Kilka refleksji metodycznych o badaniach architektury w historii sztuki
Bibliographic record
Abstract
The article reviews the current situation and trends in research in the field of the history of architecture. Various research methods are used, including traditional ones, which produce excellent results, and modern ones that have emerged relatively recently due to revolutionary technological progress. Among the latter, the use of modern measurement and analytical techniques that provide new data for interpretation is particularly fruitful. Based on examples of research from the last quarter of a century, excellent progress has been noted in research based on both the latest technologies and those based on the use of updated traditional tools. Modern techniques and methods do not render traditional methods (such as the comparative or genetic method) obsolete, but supplement them by providing substantial new data, which allows them to be used in a more precise way. A collection of many data (observation statements) alone is not an explanation. It should be organized in the form of a theory, statements that answer the basic question: Why is it like this and not different? In the case of art history, this is called interpretation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".