A Song of Sheep and Horses, revised edition, now available as printed books

cover-song-sheep-and-horses

As I said 6 months ago, 2019 is a tough year to write a blog, because this was going to be a complex regional election year and therefore a time of political promises, hence tenure offers too. Now the preliminary offers have been made, elections have passed, but the timing has slightly shifted toward 2020. So I may have the time, but not really any benefit of dedicating too much effort to the blog, and a lot of potential benefit of dedicating any time to evaluable scientific work.

On the other hand, I saw some potential benefit for publishing texts with ISBNs, hence the updates to the text and the preparation of these printed copies of the books, just in case. While Spain’s accreditation agency has some hard rules for becoming a tenured professor, especially for medical associates (whose years of professional experience are almost worthless compared to published peer-reviewed papers), it is quite flexible in assessing one’s merits.

However, regional and/or autonomous entities are not, and need an official identifier and preferably printed versions to evaluate publications, such as an ISBN for books. I took thus some time about a month ago to update the texts and supplementary materials, to publish a printed copy of the books with Amazon. The first copies have arrived, and they look good.

series-song-sheep-horses-cover

Corrections and Additions

Titles
I have changed the names and order of the books, as I intended for the first publication – as some of you may have noticed when the linguistic book was referred to as the third volume in some parts. In the first concept I just wanted to emphasize that the linguistic work had priority over the rest. Now the whole series and the linguistic volume don’t share the same name, and I hope this added clarity is for the better, despite the linguistic volume being the third one.

Uralic dialects
I have changed the nomenclature for Uralic dialects, as I said recently. I haven’t really modified anything deeper than that, because – unlike adding new information from population genomics – this would require for me to do a thorough research of the most recent publications of Uralic comparative grammar, and I just can’t begin with that right now.

Anyway, the use of terms like Finno-Ugric or Finno-Samic is as correct now for the reconstructed forms as it was before the change in nomenclature.

west-east-uralic-schema

Mediterranean
The most interesting recent genetic data has come from Iberia and the Mediterranean. Lacking direct data from the Italian Peninsula (and thus from the emergence of the Etruscan and Rhaetian ethnolinguistic community), it is becoming clearer how some quite early waves of Indo-Europeans and non-Indo-Europeans expanded and shrank – at least in West Iberia, West Mediterranean, and France.

Finno-Ugric
Some of the main updates to the text have been made to the sections on Finno-Ugric populations, because some interesting new genetic data (especially Y-DNA) have been published in the past months. This is especially true for Baltic Finns and for Ugric populations.

ananino-culture-new

Balto-Slavic
Consequently, and somehow unsurprisingly, the Balto-Slavic section has been affected by this; e.g. by the identification of Early Slavs likely with central-eastern populations dominated by (at least some subclades of) hg. I2a-L621 and E1b-V13.

Maps
I have updated some cultural borders in the prehistoric maps, and the maps with Y-DNA and mtDNA. I have also added one new version of the Early Bronze age map, to better reflect the most likely location of Indo-European languages in the Early European Bronze Age.

As those in software programming will understand, major changes in the files that are used for maps and graphics come with an increasing risk of additional errors, so I would not be surprised if some major ones would be found (I already spotted three of them). Feel free to communicate these errors in any way you see fit.

bronze-age-early-indo-european
European Early Bronze Age: tentative langage map based on linguistics, archaeology, and genetics.

SNPs
I have selected more conservative SNPs in certain controversial cases.

I have also deleted most SNP-related footnotes and replaced them with the marking of each individual tentative SNP, leaving only those footnotes that give important specific information, because:

  • My way of referencing tentative SNP authors did not make it clear which samples were tentative, if there were more than one.
  • It was probably not necessary to see four names repeated 100 times over.
  • Often I don’t really know if the person I have listed as author of the SNP call is the true author – unless I saw the full SNP data posted directly – or just someone who reposted the results.
  • Sometimes there are more than one author of SNPs for a certain sample, but I might have added just one for all.
ancient-dna-all
More than 6000 ancient DNA samples compiled to date.

