A Study on Translation of Political Terms from Perspective of Memetics Theory in China’s 19th National Congress Report
2018-10-30蒋易沁
【Abstract】English translation of political terms in governments reports is important to publicity of Chinas policies and ideology. Taking translation of Chinas 19th National Congress Report as an example, the author adopts an approach of data analysis to observe English translation of political terms from the perspective of Memetics Theory. The author intends to design a model of predicting a political terms possibility of becoming a strong meme after translation. The model is crude and needs improvement and perfection in further study.
【Key words】Political Terms; Memetics Theory; strong linguistic memes; data analysis
【作者簡介】蒋易沁,华东政法大学外语学院。
Chapter 1 Introduction
The 19th National Congress of the Communist Party of China was held in 2017. The report delivered by President Xi is a very important government report and there are several typical political terms that can be counted as strong memes in Chinese. Political terms are strong linguistic memes in Chinese because of extensive publicity and general education in domestic. Since China is going to speak in its own voice and hopes to spread its new policies and new ideas, its ideal to turn the translation of these terms into strong linguistic memes in English so that they can be widely duplicated and spread. The author wants to find out that, as there are always great differences between China and western countries in cultural and historical background, the possibilities for strong linguistic memes in Chinese of becoming strong linguistic memes in English after translation. Therefore, the author intends to design a model of predicting a political terms possibility of becoming a strong meme after translation, by checking whether it possesses the three features of strong linguistic memes—copying-fidelity, fecundity and longevity. The theory adopted here is Memetics Theory, and the methods used here are data statistics, charting and comparative analysis.
By designing and improving such a model, the author hopes that it can be a little helpful for English translation of political terms. From the model, we will find out the factors that may influence a political terms possibility of becoming a strong meme after translation and then further conclude some rules that may help us to choose a better translation method. By choosing the most suitable method for each, we can have larger chance to turn them into strong memes in English and then spread them better.
Besides, it is also hoped that such a model can be instructive for some other translation studies after it has been improved in further study.
Chapter 2 Theory Ground for Memes Study
2.1 Memetics Theory and Language
Memetics is a theory to explain the spread of information and culture based on an analogy with Darwinian evolution. The term “meme” is core of Memetics and it was coined in Richard Dawkinss book The Selfish Gene in 1976. Analogous to a gene, the meme is conceived as a “unit of culture” which is “hosted” in the minds of one or more individuals, and which can reproduce itself in the sense of jumping from the mind of one person to the mind of another. Thus what would otherwise be regarded as one individual influencing another to adopt a belief is seen as an idea-replicator reproducing itself in a new host. (Dawkins 1976)
Human language is a kind of meme itself. Every word, term, phrase, sentence, paragraph, and even every text will become a meme after duplication and spread by imitation. (Xie and He 2007) We call such kind of memes linguistic memes.
2.2 Strong Memes and Weak Memes in Language
Blackmore (1999) thought that there were risks and pressure in the whole process and only a few memes could survive among a mass of potential memes. Their competitiveness depended on their capacity of duplication, according to which memes could be divided into two groups—strong memes and weak memes. New linguistic memes in target language can also be divided into strong linguistic memes and weak linguistic memes.
Strong linguistic memes refer to those linguistic memes that can be widely used by people and be duplicated as well as spread constantly. (Chen and He 2006) On the contrary, some linguistic memes will not be used by people any more as time goes by and vanish at last. These are weak linguistic memes. He (2005) pointed out that the survival of linguistic memes depended on their pragmatic functions.
Dawkins (1976) summarized three features of successful memes—copying-fidelity, fecundity and longevity. Copy-fidelity means that strong memes bring into correspondence with original core information during duplication. Fecundity means that strong memes will follow Matthew Effect, which is to say, the more accepted the memes are, the faster and the more widely they are spread. Longevity refers to that the longer the memes stay, the more opportunities to be duplicated they have. In the same way, strong linguistic memes also possess these three features.
Therefore, the research is based on Dawkinss theory. The author designs a model to check the terms according to three features of strong memes to see whether they have possibilities of becoming strong linguistic memes in English.
Chapter 3 Research Method and Data Analysis
3.1 Research Design
The author selected 8 political terms from Chinas 19th National Congress Report. They are: The Five-Sphere Integrated Plan (五位一体), The Four-Pronged Comprehensive Strategy (四个全面), The Belt and Road Initiative (一带一
路), The Three Stricts and Three Earnests (三严三实), The Four Cardinal Principles (四项基本原则), The two Centenary Goals
(两个一百年), The Five Principles of Peaceful Coexistence (和平共处五项原则), The practice of shuanggui (雙规).
They are all translated in by loan translation, which is the adoption by one language of a phrase or compound word whose components are literal translations of the components of a corresponding phrase or compound in a foreign language. This means that these 8 terms not only carry the core information but also retain the characteristics of their original Chinese versions. That is to say, they possess one of the strong linguistic memes features—copy-fidelity.
