From English to Tok Pisin: A Sociolinguistic Inquiry of Gender Preference in the New Testament Bible Translation
Bibliographic record
Abstract
Sexist language in religious texts can be meaningfully explored through the combined perspectives of sociolinguistics and translation studies. Sociolinguistics helps uncover how gendered language reflects and reinforces social norms and power dynamics, while translation studies examine how these patterns are maintained, altered, or challenged when texts are translated into other languages. Together, these approaches offer a deeper understanding of how gender bias is embedded and transmitted through sacred texts. This study examines how gendered terms from the New English Translation (NET) Bible are rendered in the Tok Pisin Buk Baibel (TPBB), focusing on the representation, translation techniques, and shifts in gendered language. In Papua New Guinea (PNG), where Tok Pisin serves as a lingua franca, biblical translations significantly influence cultural perceptions of gender. Despite widespread discussions on gender bias in major languages, limited attention has been given to Tok Pisin Bible translations. Using a qualitative approach, the study analyzed 629 gendered language instances from the Four Gospels of the NET Bible and their Tok Pisin equivalents. Findings of this study revealed that 35.77% of the linguistic data in the form of overt sexism were gender-neutral, 32.75% masculine, and 31.48% feminine. However, 57.52% of originally neutral terms shifted to masculine in Tok Pisin, revealing a gender bias. Masculine terms were preserved in 71.84% of cases, while 87.88% of feminine terms were retained. Translation techniques favored Established Equivalence, while Particularization was common in neutral terms. Quality assessments indicated high readability and acceptability, though accuracy was lower for neutral terms (average score: 2.23). Overall, this study underscores a prevailing tendency toward male-centric translation patterns commonly referred to as the patriarchal standard in the Tok Pisin Buk Baibel, despite efforts at inclusivity. These findings highlight the sociolinguistic impact of translation choices on gender representation in religious texts.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".