite free with new terminology.

(iv) 'Bombastic'. Some scientific authors have used bombastic Latin since the second century, for instance some neo-Platonists such as (in some works) Apuleius or Martianus Capella, especially in his mythological framework, among early Christians especially Tertullian. Their unusual bombast can be concentrated in their vocabulary or consist of complicated and often ambiguous syntax; in addition, there are metaphors, wordplays, and lots of words from Greek and possibly from other old and venerable languages. All of this produces a rather hermetic and inaccessible Latin, and remained rather the predilection of a few scientific writers. Its innovative vocabulary reminds one of Democritus (chap. 7 §2).

(v) 'Scholastic'. A scholastic approach could be clearly seen emerging during the twelfth century, although it had a conspicuous predecessor in Boethius, especially in his second Porphyry commentary. This language is very much logically structured, it contains many new coinings, often from Aristotle's translated Greek, and tries to keep them unambiguous, thus relying strongly on Aristotle's lecture style (chap. 7 §5). This kind of language is syntactically straightforward and not afraid to coin new terms; both these points serve the aim of making things clearer. In contrast to the encyclopaedic type, there is a special emphasis on logical stringency. This will be the most innovative type of Latin for the sciences, and the most important one. Typical authors used in our sample were Aquinas, Albertus, Duns, Ockham, and in some respects even more the translations from the Greek of the Liber de causis and De interpretatione. Neo-scholastics may have been somewhat less daring in their language, but the approach clearly remains the same (Suárez, Boyer). This is the first Latin approach to language that would seem to correspond to a Greek scientific Denkstil in being rigorous and yet flexible enough for science. Users of both the rhetorical and the mathematical types attacked its capacity to support empty disputation and its 'ugliness'. It is indebted to Aristotle.

(vi) 'Mathematical'. The Greek rôle model of this approach is clearly Euclid. As there is no extant Euclid translation before the twelfth century, such texts tend to appear late in Latin: Copernicus, Kepler, Newton, and many of the texts in the arithmetic sample studied in the next chapter. Structuring of the content into theorems, proofs, and the like is typical for it; the texts are often accompanied by tables, charts, figures, and formulas. The syntax is simple but rigorous; there is a conspicuous technical vocabulary. In general, it can be said to be a formulaic type of language (see chap. 22, §4). The language obviously changes with the increasing formalisation of mathematics. Newton may be the best-known, typical representative of an advanced state of this type of language. It would seem to be the ancestor of today's vernacular language of the mathematical natural sciences.

(vii) 'Modern academic'. It would seem that only toward Latin's demise in the seventeenth and eighteenth centuries does there seem to arise a consensus about what scholarly Latin is supposed to look like. A kind of mixture of the scholastic and the mathematical approaches, here and there with a pinch of rhetoric, apparently became standard in the less mathematical sciences. On the one hand, this language does strive for grammatical correctness according to classical rules, and to avoid excesses in word formation (unlike the bombastic and scholastic styles), but rhetorical syntactic excesses are also avoided and the rhetorical disdain for nova verba is given up. Greek loanwords, in particular, are frequent. Typical authors were Vossius, Kircher, and Kretschmann, or countless dissertations from the seventeenth to the nineteenth centuries (not included in our samples). This academic style may be the most pragmatic scientific Latin. It could have served very well as an international auxiliary for scientific communication. This seems to be a genuine Latin approach; there does not seem to be a Greek model for it.

This list of types of scientific Latin will not be exhaustive: some authors and some fields would deserve their own labels and would require further study. In some cases, it is conspicuous that there is no typical approach in some groups of writers. This is especially the case for juridical Latin, which does not seem to be homogeneous, and there is neither a clear 'humanist' or early modern approach in science, nor a single Jesuit approach: Boscovich wrote, despite his mathematical topic, a rather rhetorical Latin, Boyer a clearly neo-scholastic one, others normal modern academic Latin (such as Orlandini; see chap. 20). It would seem that these approaches correspond to Denkstile concerning the relation between language and knowledge. This will be further pursued when discussing examples below.

These styles of rendering science in the Latin language fit in quite well with the computationally determined language styles listed above (§2); only the bombastic style proves hard to make out clearly. Various early modern and late academic styles are also hard to discern.3 In the time of the Scientific Revolution, it was more and more the case that only two styles remained valid for serious science: the mathematical and the modern academic ones.4 Indeed, an ever more perceptible differentiation between mathematical and human sciences in the times of the Scientific Revolution seems to become apparent. Unfortunately, very few such late academic Latin texts have been digitised yet. It would be interesting to study a sample of such texts separately. The number of available digital texts will become much larger with the completion of the Noscemus project (Innsbruck).

All but the last of these Latin scientific styles can be linked to Greek models. The single most important factor in the development of Latin as a language of scientific communication was certainly influence from Greek, providing new vocabulary and often also affecting syntax and textual grammar, not to mention its obvious epistemic input in most sciences. The three Greek models producing the most successful approaches to language used in science stem from Plato, Aristotle, and Euclid. These correspond roughly to the rhetorical, scholastic, and mathematical approaches in the list above. This classification and its ways of dealing with words for new things are further explored below (chap. 21). The importing of science from Greek into Latin will be pursued below (chap. 24 §5).

§4 There is no doubt that technical vocabulary and syntax are the two most conspicuously different aspects of scientific language. In extreme cases, single words may already be indicative of a particular type of language. The PREP secundum all by itself can act as a marker for scholastic texts: its frequency in the general corpora is on average 0.87 ±0.51‰; the following texts from our sample use it more than 3 stdevs more: Ficino (2.45), Boethius 2 (2.46), Boyer (2.50), Suárez (2.75), De interpretatione (3.22), De causis (4.87), Ockham (3.84), Abelard (7.11), Roger Bacon (4.32), Duns (7.14), Aquinas (7.48), Albertus (8.78) – precisely the scholastic authors. Interestingly, the less scholastic first commentary of Boethius ('Boethius 1') hardly uses it (0.15). However, in later times this ceases to be a very good marker, as writers after the Renaissance were aware that this is an 'ugly' scholastic word and may have consciously avoided it. In order to corroborate and illustrate the seven approaches of scientific Latin identified above (§3), a typical sample of each is now presented and analysed in terms of some of the more conspicuous

3 In both cases, having more available data might change the picture.