Türkiye'de sanat tarihi disiplininin analizi ve değerlendirilmesi
Bibliographic record
Abstract
Bir bilim dalının tarihsel süreç içerisindeki oluşum ve gelişimine yönelik yeterli \nbirikime sahip olmak, disiplinin kendi bilimsel içeriğinin tüm hatlarıyla kavranmasını \nsağlamakla birlikte aynı zamanda alan içerisinde yer alan kişiler tarafından icra edilen \nbilimin de belirli esas ve yöntemlere göre yapılmasına yardımcı olabilmektedir. Sanat \ntarihinin kendi bilimsel tarihi göz önünde bulundurulduğu vakit bu konu saha \niçerisinde pek fazla araştırılmamakta ve hatta önemsenmemektedir. ‘’Türkiye’de Sanat \nTarihi Disiplininin Analizi ve Değerlendirilmesi’’ adlı yüksek lisans tezi bu bağlamda \nele alınan problemlere yanıt vermeye çalışmasının yanı sıra güncel durumuna yönelik \nçeşitli veriler sunmaktadır.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.008 |
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".