“Utux Tmninun U, ini sruwa muway pusu dnui rudan sunan ka hiya”: Reading Naboth’s Refusal (1 Kings 21:3) from the Sediq Mother Tongue
Bibliographic record
Abstract
Since the advent of the vernacular Bibles for the Taiwan Indigenous Peoples (TIP), the TIP Christians are privileged to read and hear the Word of God in their ‘ancestral tones’ with familiarity and attachment. Sediq people, the nation the author belongs to, have also been privileged from the publication of the vernacular Bible. Most Sediq people are welcoming this vernacular Bible and feel blessed to use their ancestor’s language to communicate with God. However, the scarcely discussed issues are that the biblical reading and interpretive approaches employed by the Sediq people are distinctive. Namely, Sediq people’s vernacular involves Sediq’s cultural resources-philology, traditional narratives, traditional stories, cultural meanings, traditional philosophies and worldviews-into the interaction with the contents and stories of the vernacular Bible. This paper argues the significance of embracing vernacular as a foundation for biblical reading, how this acceptance shifts the role of the vernacular Bible and how this approach contributes to the contextual, decolonial and postcolonial reflections on the TIP’s land issues by reading 1 Kings 21:3, one of the verses that resonating TIP’s ancestral and cultural wisdom. Keywords: Sediq People, Taiwan Indigenous Peoples, land issues, ancestral philosophies
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".