A Ritual Economy of ‘Talent’: China and Overseas Chinese Professionals
Bibliographic record
Abstract
Since the Guangzhou municipality in south China organised the first Overseas Students Fair in 1998, large conventions aimed at recruiting overseas Chinese professionals (OCPs) have become a regular scene in major cities in China. These conventions constitute one of the most visible means of the Chinese government's engagement with the 800,000 OCPs who remain overseas after receiving tertiary education abroad. Characteristic of the conventions, and OCP policies in general, is a highly ‘materialistic’ thinking: it is argued that OCPs deserve generous financial rewards because they are economically and technologically beneficial to China, and that financial reward is the most feasible means to attract them back. My ethnographic data, however, reveal that the language of economism is communicated in a highly ritualistic manner and, conversely, political rituals serve as a crucial part of the conventions. The ritualised economic- and technological-determinist discourse appears apolitical, yet acquires strong mobilising and legitimating power, and is thus particularly effective in accommodating OCPs into the established political order. The concept ‘ritual economy’ denotes such deep intertwining between the economic, the ritualistic and the political.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".