For a centralized file to host the names of those responsible for the unofficial/tentative SNPs used in the text – and to correct them if necessary -, readers will be eventually able to use Phylogeographer‘s tool for ancient Y-DNA, for which they use (partly) the same data I compiled, adding Y-Full‘s nomenclature and references. You can see another map tool in ArcGIS.

NOTE. As I say in the text, if the final working map tool does not deliver the names, I will publish another supplementary table to the text, listing all tentative SNPs with their respective author(s).

If you are interested in ancient Y-DNA and you want to help develop comprehensive and precise maps of ancient Y-DNA and mtDNA haplogroups, you can contact Hunter Provyn at Phylogeographer.com. You can also find more about phylogeography projects at Iain McDonald’s website.

Graphics
I have also added more samples to both the “Asian” and the “European” PCAs, and to the ADMIXTURE analyses, too.

I previously used certain samples prepared by amateurs from BAM files (like Botai, Okunevo, or Hittites), and the results were obviously less than satisfactory – hence my criticism of the lack of publication of prepared files by the most famous labs, especially the Copenhagen group.

Fortunately for all of us, most published datasets are free, so we don’t have to reinvent the wheel. I criticized genetic labs for not releasing all data, so now it is time for praise, at least for one of them: thank you to all responsible at the Reich Lab for this great merged dataset, which includes samples from other labs.

NOTE. I would like to make my tiny contribution here, for beginners interested in working with these files, so I will update – whenever I have time – the “How To” sections of this blog for PCAs, PCA3d, and ADMIXTURE.

-iron-age-europe-romans
Detail of the PCA of European Iron Age populations. See full versions.

ADMIXTURE
For unsupervised ADMIXTURE in the maps, a K=5 is selected based on the CV, giving a kind of visual WHG : NWAN : CHG/IN : EHG : ENA, but with Steppe ancestry “in between”. Higher K gave worse CV, which I guess depends on the many ancient and modern samples selected (and on the fact that many samples are repeated from different sources in my files, because I did not have time to filter them all individually).

I found some interesting component shared by Central European populations in K=7 to K=9 (from CEU Bell Beakers to Denmark LN to Hungarian EBA to Iberia BA, in a sort of “CEU BBC ancestry” potentially related to North-West Indo-Europeans), but still, I prefer to go for a theoretically more correct visualization instead of cherry-picking the ‘best-looking’ results.

Since I made fun of the search for “Siberian ancestry” in coloured components in Tambets et al. 2018, I have to be consistent and preferred to avoid doing the same here…

qpAdm
In the first publication (in January) and subsequent minor revisions until March, I trusted analyses and ancestry estimates reported by amateurs in 2018, which I used for the text adding my own interpretations. Most of them have been refuted in papers from 2019, as you probably know if you have followed this blog (see very recent examples here, here, or here), compelling me to delete or change them again, and again, and again. I don’t have experience from previous years, although the current pattern must have been evidently repeated many times over, or else we would be still talking about such previous analyses as being confirmed today…

I wanted to be one step ahead of peer-reviewed publications in the books, but I prefer now to go for something safe in the book series, rather than having one potentially interesting prediction – which may or may not be right – and ten huge mistakes that I would have helped to endlessly redistribute among my readers (online and now in print) based on some cherry-picked pairwise comparisons. This is especially true when predictions of “Steppe“- and/or “Siberian“-related ancestry have been published, which, for some reason, seem to go horribly wrong most of the time.

I am sure whole books can be written about why and how this happened (and how this is going to keep happening), based on psychology and sociology, but the reasons are irrelevant, and that would be a futile effort; like writing books about glottochronology and its intermittent popularity due to misunderstood scientist trends. The most efficient way to deal with this problem is to avoid such information altogether, because – as you can see in the current revised text – they wouldn’t really add anything essential to the content of these books, anyway.

