Bibliographic record
Abstract
Anyone who works on a subject over a period of more than twenty years owes many debts of gratitude. It was in 1971 in his ‘Theological Controversies’ course at Harvard Divinity School that Arthur McGill proposed that we should study the subject of justification on the one hand in Luther, on the other at Trent. I believe that I was immediately captivated. (The second-hand copy of John Dillen-berger's Selections from Luther's writings – which I bought thinking I should only need it for a week – is still with me and in dilapidated condition.) When some years later I came to write a doctoral thesis I had no doubt as to what the topic should be (though I had some difficulty in convincing my teachers). Then there was a day when Arthur McGill asked how Kierkegaard related to all this. I replied, as though it was self-evident, that his was the best solution I had encountered in the history of Western thought to the split between Catholic and Lutheran. ‘There’, he said, ‘is your thesis’.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".