In addition, within-group conflict may disrupt a well-documented positive feedback between social cohesiveness and the establishment of group-level traits such as language [ 71 ]. However, our finding was independent of population size, as the two variables were not significantly correlated S2 Fig. The different conflict variables were not associated with each other either, hence we find no evidence for some groups being generally more prone to conflict than others. Social isolation, which acts as a social barrier to cultural and linguistic exchange, had the opposite effect of geographical isolation of rates of linguistic differentiation.
Conflict between cultures decelerated both the rate of word gains and losses. Inter-cultural conflict may discourage communication between speakers of different languages and therefore impose social as opposed to physical barriers to the emergence of new variants via the process of second language acquisition [ 72 , 73 ].
At the same time, since conflict poses a risk of acculturation or extinction, groups may turn to linguistic prescriptivism and the use of language as a marker of identity to prevent losses of structural integrity [ 45 ] and preserve group boundaries [ 41 ], thus resulting in a reduced rate of word loss.
Finally, although it is not within the scope of this study to provide a formal test on the role of cultural group selection on language evolution [ 46 , 47 ] our results did not support the idea that between-group conflict promotes linguistic differentiation at least in the case of Austronesian languages. In fact, Austronesia is famous for the importance of long-reaching networks of institutionalised ritualistic alliances such as the Kula Ring [ 74 ] and other cultural practices such as spousal exchanges, collective defence arrangements and exchange of social information and technology [ 75 , 76 ] aimed at creating ties between groups separated by thousands of kilometres.
Those processes have been interpreted as adaptations for mitigating the potentially detrimental effects of isolation on the genetic and cultural diversity of insular populations [ 17 ].
Therefore, peaceful contact rather than warfare seems to contribute to extensive multilingualism and fast lexical turnover among Austronesian populations, whose mean distance to the nearest landmass is over km in our sample. In summary, we identified increased isolation and internal conflict, and reduced between-group conflict, as factors contributing to linguistic differentiation.
They operate by altering rates of word gain, word loss, or both. In addition, although population size did not have an effect on the overall rate of lexical evolution, languages spoken in larger communities gained words at a faster pace. Our conclusions may be specific to the case of Austronesian languages, spoken by populations separated by long distances and living on islands often unable to support multiple communities or cultural groups.
It is not clear whether linguistic differentiation would reflect a different set of factors in groups where isolation does not pose an imminent risk, or on islands such as Papua New Guinea where a large number or groups are present and where social boundaries resulting from between-group conflict may be as relevant as geographical boundaries.
In addition, the median number of speakers in our sample in only 26, compared to over seven million in Indo-European languages [ 4 ], which is relevant since the effect of population size may change beyond a given critical mass [ 77 ].
Finally, social and demographic factors may be more relevant to the evolution of lexicon than grammar or phonology, as the former have been shown to evolve in punctuational bursts rather than in a gradual fashion among Austronesian languages [ 39 , 40 ]. The Austronesian language family is one of the most diverse on the planet, comprising between 1, and 1, languages [ 78 ].
Austronesian cultures and languages are the product of a recent expansion [ 52 ] and thus Austronesian cultures and languages share many similarities with one another [ 79 ]. Their spread into Oceania was part of an expansion starting from Taiwan at around 5, ya, reaching the Bismarck Archipelago by 3, ya and Remote Oceania by 3, ya, in association with the appearance of Lapita pottery [ 80 ].
To control for evolutionary relatedness between Austronesian languages we used the method of phylogenetically independent sister pairs [ 48 , 54 ]. This implies that pairs are phylogenetically independent from each other [ 81 ], because any differences between the two languages in the same pair have evolved since their split from a common ancestor not shared with any other language in the sample see Greenhill et al.
This method allowed us to address the relationships between rates of word gains, losses and overall lexical turnover between sister languages on the one hand, and contrasts in five sociodemographic predictors on the other while controlling for phylogenetic ancestry. In other words, when two languages evolve from a common stock, our approach allowed us to investigate whether the more isolated language lose words at a faster rate than the one in closer contact to other languages?. Phylogenetically independent pairs of languages were chosen from a previously published time-calibrated phylogenetic tree containing Austronesian languages [ 52 ].
