Acts of Impropriety: The Imbalance of History and Theology in Luke-Acts
Bibliographic record
Abstract
Jews and Christians both have Scripture. Likewise, they both have a number of different traditions of interpretation for these texts. And, unfortunately, they also use and have used their Bibles as history books so as to establish the historical foundations of their respective faith communities. Even more upsetting is the fact that these biblical histories of faith communities continue to be taken more or less literally — even after the recent revolution in our understanding of historiography has enabled us to develop a new historical consciousness. We know that written histories contain both truth and falsehood, that history can be distorted or even falsified, and that such manipulations are capable of being discovered. Eyewitnesses most easily distinguish truth and falsehood, of course. As we go further back in time and the number of perspectives from which events are perceived increases, it becomes more difficult to distinguish between objective reporting and wilful or even unconscious "management" of the facts. In more than a few cases it may be impossible to know precisely what happened. Since no one can write entirely objective history, we must be ever alert to identify ideology when it plays a recognizable role. Since we are aware that history is manipulated even now in a world teeming with information, it seems to me entirely legitimate to begin with the assumption that in times when sources were few and less easily tested, history must have been even more commonly manipulated—and more thoroughly.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.064 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| 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".