Bibliographic record
Abstract
Issues involving the deep and plain kens arose in the construction of temples, between the need to create a structure in normal spacetime and the need to imbue that structure with symbolic resonance. This chapter shows how prominent temples such as the Church of the Nativity, the Mosque of the Cradle, and the Church of the Holy Sepulchre drew meaningful connections with key points in Jesus's life. At the same time, pilgrims, real or would-be, became interested in the plain-ken specifics of the contemporary Holy Land. This plain-ken interest of the actual spatial dimensions of the Holy Sepulchre, for example, was balanced by a deep-ken interest in geometrical perfection. Attention on the tomb itself was part of a broader plain-ken attention to Jerusalem's metrics, which predated, but peaked in, our period. This plain-ken love for precise, if ugly, measurements existed in a deep-ken space where the original tomb consonated with scale copies re-created across Europe. Inscriptions played a particularly important role in Islamic architecture, including Jesus references encircling the Dome of the Rock in Jerusalem and the Minaret of Jam near Kabul.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".