On Belief and the Making of All Things Beautiful and Sublime: Creation by Ordinance and Destruction by Chaos
Bibliographic record
Abstract
This is a study of beauty as a construct and a property of structural composition. I examine alternate possibilities of structural compositions, linguistics, or material arguments that beauty, impossible in utter chaos, might not be definitely found in order, but the latter is essential thereto. A distinction is also made between complex systems of order found in nature, often qualified as organic—the seemingly free and flowing forms found in formal sophistication beyond simple geometrical reduction—and the absence of order as pure chaos. Beauty is examined through order from historical linguistic, perceptual, and systemic constructivist perspectives, along with the sublime and the harmonious. Linguistically, order is a term of convergence of the seemingly disparate streams of significance of rank—in society, religion, and the belief in collective constants—and ornament is a term of bearing beauty and enhancement of taste that emanates from within the structure and should not be reduced to superficial application. I cite costume, including accessories of weaponry, as moments of proximity between style, purpose, utility, and the collective as semiotic bearer of meaning in culture and social order.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".