Translation profiles
What profile does each translation show across the frozen constructs?
Scripture Leaf · Translation Study
A source-aware comparison of BSB, ESV, NASB 2020, CSB 2020 and NIV 2011 across a frozen 160-passage corpus, reviewed independently by two AI systems. Translation dimensions are kept separate rather than collapsed into one accuracy score.
The challenge corpus deliberately concentrates difficult translation problems. Results describe this corpus; they are not whole-Bible prevalence estimates. AI Reviewer A and AI Reviewer B remain separate throughout. Agreement is a robustness signal; disagreement is reviewer sensitivity, not a penalty against a translation.
Study map
What profile does each translation show across the frozen constructs?
What kinds of semantic, grammatical, ambiguity and explicitness choices appear?
How do observed profiles sit alongside each publisher's own stated philosophy?
How do patterns look within eight prospectively frozen challenge categories?
When translations materially differ, how does each reviewer classify the cause?
No overall translation rank was created. No composite accuracy score, weighted winner or clarity-fidelity blend was created.
In plain English
Across the five translations and two independent AI reviewers, semantic-preservation rates on the frozen semantic opportunities sit in a relatively narrow band of about 89–94%. The study does not support a simple faithful-versus-unfaithful split among these five versions.
The versions separate more in how they express meaning: grammatical restructuring, explicitness, ambiguity, lexical choices and English style. Those differences are real, but more literal or more explicit is not automatically better.
BSB falls within the same broad semantic-preservation range as ESV, NASB, CSB and NIV and receives many high English-clarity ratings. The relationship view below places its translation-choice profile closer to CSB and NIV than to ESV or NASB under this post-hoc descriptive measure.
The two independent AI reviewers often agree on broad semantic, morphosyntactic and lexical groupings, but differ more on exact clarity scores and some subtle cause judgements. The study treats that as uncertainty rather than deciding that one reviewer is right.
Scope matters. These conclusions describe a deliberately difficult 160-passage study corpus. They are not whole-Bible percentages and they do not identify a best translation.
Study corpus
The frozen corpus contains 120 deliberately difficult challenge passages and 40 controls. Each reference below opens BibleHub at the first verse of the study passage; ranges continue from that starting point.
Post-release descriptive extension
These matrices are derived only from the already-frozen study data. They were not part of the original measurement instrument, so they are presented as a transparent post-hoc descriptive view rather than a confirmatory finding. Similarity here means a similar distribution of recorded study outcomes; it does not mean identical wording, common editorial ancestry, or higher quality.
Semantic representation (SEM), morphosyntax, explicitness, ambiguity, intertextual visibility and lexical continuity; equal weight by construct.
| Version | BSB | ESV | NASB | CSB | NIV |
|---|---|---|---|---|---|
| BSB | 100%same translation | 87.4–87.7%reviewer range | 85.8–86.0%reviewer range | 91.2–92.2%reviewer range | 88.8–91.3%reviewer range |
| ESV | 87.4–87.7%reviewer range | 100%same translation | 86.9–89.3%reviewer range | 83.8–87.1%reviewer range | 79.2–81.1%reviewer range |
| NASB | 85.8–86.0%reviewer range | 86.9–89.3%reviewer range | 100%same translation | 82.5–90.0%reviewer range | 82.3–83.4%reviewer range |
| CSB | 91.2–92.2%reviewer range | 83.8–87.1%reviewer range | 82.5–90.0%reviewer range | 100%same translation | 87.6–87.9%reviewer range |
| NIV | 88.8–91.3%reviewer range | 79.2–81.1%reviewer range | 82.3–83.4%reviewer range | 87.6–87.9%reviewer range | 100%same translation |
Syntactic clarity, referential clarity and idiomatic naturalness; equal weight by clarity dimension.
| Version | BSB | ESV | NASB | CSB | NIV |
|---|---|---|---|---|---|
| BSB | 100%same translation | 76.5–87.3%reviewer range | 75.8–79.4%reviewer range | 85.2–90.0%reviewer range | 89.6–92.3%reviewer range |
| ESV | 76.5–87.3%reviewer range | 100%same translation | 90.0–93.8%reviewer range | 81.0–89.2%reviewer range | 71.9–82.7%reviewer range |
| NASB | 75.8–79.4%reviewer range | 90.0–93.8%reviewer range | 100%same translation | 81.0–85.8%reviewer range | 71.5–74.4%reviewer range |
| CSB | 85.2–90.0%reviewer range | 81.0–89.2%reviewer range | 81.0–85.8%reviewer range | 100%same translation | 83.8–84.6%reviewer range |
| NIV | 89.6–92.3%reviewer range | 71.9–82.7%reviewer range | 71.5–74.4%reviewer range | 83.8–84.6%reviewer range | 100%same translation |
Each off-diagonal cell shows the range between AI Reviewer A and AI Reviewer B rather than averaging them. For each reviewer separately, similarity is calculated as 1 minus total-variation distance between the two translations' normalised outcome distributions. The translation-choice matrix gives equal weight to six already-frozen constructs; the clarity matrix gives equal weight to the three already-frozen clarity dimensions. A higher percentage means the two profiles behaved more similarly on this corpus; it is not an accuracy score.
RQ1 + RQ2
The cards stay in the frozen display order: BSB, ESV, NASB, CSB, NIV. Percentages are construct-specific descriptive rates, not an overall quality score.
Two independent reviewer-system profiles. Display order is fixed and is not a ranking.
English clarity distributions1 lower · 5 higher · no mean calculated
English clarity distributions1 lower · 5 higher · no mean calculated
Counts describe how the frozen instrument classified choices. More explicit, more literal or more repetitive is not automatically better.
