Bibliographic record
Abstract
Abstract When Paul says ‘Israel’, what or whom does he have in mind? Christian theological tradition has long answered that by ‘Israel’, a universalist Paul means ethnically non-specific ‘Christians’. But a great deal of evidence in Paul’s letters weighs against such an idea. This chapter examines, in turn, the modern myth of a post-ethnic Paul, ancient ideas about divine and human ethnicity, Paul’s language about Jewish and gentile ‘natures’, Paul’s language about Jewish and Gentile kinds of sins, Paul’s application of different Jewish laws to Jews and Gentiles, respectively, and finally Paul’s actual usage of the ethnonyms ‘Jew’ and ‘Israel’. It is concluded that, for Paul, Jews are Israel, and Israel, his own family, is the Jews. God, through Christ, at the end of the ages (mid-first century ce), was graciously calling all humanity into the redemption that he had promised to Israel long ago. Eschatological humanity thus remains two different people groups—Israel and the nations—embraced by a single salvation.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".