Continue reading

Official site of the book series:
A Song of Sheep and Horses: eurafrasia nostratica, eurasia indouralica

A Game of Thrones in Indo-European: proto-languages in Westeros and Essos, and population genomics

game-of-thrones-westeros-essos-map

I think proto-languages can be applied to basically any appropriate prehistoric setting, and especially to science fiction and fantasy settings. I often viewed the lack of interest for them as based on the idea that they are not fantastic enough, that they would render a fantastic world too realistic to allow for an adequate immersion of the reader (or viewer) into a new world.

With time, I have become more and more convinced that most authors don’t use proto-languages (or tweaked versions of them) simply because they can’t, and resort to the easier way: inventing some rules and words based on some basic ideas and sounds they feel would fit a certain culture or people, to get going. After all, world-building is about a good enough, not too detailed description, and books are about characters and settings, not worlds.

After the end of the 7th season of the Game of Thrones TV series, of which I have become a great fan, I had some season finale grief to deal with, so I thought about applying what we knew about Proto-Indo-Europeans to the fantasy world. Since all book translations deal with English names as if they were translations of the Common Tongue (e.g. Spanish “Invernalia” or “Poniente” for “Winterfel” or “Westeros”), the idea of a translation into Proto-Indo-European seemed quite interesting.

NOTE. I understand that, for some, the idea that “the original language is the best” would make them reject this. However, just take into account the millions who enjoy the books and the TV series only in their native language, and know nothing about the ‘original’ version…

Here are the text and images:

A Dance with Old Tongues

As you can see, the idea of the Common Tongue being Late Proto-Indo-European brings about a whole new (infinite) world of dialectal evolution, language contacts, and population expansions which must be established for the whole setting to work. This is what the text I began to write was about: to use languages (and related populations) of ca. 6000-1500 BC, and to avoid anachronisms and impossible language relationships.

As an added advantage, fans of role-playing games could expand their world with the use of the language correspondences and the maps. This way, instead of “Northern English” being spoken in the North, and “Spanish English” being spoken in Dorne, according to some selections that have been naturally criticized, you have ancient languages that fit with the ancient setting, and which were actually related to each other.

8-westeros-essos-languages-equivalence
Equivalence of languages of the known world with coeval proto-languages. Solid red lines divide Graeco-Aryan from Northern Indo-European dialects (Tocharian is separated from North-West Indo-European by a dotted red line). See all maps.

I also began drawing a fantasy map, my first one – even though I have been member of Cartographer’s Guild for years – , which eventually helped me with my updates of maps of prehistoric migrations, and even with the use of arrows and colors for scientific publications. I drew details mainly to illustrate the text, not to offer a comprehensive translated world. Most of the work was done in the Summer of 2017, with some map changes done in 2018 with help of the maps and works of fans.

NOTE. I have reviewed it during some long travels lately, and included names of “bloodlines” (i.e. haplogroups), which I find more interesting today for people to understand bottlenecks during prehistoric migrations; I have also added a map using pie charts. If this doesn’t fit well with the whole picture, it’s because it’s a recent addition. The rest is more or less the same as one-two years ago.

I don’t have time now to correct much of what I wrote. I have forgotten most of the relevant details from the books, especially A World of Ice and Fire which I think helped me a lot with this, and I am sure that after writing A Song of Sheep and Horses (now you know the why of the book names) I would deal with some language identification and cognates differently.

I decided to publish it to liven up our Facebook page of Modern Indo-European now that the 8th season is near, so that people can participate and try to translate (translatable) names and expressions into Proto-Indo-European, to see how it would work out. You can also request access our Modern Indo-European and Proto-Indo-European groups; both are administered mainly by Fernando.

If you think this whole idea is crazy, or a huge loss of time, I agree; this is how you lose your time when you like fantasy, comic books, etc. But I am a great fan of fantasy and fiction, and I had a lot of free time back then, so I couldn’t help it…

On the other hand, if you feel that mixing fantasy (or SF) with the Proto-Indo-European question (especially population genomics) is a bad idea, I may have agreed with that two years ago, and maybe this is the reason why I hesitated to publish it then.