According to Dawkinss theory, the author needs to check whether these 8 terms possess other two features—fecundity and longevity—to see whether they have possibilities of becoming strong memes.
To check their longevity, the author searched online to find out the time when their Chinese versions were first put forward and then recorded. Whichever was put forward earlier, it has longer existence time, and then it may possess longevity.
As for fecundity, its difficult to check. Therefore the author used Google search engine and adapted data analysis to observe the fecundity of these 8 terms.
3.2 Research Basis
Google is recognized as the largest search engine in the world and its data are comprehensive and international. Hence the search results from Google are representative to some extent.
There is a total search result presented under the search bar when a term is typed in. It shows how many web pages that mention the term are searched and it further indicates the use and spread of the term worldwide. Generally speaking, the more the total search results a term has, the more widely it is used.
The articles on Chinese websites are mostly written by Chinese and play a role of foreign publicity. But if a term appears in foreign websites, it means that foreigners are using it and spreading it, from which we can infer that the lager the proportion of foreign websites is, the more widespread of the English term is in the world.
Both of the amount of total search results and the amount of foreign websites in the top 100 search results can demonstrate the fecundity of a term in theory.
Chapter 4 Findings and Discussions
4.1 Results and Data
All of the statistical data were tabulated in Table 1, including the time that Chinese terms were first put forward, the amounts of total search results, and the amounts of foreign websites in the top 100 search results.
4.2 Strong Linguistic Memes
4.2.1 Longevity
By comparing the time they first put forward, the author finds that the first four terms have been existent for less than 6 years. In contrast, other four terms have been existent much longer, more than 20 years. Therefore, the author reckons that the terms “The Four Cardinal Principles”, “The Two Centenary Goals”, “The Five Principles of Peaceful Coexistence” and “The Practice of Shuanggui” may possess longevity, while the others may not.
4.2.2 Fecundity
After checking the longevity of these terms, the author moved on to check their fecundity. Since both of the amount of total search results and the amount of foreign websites in the top 100 search results can demonstrate the fecundity of a term in theory, the author first compared these two sets of data to see whether they were consistent with each other. To make them visual and comparable, the author made a graph to illustrate them. (Graph 1)
By comparison, the author finds that these two lines share a similar trend, if it cannot be described as a same trend. This shows that these two sets of data are consistent with each other and have similarity in demonstrating the fecundity of these 8 terms.
These two lines have three same peak points and their corresponding terms are “The Five Principles of Peaceful Coexistence”, “The Four Cardinal Principles” and “The Belt and Road Initiative”. This means that these three terms have more total search results and they are mentioned on more foreign websites. Therefore, the author reckons that these three terms possess fecundity.
4.2.3 Strong Linguistic Memes
The author fills in the Table 1 according to the preceding analysis and the new table (Table 2) is as follows.
From Table 2, the author finds that there are only two terms—“The Four Cardinal Principles” and “The Five Principles of Peaceful Coexistence”—possess all of the three features of strong memes, which is to say that only these two terms have possibilities of becoming strong linguistic memes in English.
4.3 A Special case
From Graph 1, the author finds the term “One Belt and Road Initiative” performs so outstanding among these 8 terms. Both its total search results and the foreign websites are far more than other terms, and their amounts of total search results are even not in the same order of magnitude. It seems that this term is used very widely by people from other countries. But in fact, it was put forward in 2013, only 5 years since then.
So, why does such a term look like a strong linguistic meme in such a short time?
The author brings forward two possible reasons here.
Firstly, “One Belt and Road Initiative” has been being a hot topic in the world since it was first put forward. Although it was put forward by China, it is actually a globe-beneficial initiative. People all around the world would like to talk about it. Therefore, the term “One Belt and Road Initiative” was just like a virus, triggering a pandemic that swept the globe.
Secondly, “One Belt and Road Initiative” is not only a political term, but also an economic term. Politicians and political news talk about it, while economists and economic news also talk about it. Because of its dual nature, this term is used and spread more widely.
As for whether it has possibility of becoming a strong meme, the author holds “yes” because of its specialty.
Chapter 5 Conclusion
Based on the model supported by data and graph analysis, the author concludes that the terms “The Five Principles of Peaceful Coexistence”, “The Four Cardinal Principles” and “The Belt and Road Initiative” have possibilities of becoming strong linguistic memes and the term “The Belt and Road Initiative” is a special case. And meanwhile, the terms “The Five-Sphere Integrated Plan”, “The Four-Pronged Comprehensive Strategy”, “The Three Stricts and Three Earnests”, “The two Centenary Goals” and “The practice of shuanggui” are not strong linguistic memes in English yet.
All of the hypotheses and conclusions above deserve further study, since the model is still crude and some bugs during the research are inevitable. For example, the change of search results according to time will influence accuracy of data.
The author hopes that the conclusions can be a little helpful for English translation of political terms. As for those whose English corresponding terms have not been strong linguistic memes yet, wed better add footnotes to explain them when we translate them by loan translation. It is also hoped that such a model can be instructive for some other translation studies and that it can be improved in further study.
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