Of Alchemy and Authenticity: Teaching About Daoism Today
Bibliographic record
Abstract
Abstract. The authors discuss the complexities and responsibilities of teaching about Daoism in contemporary North American colleges and universities. Expanding and revising the findings of Kirkland (1998) , they argue that enough has changed in educational and cultural contexts to warrant new strategies for teaching about Daoism. Textbooks are now available that offer more accurate and responsible presentations of Daoist history, and this enables a richer appreciation of Daoist culture and religion, and its significance within broader areas of Chinese culture such as art, politics, and science. On the other hand, students have a far greater possibility of interacting outside the classroom with North Americans of Chinese and European background who claim affiliation to the Daoist tradition especially through techniques of moving meditation such asQigongand internal alchemy. This situation poses challenges in the classroom concerning claims of authenticity, tradition, and representation. Rather than shying away from these contemporary North American cultural forms, the authors argue that the skilled teacher can use these interactions to facilitate a deeper inquiry into questions of authenticity and tradition. Moreover, the authors discuss the use of an interactive website designed specifically to assist in reflecting on these issues in the classroom.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| 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".