Hoewever, today we can read a whole new (2018 and 2019) bunch of “steppe ancestry=Indo-European” fantasies: invisible Nganasan reindeer hordes, a Fearsome Tisza River where Yamna settlers mysteriously disappear, shapeshifting Dutch CWC peoples who change haplogroups, languages dependent on cephalic types, or Yamna/Bell Beaker expanding Vasconic…So what’s the matter with some more fantasy?

Tales of Human Migration, Admixture, and Selection in Africa

african-migrations

Comprehensive review (behind paywall) Tales of Human Migration, Admixture, and Selection in Africa, by Carina M. Schlebusch & Mattias Jakobsson, Annual Review of Genomics and Human Genetics (2018), Vol. 9.

Abstract (emphasis mine):

In the last three decades, genetic studies have played an increasingly important role in exploring human history. They have helped to conclusively establish that anatomically modern humans first appeared in Africa roughly 250,000–350,000 years before present and subsequently migrated to other parts of the world. The history of humans in Africa is complex and includes demographic events that influenced patterns of genetic variation across the continent. Through genetic studies, it has become evident that deep African population history is captured by relationships among African hunter–gatherers, as the world’s deepest population divergences occur among these groups, and that the deepest population divergence dates to 300,000 years before present. However, the spread of pastoralism and agriculture in the last few thousand years has shaped the geographic distribution of present-day Africans and their genetic diversity. With today’s sequencing technologies, we can obtain full genome sequences from diverse sets of extant and prehistoric Africans. The coming years will contribute exciting new insights toward deciphering human evolutionary history in Africa.

Regarding potential Afroasiatic origins and expansions:

It is currently believed that farming practices in northeastern and eastern Africa developed independently in the Sahara/Sahel (around 7,000 BP) and the Ethiopian highlands (7,000–4,000 BP), while farming in the Nile River Valley developed as a consequence of the Neolithic Revolution in the Middle East (84). Northeastern and eastern African farmers today speak languages from the Afro-Asiatic and Nilo-Saharan linguistic groups, which is also reflected in their genetic affinities (Figure 3, K=6). In the northern parts of East Africa (South Sudan, Somalia, and Ethiopia), Nilo-Saharan and Afro-Asiatic speakers with farming lifeways have completely replaced hunter–gatherers. It is still largely unclear how farming and herding practices influenced the northeastern African prefarming population structure and whether the spread of farming is better explained by demic or cultural diffusion in this part of the world. Genetic studies of contemporary populations and aDNA have started to provide some insights into population continuity and incoming gene flow in this region of Africa.

african-demographic-history
Demographic model of African history and estimated divergences. (a) Population split times, hierarchy, and population sizes (summarized from 123). Horizontal width represents population size; horizontal colored lines represent migrations, with down-pointing triangles indicating admixture into another group. (b) Population structure analysis at 5 assumed ancestries (K=5) for 93 African and 6 non-African populations. Non-Africans (brown), East Africans (blue), West Africans ( green), central African hunter–gatherers (light blue), and Khoe-San (red ) populations are sorted according to their broad historical distributions.

