Bibliographic record
Abstract
Confucius Murders Squirrels Perry Link Confucius Institutes: Academic Malware by Marshall Sahlins. Chicago: Prickly Paradigm Press, 2015. Pp. 65. $12.95 paper. Cognitive scientists disagree about the extent to which it is true, as Edward Sapir and Benjamin Whorf famously argued nearly eighty years ago, that one’s language determines one’s thought. But wherever the truth may lie, it is fairly clear that for centuries Chinese culture assumed that the determination does hold. If China has differed from Sapir and Whorf, it has only been to put greater emphasis on written language in particular. As explained in The Great Learning (Daxue 大學) and as long assumed in literate society (and as tested on the civil service exams), internalization of written classics brings inner cultivation that can set one on track to deliver morally appropriate service to the family and then to higher levels of society all the way, for the most brilliant, to the emperor. When Mao Zedong asked young people to memorize his written words in order to induce correct thought and behavior in them, he was being more traditional than he would have wanted to admit. When rebels—such as the White Lotus or the Taiping in recent centuries, or the Falun Gong today—have challenged the ruling authority, they have relied on their own tianshu 天書 (heavenly documents) to define and anchor right ways of thinking. Heavenly documents and the thinking that they generated created strong expectations about identity and loyalty. A person belonged to the group that shared a tianshu. It should be no surprise, therefore, that during the twentieth century Chinese Nationalists and Chinese Communists squabbled over [End Page 163] language. Political identity, not just communication, was at stake. In the wake of May Fourth, when Chinese intellectuals began debating how to transcribe Mandarin Chinese in roman letters, the Communists and Nationalists each put forward proposals for how to do it and pressed their proposals with a zeal that was fraught with politics. At mid-century, when the Communists introduced their new system of simplified Chinese characters, it is no accident that they called them “standard” characters, while the Nationalists, now banished to Taiwan, continued to view the traditional characters as standard. It was important who was standard. Today, overseas Chinese communities in the US, Canada, Australia, and elsewhere organize schools, usually on weekends, to teach Chinese to their children. Often there are parallel schools—one that teaches Beijing Chinese using Hanyu pinyin and simplified characters and the other that teaches Taipei Chinese using ㄅㄆㄇㄈ (bopomofo) and traditional characters. When there is only one school for all children, parents sometimes get red-faced with passion as they argue over which kinds of writing to use. (The children, as a rule, don’t care much.) In 2004, the Chinese government launched a major effort to teach Chinese language worldwide. Second-generation overseas Chinese were not their main target, however; the main goal was to reach the growing number of non-Chinese who, as they witnessed the “rise of China,” wanted to learn the language. Chinese officials estimated in 2004 that before long there might be one hundred million such would-be learners. They announced a program of “Confucius Institutes”—or, on a smaller scale, “Confucius Classrooms.” Run from an office in Beijing known as Guojia Hanban 国家汉办 (state management of Chinese), Confucius Institutes and Classrooms provide foreign universities and high schools, and occasionally primary schools, with teachers, teaching materials, and budgets (normally US$100,000 up front) to teach Chinese language and culture in the Hanban-approved way. In the world today there are more than a thousand such programs, nearly half in North America. In 2009, which is the last year for which I could find data, the worldwide Hanban budget was 1.23 billion yuan (about US$189,000,000). Government officials referred to the program as an investment in “soft power.” Marshall Sahlins, a distinguished anthropologist and chair professor emeritus at the University of Chicago, in his deft little book Confucius Institutes: Academic Malware, points out deception in the way [End Page 164] the Institutes are presented to foreign recipients. School officials are told that China’s Ministry of Education is the sponsor and funder, but...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".