"Where your treasure is, there your heart will be also" : narrative, ethics, and possessions in Luke-Acts
Bibliographic record
Abstract
This thesis is a project in narrative New Testament ethics. It offers a fresh reading of the material in Luke-Acts that concerns wealth and possessions, beginning with two primary premises, which are developed in Part 1: (1) The descriptive and synthetic activities traditionally accorded to New Testament ethics are not fully separable from the hermeneutical and pragmatic concerns usually considered the domain of theological ethics. (2) The conceptualizations of the moral life readers bring with them to the biblical text will influence the reading strategies they employ and thus the critical readings that result. Based on these premises, this thesis reads Luke-Acts with a contemporary, pragmatic ethical question in view, "What attitudes, dispositions, and practices should members of Christian communities in North America at the beginning of the third Christian millennium adopt in an environment of personal and societal affluence, capitalist consumerism, and economic globalization?" Furthermore, it approaches Luke-Acts in terms of a narratively-based ethics of character, based on the work of Alasdair Maclntyre and Stanley Hauerwas. A concluding chapter in Part 1 locates Luke's narrative moral discourse within the moral discourse of narrative literature in New Testament literary environment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".