Bibliographic record
Abstract
Passio, is Arvo Pärt’s first large scale vocal-instrumental work in the tintinnabuli style and remains today one of his most significant compositions. In this setting of the Passion text according to St. John, Pärt codifies procedures of tintinnabuli that will remain his principle means of musical communication for years to come while implying a very important perspective of Johannine theology. His compositional design utilizes both small-scale and large-scale chiastic constructions and gives prominence to John’s observance in Chapter 18, verse 4, that Christ knows all that will occur in the events leading to his crucifixion. Seen in this light, the Passion narrative unfolds according to a pre-ordained plan; it is this subtle perspective of the Gospel that Arvo Pärt reveals musically in his Passio. This paper approaches a musical analysis of Passio in relation to John’s perspective that Christ knew all that was to follow. It illustrates that virtually every note is linked in some way to Pärt’s musical pilgrimage to the cross. With a microscopic lens, the analysis connects Pärt’s use of melody, texture, inversion and tintinnabuli to a poignant marriage of music and the biblical text. And on a macroscopic level, it is shown that musical events unfold over time to reveal the inevitability of the crucifixion. It is revealed that within the work’s tonal centres, large-scale textural procedures, pedal points and the music of the Exordium and Conclusio the path to the cross is present from beginning to end. In this way, the listener is taken through the narrative only to realize afterward that the Gospel’s outcome was present from beginning to end.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".