GELENEKSEL KÂĞIT KESME SANATI VE GÜNCEL SANATA YANSIMALARI: CHRISTINE KIM ÖRNEĞİ
Bibliographic record
Abstract
Paper cutting is a traditional art form of China, the history of which goes back many centuries. This art form has been shaped by being influenced by the social, cultural and economic structure of the people. While different techniques have been used in the past, new methods and techniques are also being used in parallel with the development of technology today. To be synthesized of traditional techniques with current art practices has become a very popular approach. Toronto-based artist Christine Kim interpret her discourses in the context of contemporary art while preserving tradition by uses this technique. In particular, the artist, who is seeking to establish abstract and concrete connections between portrait art and traditional paper-cutting, shows that he also has an original attitude with his compositional fictions. In this research, which uses the document analysis and artwork analysis method, the paper cutting technique will be expressed in the context of the concept and working style, and the works of Christine Kim, who has produced important works in this field, will be evaluated with examples. Starting with a brief overview of the Chinese tradition of paper cutting, the article will move along an axis where Kim's work is analyzed and evaluated and how this original art practice has gone from randomness to stabilization. It is considered that the study will be useful to those who aim to produce works in this field and to educators who are looking for new techniques and methods in art education. For this reason, it is considered that there is not a lot of resources in the field of paper cutting art in the Turkish literature make our work important.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.010 |
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".