Bibliographic record
Abstract
Abstract The last few years have been exciting for the field of Thai art history because of new archaeological discoveries and publications that have shed new light on several periods and subjects. New art history books range from highly technical books written for specialists like Hiram Woodward to less technical books, written by specialists, but for general readers, such as Betty Gosling's book The Origins of Thai Art , guidebooks written by specialists for a wide audience that includes scholars and educated tourists such as Dawn Rooney's book, Ancient Sukhothai: Thailand's Cultural Heritage , and art exhibition catalogues written by specialists for museum goers and scholars such as Forrest McGill's catalogue, The Kingdom of Siam: The Art of Central Thailand, 1350–1800 . New light has also been shed on the field of Buddhism in Thailand, scholars such as Peter Skilling, Steve Collions, Donald Swearer, Justin McDaniel, Leedom Lefferts, and Bonnie Brereton published new translations of texts, compiled dictionaries, and studied ritual practices in relations to texts and objects. At the same time, Buddhist scholars and anthropologists have incorporated Buddhist art and architecture in their studies of texts and rituals. This article will offer a critical overview of the relation between the study of art and Buddhism in Thailand.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".