For example, studies have shown that a back-migration from Eurasia into Africa affected most of northeastern and eastern Africa (36, 46, 53, 89, 132) (Figure 1b). A genetic baseline of eastern African ancestral genetic variation unaffected by recent Eurasian admixture and farming migrations within the last 4,500 years has been suggested in the form of the genome sequence of a 4,500-year-old individual from Mota, Ethiopia (36). Based on comparisons with the ancient Mota genome, we know that certain populations from northeastern Africa show deep continuity in their local area with very limited gene flow resulting from recent population movements. For example, the Nilotic herder populations from South Sudan (e.g., Dinka, Nuer, and Shilluk) appear to have remained relatively isolated over time and received little to no gene flow from Eurasians, West African Bantu-speaking farmers, and other surrounding groups (53) (Figures 2 and 3). By contrast, the Nubian and Arab populations to their north show gene flow with Eurasians, which has been connected to the Arab expansion (53). The Nubian, Arab, and Beja populations of northeastern Africa roughly display equal admixture fractions from a local northeastern African gene pool (similar to the Nilotic component) and an incoming Eurasian migrant component (53) (Figure 3). The Eurasian component has been linked to the Middle East and the Arab migration, but only the Arab groups shifted to the Semitic languages; the Nubians and Beja groups kept their original languages. The Eurasian gene flow appears to have spread from north to south along the Nile and Blue Nile in a succession of admixture events (53).

Skoglund and Mathieson’s preprint has also been published in the same volume, without meaningful changes.

Related:

The origin and expansion of Pama–Nyungan languages across Australia

Yet another questionable paper by Nature, The origin and expansion of Pama–Nyungan languages across Australia, by Bouckaert, Bowern & Atkinson, Nat Ecol Evol (2018).

Abstract:

It remains a mystery how Pama–Nyungan, the world’s largest hunter-gatherer language family, came to dominate the Australian continent. Some argue that social or technological advantages allowed rapid language replacement from the Gulf Plains region during the mid-Holocene. Others have proposed expansions from refugia linked to climatic changes after the last ice age or, more controversially, during the initial colonization of Australia. Here, we combine basic vocabulary data from 306 Pama–Nyungan languages with Bayesian phylogeographic methods to explicitly model the expansion of the family across Australia and test between these origin scenarios. We find strong and robust support for a Pama–Nyungan origin in the Gulf Plains region during the mid-Holocene, implying rapid replacement of non-Pama–Nyungan languages. Concomitant changes in the archaeological record, together with a lack of strong genetic evidence for Holocene population expansion, suggests that Pama–Nyungan languages were carried as part of an expanding package of cultural innovations that probably facilitated the absorption and assimilation of existing hunter-gatherer groups.

pama-nyungan-language-family
“Diversification of the Pama–Nyungan language family. Maximum clade credibility tree showing the inferred timing and emergence of the major branches and their subsequent diversification.”

Even with my absolute lack of knowledge on Australian languages, I am not conviced. Not at all.

I have already expressed more than once my opinion on Glottochronology – and the improved method of this paper seems like the final twist of the screw for its strongest proponents.

Interestingly, this paper includes the same journal, author, and (mostly) method of the famous Language-tree divergence times support the Anatolian theory of Indo-European origin (2003).

And we have also seen how most suggested prehistorical cultural diffusion events were actually migrations, so it seems rather odd to dare publish this right now.

At a time of groundbreaking genomic papers being published on South-East Asian migrations, and probably expecting more on the region – including Australia – , this paper seems to me quite unnecessary.

It will especially not help Nature make forget its latest fiasco on Indo-European migrations.

See also:

Population turnover in remote Oceania shortly after initial settlement

papuan-oceanian

Interesting preprint at BioRxiv by the team of the Reich lab, Population Turnover in Remote Oceania Shortly After Initial Settlement, by Mark Lipson, Pontus Skoglund, Matthew Spriggs, et al. (2018).

Abstract (emphasis mine):

