Cultural Heritage Education Through the Lens of Qiang Architectural Development in Sichuan of China
Bibliographic record
Abstract
This study investigates the role of Qiang architectural development in promoting cultural heritage education in Sichuan, China. Qiang architecture, with its iconic stone watchtowers, wooden beam houses, and ritual spaces, is not merely a material legacy but a living pedagogical system embedded in community life. Using a qualitative ethnographic approach, the research was conducted in Taoping Qiang Village, a recognised heritage site known for its preserved architectural landscape. Data were collected through in-depth interviews with 30 purposively sampled informants ranging from master builders and artisans to returning youth and educators, as well as through participant observation and document analysis. Thematic analysis revealed three core educational functions of Qiang architecture: 1) the transmission of indigenous knowledge through architectural practices, 2) intergenerational learning via community rituals and rebuilding events, and 3) the integration of architectural heritage into rural tourism and formal education initiatives. These findings highlight how architecture acts as a living curriculum, supporting cultural identity, environmental awareness, and intergenerational cohesion. The study concludes that embedding traditional architectural knowledge in education, both informal and formal, can foster cultural resilience and sustainability. It recommends heritage-based curriculum development, youth engagement in community practices, and policy support for architectural education as a form of cultural preservation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".