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Cleanup prose in written documentation

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Aaron Po
2026-08-31 17:23:46 -04:00
parent f28f188a54
commit 30995f6f40
9 changed files with 141 additions and 113 deletions
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docs/pipeline/ETHICS-AND-KNOWN-ISSUES.md
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@@ -47,7 +47,7 @@ as a source of truth for brewing techniques or cultural representation.**
**Natural language processing is a powerful tool for data analysis and
generation, but its output should be treated with scrutiny. Human language is
not simply data points to be analyzed — it carries cultural and human meaning
not simply data points to be analyzed: it carries cultural and human meaning
that artificial intelligence cannot capture.**
---
@@ -102,7 +102,7 @@ vendored verbatim, unmodified, from
(the `common-forenames-by-country.json` / `common-surnames-by-country.json`
release assets), released under **CC0** (public domain). That dataset's own
forename/surname lists are pulled from Wikipedia's "Lists of most common
surnames" and "List of most popular given names" as of the week of 2023-07-08 —
surnames" and "List of most popular given names" as of the week of 2023-07-08;
see that project's README for full provenance. Names are not LLM-generated; this
is curated fixture data per ROADMAP.md §2. Per-forename gender from the source
data is preserved through to the sampled `Name` (rather than discarded during
@@ -113,7 +113,7 @@ for surnames) rather than trimmed to `locations.json`'s current country list, so
it doesn't need re-sourcing if more countries are added later. `SampleName()` (a
free helper in `generate_users.cc`) returns no result for a country present in
neither file; of the countries in `locations.json`, that's currently `KE`, `SE`,
`SG`, `TH`, `VN`, and `ZA` — `GenerateUsers` skips cities in those countries the
`SG`, `TH`, `VN`, and `ZA`; `GenerateUsers` skips cities in those countries the
same way brewery generation skips cities whose enrichment lookup fails.
---
@@ -290,8 +290,8 @@ Each brewery and user address carries a longitude/latitude pair, sampled
uniformly at random within a 5 km disc centred on the city's curated
`latitude`/`longitude` from `locations.json`.
The resulting point is **plausible by construction** — it always falls within
the city's vicinity — but it is not looked up from any real address registry.
The resulting point is **plausible by construction**, always falling within
the city's vicinity, but it is not looked up from any real address registry.
It does not correspond to a real address, business, or resident, and should
not be treated as accurate geocoding data. This is consistent with the rest of
the dataset: fixture data for a proof-of-concept, not a source of truth.