Ancient DNA analysis of three individuals dated to ~3000 years before present (BP) from Vanuatu and one ~2600 BP individual from Tonga has revealed that the first inhabitants of Remote Oceania (“First Remote Oceanians”) were almost entirely of East Asian ancestry, and thus their ancestors passed New Guinea, the Bismarck Archipelago, and the Solomon Islands with minimal admixture with the Papuan groups they encountered. However, all present-day populations in Near and Remote Oceania harbor 25-100% Papuan ancestry, implying that there must have been at least one later stream of migration eastward from Near Oceani>. We generated genome-wide data for 14 ancient individuals from Efate and Epi Islands in Vanuatu ranging from 3,000-150 BP, along with 185 present-day Vanuatu individuals from 18 islands. We show that people of almost entirely Papuan ancestry had arrived in Vanuatu by 2400 BP, an event that coincided with the end of the Lapita cultural period, changes in skeletal morphology, and the cessation of long-distance trade between Near and Remote Oceania. First Remote Oceanian ancestry subsequently increased via admixture but remains at 10-20% in most islands. Through a fine-grained comparison of ancestry profiles in Vanuatu and Polynesia with diverse groups in Near Oceania, we find that Papuan ancestry in Vanuatu is consistent with deriving from the Bismarck Archipelago instead of the geographically closer Solomon Islands. Papuan ancestry in Polynesia also shows connections to the ancestry profiles present in the Bismarck Archipelago but is more similar to Tolai from New Britain and Tutuba from Vanuatu than to the ancient Vanuatu individuals and the great majority of present-day Vanuatu populations. This suggests a third eastward stream of migration from Near to Remote Oceania bringing a different type of Papuan ancestry.

qpgraph-oceanian-papuan
Admixture graph model with inferred parameters, alternative visualization. Branch lengths are given in units of f2 genetic drift distance times 1000, and admixture proportions are indicated along corresponding dotted lines. Red, Solomon Islands majority source; blue, Bismarck Archipelago majority source; purple, New Guinea-related source; green, First Remote Oceanian; brown, mixed ancestry. The order of admixture events specified is arbitrary.

See also:

Indo-European and Central Asian admixture in Indian population, dependent on ethnolinguistic and geodemographic divisions

indian-population-genetics

Preprint paper at BioRxiv, Dissecting Population Substructure in India via Correlation Optimization of Genetics and Geodemographics, by Bose et al. (2017), a mixed group from Purdue University and IBM TJ Watson Research Center. A rather simple paper, which is nevertheless interesting in its approach to the known multiple Indian demographic divisions, and in its short reported methods and results.

Abstract:

India represents an intricate tapestry of population substructure shaped by geography, language, culture and social stratification operating in concert. To date, no study has attempted to model and evaluate how these evolutionary forces have interacted to shape the patterns of genetic diversity within India. Geography has been shown to closely correlate with genetic structure in other parts of the world. However, the strict endogamy imposed by the Indian caste system, and the large number of spoken languages add further levels of complexity. We merged all publicly available data from the Indian subcontinent into a data set of 835 individuals across 48,373 SNPs from 84 well-defined groups. Bringing together geography, sociolinguistics and genetics, we developed COGG (Correlation Optimization of Genetics and Geodemographics) in order to build a model that optimally explains the observed population genetic sub-structure. We find that shared language rather than geography or social structure has been the most powerful force in creating paths of gene flow within India. Further investigating the origins of Indian substructure, we create population genetic networks across Eurasia. We observe two major corridors towards mainland India; one through the Northwestern and another through the Northeastern frontier with the Uygur population acting as a bridge across the two routes. Importantly, network, ADMIXTURE analysis and f3 statistics support a far northern path connecting Europe to Siberia and gene flow from Siberia and Mongolia towards Central Asia and India.

Among the most interesting results (emphasis mine):

Our meta-analysis of the ADMIXTURE output shows that the IE and DR populations across castes shared very high ancestry, indicating the autochthonous origin of the caste system in India (Figure 2). f3 statistics show that most of the castes and tribes in India are admixed, with contributions from other castes and/or tribes, across languages affiliations (Supplementary Table 4 and Supplementary Note). The geographically isolated Tibeto-Burman tribes and the Dravidian speaking tribes appear to be the most isolated in India. Linear Discriminant Analysis on the normalized data set clearly supports genetic strati cation by castes and languages in the Indian sub-continent

(…)

Our meta-analysis of the ADMIXTURE plot in Figure 4A quantifies the ADMIXTURE results (darker colors indicate higher pairwise shared ancestry). Indian populations show a greater proportion of shared ancestry with the so-called Indian Northwestern Frontier populations, namely the tribal populations spanning Afghanistan and Pakistan. Central Asian populations share higher degrees of ancestry with IE and DR Froward castes. Uygurs share high degrees of ancestry with Indian populations.