We trimmed the original phylogeny to include all languages that were also listed in the Pulotu dataset [ 82 ] covering the main Austronesian cultural groups. We then extracted sister pairs from the phylogeny, discarding any pairs whose classification was at the odds with the Ethnologue [ 4 ]. Last, we checked that the branch lengths between our sister pairs coincided with those reported by Greenhill et al.
Furthermore, to reduce uncertainty, we excluded two sister pairs whose branch lengths were the entire tree 4, years as they did not truly represent closely related languages but opposite ends of the phylogenetic tree. The sister-pairs approach has two main advantages over whole tree phylogenetic methods that use every branch in a phylogeny as a datapoint in an analysis, namely: i using only the tips of the phylogeny avoids the need to infer less reliable ancestral states down the phylogeny, which is particularly important given that some Austronesian languages date back as far as 4, years ago; and ii using only tip branches also avoids the problem of non-independence between ancestor and descendant lineages within the phylogeny, as each branch is likely to be more similar in many traits to its immediate neighbours than to more distantly related branches simply due to relatedness [ 22 ].
We made sure the ISO codes between the entries matched the taxa from our tree. Languages with insufficient linguistic, temporal or sociodemographic data were also excluded. Details on the variables extracted from the Pulotu dataset and our treatment prior to analysis are reported in Table 1.
We found one disagreement in the case of Hawaiian so we modified our dataset to match the map-based estimates. Before conducting our statistical analyses, we checked for multicollinearity among predictors using the generalized variance inflation factor GVIF.
All GVIF values fell below the lowest commonly recommended threshold of 2, indicating that our models should not suffer from multicollinearity S6 Table [ 83 ]. We estimated rates of gain and loss of word variants [ 22 , 48 ]. Using basic vocabulary permits ensuring that cognate terms not only have a common history but a common meaning across language comparisons. For each of the languages in our sample, we took each of the identified basic vocabulary items as semantic units.
Hence, when we say that a word in one language has a cognate in another language, we mean that both languages contain words from the same cognate set in the same semantic unit. We identified patterns of word gain and loss by recording instances where a cognate form within a given semantic category was present in one language of a sister pair but not in the other 48, If a word form found in one sister language has a cognate in other languages in the language family, it is likely to have been inherited from the common ancestor.
This implies that the absence of that cognate form in the other sister language must be due to its loss after divergence from their exclusive common ancestor. On the other hand, if one of the sister languages has a unique word form with no recognised cognates in any other language in the family, it presumably represents a gain of a new word since the split from its sister language.
Therefore, any changes in such terms between sister languages implies that they become more dissimilar to one another i. We did not include any identified loan words in the analysis, and therefore any cognate terms shared by two languages should be present due to inheritance from a common ancestor. This implies that the addition of a new word requires innovation as opposed to borrowing horizontal transfer from another language. Simulation studies of borrowing suggest that including loan words would make the sister languages seem more similar than they actually are by masking innovations or losses see Greenhill et al.
Since the addition of a new word does not necessarily involve the loss of an existing word as languages can have multiple lexemes for one category , each recorded gain, or loss of a lexeme was counted as a separate event, regardless of semantic category.
We did not consider cognate forms either present or absent in both members of a sister pair, as they provide no information on word gain or loss. The overall rate of lexical turnover was then computed for each language pair by adding the number of gains and losses. We used Bayesian inference for all statistical analyses. In a Bayesian framework, each model conditions data on prior probability distributions and uses Monte Carlo sampling methods to generate posterior distributions of estimated parameters.
This framework allows us to compare entire posterior distributions, without relying on specific post-hoc tests and obviating the need to adjust for multiple comparisons. We are also better able to visualise and interpret differences between parameter estimates relative to a specific value, by reporting and displaying the entire posterior distribution for each predictor rather than assuming any particular threshold for statistical significance.
