diff options
Diffstat (limited to 'working/voice-term-density/profile.diff')
| -rw-r--r-- | working/voice-term-density/profile.diff | 36 |
1 files changed, 36 insertions, 0 deletions
diff --git a/working/voice-term-density/profile.diff b/working/voice-term-density/profile.diff new file mode 100644 index 0000000..3134ebf --- /dev/null +++ b/working/voice-term-density/profile.diff @@ -0,0 +1,36 @@ +--- voice/references/voice-profile.org 2026-07-23 23:24:57.119185940 -0500 ++++ /tmp/profile.proposed 2026-07-23 23:29:48.169642034 -0500 +@@ -1611,3 +1611,33 @@ + + *** History + - 2026-07-23: added from the home session drafting a Signal reply. The first handoff proposed two new patterns and flagged a conflict with §43; the superseding design resolved that the conflict was a misreading of §43 (angle = topic), leaving one genuinely new pattern here and a calibration to §43. Prose/correspondence-scoped per Craig — email and Signal are prose, not publish artifacts. ++ ++** §48 Term-Translation Density ++ ++*** Modes ++General mode, so it runs in all three (general, prose, personal). It's a universal clarity rule in the Orwell / Plain English family, not a Craig-voice trait, and it reads to anyone editing any prose. The later number is an artifact of when it was added, not a scope signal. ++ ++*** Rule ++A sentence that forces the reader to stop and translate more than one specialized term (an acronym, a coined phrase, a product name) is too dense. One is fine; two or more in one sentence means rewrite: split the sentence, gloss one term in a parenthetical, or drop to plain language. The test is the reader's parse, not the writer's familiarity, and it is audience-relative. ++ ++*** Problem ++A writer fluent in the domain doesn't feel the translation cost of the terms, so a sentence stacking three of them reads as normal to the author and stalls the reader on every clause. Density is the metric, not any single word: two coined terms in one sentence is worse than a paragraph that introduces the same two one at a time. Audience-relative, because SAR to a defense team is shared vocabulary carrying no load, while a coined phrase only the writer holds carries full load for everyone else. ++ ++*** Basis ++Craig's edit of a customer-partner email, 2026-07-23 (work session), where one sentence stacked three terms and he flagged it. Distinct from #7 (specific AI-vocabulary words) and #30 (telegraphic fragments); this measures jargon density per sentence. ++ ++*** Before (one sentence, three terms the reader must translate) ++#+begin_example ++A ViT detector gating a VLM for enrichment is close to our own detect-then-contextualize direction. ++#+end_example ++ ++*** After (split, glossed, plain) ++#+begin_example ++Their setup is a fast detector that hands off to a heavier model for a closer read. That mirrors our own two-stage approach (find it first, then work out what it is). ++#+end_example ++ ++*** Detection ++Count the specialized terms in each sentence that a member of the intended audience would have to stop and translate. Two or more is the trigger. Acronyms, coined phrases, and product names count; shared-vocabulary terms for that audience don't. ++ ++*** History ++- 2026-07-23: proposed by Craig from the work session, drafting a customer-partner email. Placed in general mode (universal clarity rule); numbered #48, after the prose-only #47. |