(…)

f3 statistics (all negative Z-scores are shown) indicate Chinese and Siberian ancestry contributing to the Tibeto-Burman tribal speakers. On the other hand, the Mongols and the Europeans have contributed significant amounts of ancestry to the Indo-European and Tibeto-Burman forward castes. F3 statistics also show that the Central Asians are an admixed population with signs of admixture from Caucasus and other parts of Europe.

Among the results for proportions of shared ancestry between Indians and Eurasians (FIG. 4), there is an obvious influence of European admixture (Caucasus, and Southern, Central, and Northern EU), potentially from the Yamna-Corded Ware expansion, in IE_ForwardCaste, which is lessened in IE_BackwardCaste and also in IE_Tribal, while DR_ForwardCaste shows again more admixture than IE_Tribal, but diminishing with lower castes and quite low in DR_Tribal.

Ancestry from Central Asia is strong with a similar pattern, which hints at the influence of Sintashta, Andronovo, and BMAC influence in the expansion of the Steppe component, even more than a later Turkic component.

On the other hand, the influence from Turkey is difficult to assess, given the complex genetic history of Anatolia, but the map contained in Fig. 6 doesn’t feel right, not only from a genetic viewpoint, but also from linguistic and archaeological points of view. This is the typical map created with admixture analyses that is wrong because of not taking into account anthropological theories.

Quite interesting is then the influence of admixture in these different ethnolinguistic groups, Indo-European and Dravidic, which points to an initially greater expansion of Indo-European speakers, and later resurge of Dravidian languages.

Featured image contains simplified origin and data of samples studied, from the article.

Related:

About the European Union’s arcane language: the EU does seem difficult for people to understand

Mark Mardell asks in his post Learn EU-speak:

Does the EU shroud itself in obscure language on purpose or does any work of detail produce its own arcane language? Of course it is not just the lingo: the EU does seem difficult for people to understand. What’s at the heart of the problem?

His answer on the radio (as those comments that can be read in his blog) will probably look for complex reasoning on the nature of the European Union as an elitist institution, distant from real people, on the “obscure language” (intentionally?) used by MEPs, on the need of that language to be obscured by legal terms, etc.

All that is great. You can talk a lot about the possible reasons why people would find too boring those Europarliament discussions where everyone speaks his own national language; possible reasons why important media (like the BBC) would never show debates on important issues, unless the MEP uses their national language; possible reasons why that doesn’t happen with national parliaments where everyone speaks a common language…

But the most probable answer is so obvious it doesn’t really make sense to ask. The initeresting question is do people actually want to pay the price for having a common Europe?

Five lines of ancient script on a shard of pottery could be the longest proto-Canaanite text ever found, archaeologists say

According to the BBC News ‘Oldest Hebrew script’ is found:

The shard was found by a teenage volunteer during a dig about 20km (12 miles) south-west of Jerusalem. Experts at Hebrew University said dating showed it was written 3,000 years ago – about 1,000 years earlier than the Dead Sea Scrolls. Other scientists cautioned that further study was needed to understand it.

Preliminary investigations since the shard was found in July have deciphered some words, including judge, slave and king. The characters are written in Proto-Canaanite, a precursor of the Hebrew alphabet.

I found it interesting because of the implications that these findings might have on classifications of dead languages into more natural or artificial regarding the knowledge we have of them, especially about proto-languages like Proto-Canaanite (or Europe’s Indo-European), which can easily move from category 9 (‘hypothetical language’) to category 8 or even 7 (‘dead language’).

As we have said before, this implies that, despite the efforts of some conlangers to make their newly created conlangs (look) the same as proto-languages like PIE – in the sense of ‘artificiality’, they obviously aren’t.