Two independent reviewer-system profiles. Display order is fixed and is not a ranking.
English clarity distributions1 lower · 5 higher · no mean calculated
English clarity distributions1 lower · 5 higher · no mean calculated
Counts describe how the frozen instrument classified choices. More explicit, more literal or more repetitive is not automatically better.
Two independent reviewer-system profiles. Display order is fixed and is not a ranking.
English clarity distributions1 lower · 5 higher · no mean calculated
English clarity distributions1 lower · 5 higher · no mean calculated
Counts describe how the frozen instrument classified choices. More explicit, more literal or more repetitive is not automatically better.
Two independent reviewer-system profiles. Display order is fixed and is not a ranking.
English clarity distributions1 lower · 5 higher · no mean calculated
English clarity distributions1 lower · 5 higher · no mean calculated
Counts describe how the frozen instrument classified choices. More explicit, more literal or more repetitive is not automatically better.
Two independent reviewer-system profiles. Display order is fixed and is not a ranking.
English clarity distributions1 lower · 5 higher · no mean calculated
English clarity distributions1 lower · 5 higher · no mean calculated
Counts describe how the frozen instrument classified choices. More explicit, more literal or more repetitive is not automatically better.
English clarity
The study scores syntactic clarity, referential clarity and idiomatic naturalness from 1–5. The public package deliberately does not calculate a clarity mean or combine clarity with source-relative fidelity. The distributions above let you see, for example, how BSB performs in English without turning readability into an accuracy bonus.
RQ3
Philosophy was added only after the result layer was frozen. It is descriptive context, not a quality proxy and not a causal explanation for the measured outcomes.
modern English study translation
The Berean Bible describes the BSB tier as a modern-English study translation and places it within a transparent multi-tier process linked to the original languages. Its official material says the BSB aims to maintain core meanings while producing high-literary-quality English, and the wider tier system is intended to preserve access to both word-for-word and thought-for-thought renderings where languages do not map one-to-one.
essentially literal
Crossway describes the ESV as essentially literal: it seeks close correspondence to original wording and writer style while accounting for differences in grammar, syntax and idiom, and it explicitly describes translation as involving trade-offs between literal precision and readability.
formal equivalence
The Lockman Foundation describes the NASB as a formal-equivalence translation that seeks word-for-word correspondence from the original languages as far as possible while recognising the need for readable, understandable English. For NASB 2020 it states that the longstanding standard remains while language, vocabulary, grammar and sentence structure were modernised to improve clarity and readability.
optimal equivalence
Official CSB material describes optimal equivalence as pursuing linguistic precision to the original languages together with contemporary-English readability. It states that word-for-word rendering is used where it communicates clearly, while more dynamic rendering may be used where a word-for-word construction would obscure meaning.
balanced approach
Biblica describes the NIV approach as balancing transparency to the original with clarity of meaning in contemporary English. Its stated goal is accurate communication in clear, natural English rather than mechanically preserving source-language form or moving so far from form that source nuances are unnecessarily lost.
RQ4
Each challenge stratum contains 15 passages. The 40 controls remain a separate control cohort, not a ninth stratum.
RQ5
AI Reviewer A classified 17 primary material differences and AI Reviewer B 7; their cause distributions also differ substantially. The study therefore does not average them or publish a consensus claim about which cause predominates.
Reviewer sensitivity
The two AI reviewer estimates remain separate. Differences between reviewer systems are sensitivity evidence and are not averaged, adjudicated or converted into translation penalties.
Evidence
These are deterministic examples from predeclared construct cells, not a list of the “worst” passages or examples selected to favour one translation. Restricted translation wording is not reproduced; each case links to BibleHub for comparison.
Represent the semantic content carried by the frozen source-language units for the primary span Deuteronomy 28:61; functional English restructuring is permitted and formal correspondence is not required.
Represent the semantic content carried by the frozen source-language units for the primary span 2 Samuel 5:7; functional English restructuring is permitted and formal correspondence is not required.
Represent the semantic content carried by the frozen source-language units for the primary span 1 Samuel 2:19; functional English restructuring is permitted and formal correspondence is not required.
Represent the semantic content carried by the frozen source-language units for the primary span Ruth 2:16; functional English restructuring is permitted and formal correspondence is not required.
The singular collective ha-adam is followed by male/female and plural pronouns; English must move between humanity person and plural human beings
The rare noun ason in the injury law is crucial to whether the harm refers to the woman child or any fatal injury
Nacham spans regret relent comfort and change-of-course senses and here occurs in a denial of divine human-like changing
Ancient witnesses preserve a substantially longer form of Saul's prayer for the sacred lot
Assess interpretive explicitness against the complete frozen source evidence for this passage; greater explicitness is descriptive and is not automatically better or worse.
This RQ5 example shows how a material pair difference was classified without publishing restricted target wording.
Glossary
Method and limits
120 passages deliberately concentrate recognised translation challenges; 40 controls provide contrast. This design supports stress-testing, not whole-Bible prevalence claims.
Two AI systems independently reviewed the frozen instrument. Their outputs are labelled AI Reviewer A and AI Reviewer B on this page and are not averaged or adjudicated into a single reviewer.
Semantic representation, morphosyntax, explicitness, ambiguity, lexical continuity, intertextual visibility, reader disclosure and English clarity answer different questions.
The study does not identify a best translation, create an overall accuracy percentage, or replace expert human textual and translation scholarship.
The similarity matrices were added after the study results were frozen. They reuse frozen outcome distributions only, keep reviewer estimates separate as a displayed range, do not alter any study score, and must not be read as a new quality ranking.
Reproducibility
The public package contains no restricted target wording and no private blinded target identifiers. Historical V1 research files remain retained separately in the repository.