In addition, standardisation of the variables allowed us to make direct comparisons of effect sizes. We fitted three sets of Bayesian generalized linear models with Poisson link function, the first set predicting the rates of word gain, the second predicting the rate of word loss, and the third predicting the overall rate of lexical turnover. For each set, we fitted a null model intercept only , a full or maximal additive model containing the set of five predictors population size, geographical isolation, within-group conflict, between-group conflict same cultural group , and between-group conflict distinct cultural groups , five models containing each predictor in isolation, and three additive models containing different combinations of the five predictors S2 — S4 Tables.
We adopted regularising priors that are more conservative than the implied flat priors of non-Bayesian procedures, which prevents the model from overfitting data [ 85 ]. We have also fitted alternative model parameterisations, to verify that our results are qualitatively robust to changes in priors. The full Poisson additive model in each of the three sets was:.
This entailed 10, samples per chain, 2, of which were used as warm-up. We also visually inspected trace plots of the chains to ensure that they converged to the same target distribution and compared the posterior predictions to the raw data to ensure that the model corresponded to descriptive summaries of the samples.
We also checked the bivariate correlations between all predictors S2 Fig , none of which was significant.
For model comparisons, we used Widely Applicable Information Criteria WAIC which provides an approximation of the out-of-sample deviance that converges to the leave-one-out cross-validation approximation in a large sample.
Analyses were performed in R 3. We calculated model weights the probability that a given model will perform best on new data relative to other candidate models [ 85 ]. Recent extensions of the coefficient of determination R 2 generalised it to non-Gaussian distributions [ 89 ], which allows us to partition the proportion of variance captured by different predictors and evaluate their relative importance in explaining variation in rates of language change in our sample.
It is composed of all the languages included in Gray et al. The branch length indicates the number of years since the two languages diverged from a common ancestor, as obtained from RateCounter [ 11 ]. The authors wish to acknowledge Simon Greenhill for help with the implementation of RateCounter and Andrea Migliano for helpful discussions on previous versions of the paper.
We also want to thank Terhi Honkola and two anonymous reviewers for their contribution to improving the manuscript. Browse Subject Areas?
Click through the PLOS taxonomy to find articles in your field. Abstract The origins of linguistic diversity remain controversial. Funding: The author s received no specific funding for this work.
Introduction Languages are the product of long-term cumulative cultural evolution [ 1 ]. Download: PPT. Fig 1. Map indicating the approximate geographical location of the 54 Austronesian languages considered in our analyses. Results Multiple social, demographic and geographic factors exert independent effects on the rates of linguistic differentiation. Fig 2. Discussion We applied a phylogenetic sister-pairs approach to three measures of lexical divergence among Austronesian languages and showed that the five sociodemographic factors were able to explain most variation in lexical differentiation between Austronesian languages.
Finally, although our sample is smaller, it was still three times as large as those utilised in similar previous studies [ 48 ], and importantly, more evenly representative of the different geographical areas where Austronesian languages are spoken as well as their different linguistic subgroups Fig 2 Our findings seemingly contradict those obtained in other cultural domains where well interconnected groups tend to lose cultural diversity faster, possibly due to the propensity of individuals to learn from successful cultural models and hence accelerated population convergence [ 67 ].
Materials and methods The Austronesian language family is one of the most diverse on the planet, comprising between 1, and 1, languages [ 78 ]. Phylogenetic sister-pairs approach and selection of languages To control for evolutionary relatedness between Austronesian languages we used the method of phylogenetically independent sister pairs [ 48 , 54 ]. Vocabulary data We estimated rates of gain and loss of word variants [ 22 , 48 ].
Rates of language change We identified patterns of word gain and loss by recording instances where a cognate form within a given semantic category was present in one language of a sister pair but not in the other 48, Statistical analysis We used Bayesian inference for all statistical analyses. Supporting information. S1 Fig. Phylogenetic tree used to extract the sister pairs used in our analyses. S2 Fig. Bivariate correlations between all the predictor variables included in the full model.
S1 Table. Nearly 40 species of birds became extinct during this brief period of time. The mass extinction happened because of habitat destruction, hunting, and competition with introduced species. Dogs and rats, for example, are species that were introduced to the islands of New Zealand by the Maori. One bird species, the moa, became extinct within a century of human arrival to New Zealand.
Moa were giant birds, almost 4 meters 12 feet tall and kilograms pounds. Giant moa, unable to fly, were such easy prey that the Maori were able to feed large villages with a single bird.
This wasteful hunting strategy, however, caused the moa to become extinct by about The environment also affected traditional beliefs and cultural practices of the indigenous communities in Australia. Although there are hundreds of indigenous groups native to Australia, these groups use the unified name Aboriginal Australian s, or Aborigines.
Aboriginal Australian cultures often had strong spiritual relationships with the local environment. They developed myth s to explain the landscape.
Modern scientific research has proven that many of these myths are fairly accurate historic records. One series of Aboriginal myths explains that the Australian coastline was once near the edge of the Great Barrier Reef, for example. The reef is now dozens, even hundreds, of meters from the shore. Geologists have proven that this story is accurate.
Cultural groups and practices focus on uniting peoples and consolidating power in the face of their isolated locations and small populations. These unifying movements are seen at both national and regional levels. Papua New Guinea demonstrates this cultural unification at the national level. The country is one of the most diverse in the world, with more than indigenous groups and indigenous languages.
The constitution also identifies and promotes traditional practices as part of contemporary culture. Customary land title is a recognition that ownership of traditional, tribal land will remain with the indigenous community. Almost all of the land in Papua New Guinea is held with customary land title; less than 3 percent of the land is privately owned.
Indigenous groups regularly work with the government and private companies to harvest the resources on tribal land. Conflicts over land use and resource rights continue to occur between indigenous groups, the government, and corporations. Rugby is a very popular sport throughout the continent—more popular than soccer, baseball, or cricket. Rugby league is the national sport of Papua New Guinea.
Rugby union, which has fewer players and slightly different rules than rugby league, is the national sport of New Zealand, Samoa, Fiji, and Tonga. Australia and New Zealand have world-famous teams in both rugby league and rugby union. The two countries have often hosted these tournament s, sometimes jointly, and many countries participate.
The tournaments, regional play, and friendly games that occur between these countries make rugby a truly unifying sport in Australia and Oceania.
The arts are another unifying cultural practice in Australia and Oceania. The Festival of Pacific Arts is a festival hosted every four years in a different country. The festival encourages diverse expressions of Pacific-wide culture, focusing on traditional song and dance. More than 2, participants from 27 countries attend the festival. Each country is represented by a group of artist-delegates and each festival is centered on a specific theme. The tourism industry is the unifying economic force in Australia and Oceania.
Tourism often focuses on fishing and other recreational water sports. There are key dates and events throughout the year that provide schools with opportunities to celebrate cultural diversity and strengthen multicultural inclusion.
Schools are encouraged to involve their staff, students and communities in activities to raise awareness of these events through the school curriculum, extra-curricular activities and local events. Schools may wish to consider:. Cultural Diversity Week : held in March each year, brings Victorians together to recognise the benefits of diversity and to showcase the many cultures that have shaped our Victorian identity.
Coincides with Cultural Diversity Week. It coincides with Cultural Diversity Week. Refugee Week is held in June each year. The week raises awareness about the issues affecting refugee communities and celebrates the positive contributions made by people from refugee backgrounds to Australian society.
Find information about professional learning for teachers in the EAL and multicultural education professional learning calendar. For more information contact multicultural. Our website uses a free tool to translate into other languages.
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In many countries, people report having multiple identities. However, the tension between different identities can become the driving force for a renewal of national unity. This is based on an understanding of social cohesion that integrates the diversity of its cultural components.
The key to successful intercultural dialogue lies in the acknowledgement of the equal dignity of participants. Challenges to building intercultural dialogue include: building intercultural competencies, promoting interfaith dialogue, and reconciling conflicting memories.
There is a need for continued reflection on ways to establish genuine intercultural dialogue today. This includes the development of appropriate skills, support for initiatives and networks of all kinds and the involvement of many new actors.
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